Article

How I reduce fuel consumption: An experimental study on mental models of eco-driving

February 2015
Transportation Research Part C Emerging Technologies 58(1)

DOI:10.1016/j.trc.2015.02.005

Project: ecoDriver

Authors:

Sanna M. Pampel

University of Nottingham

Samantha Jamson

University of Leeds

Daryl L. Hibberd

University of Leeds

Yvonne Barnard

University of Leeds

Eco-driving has the potential to reduce fuel consumption and therefore emissions considerably. Previous research suggests that drivers have a certain level of eco-driving knowledge and skills, which they refrain from practising in their everyday lives. At the same time misconceptions and ambiguous messages from eco-driving support systems can confuse and demotivate. This research aimed to identify the mental models of eco-driving that regular drivers have. A driving simulator experiment with a varied road layout comprising urban and motorway sections was designed. The study used simple driving task instructions to investigate changes in the participants’ behaviour and thoughts in three conditions. Sixteen drivers were asked to ‘Drive normally’, ‘Drive safely’ or ‘Drive fuel-efficiently’. Behavioural measures, think aloud protocols and interviews were compared and analysed. The emphasis of this study was on eco-driving relevant indicators such as accelerating, braking, coasting and car-following. The results show that the participants do have mental models of eco-driving, which they did not use in the Baseline drive, when they were instructed to ‘Drive normally’. Misconceptions about speed and travel time provide the potential for more effective communication with the driver about the momentary efficient speed as well as resulting time losses and fuel savings. In addition, in-vehicle guidance can increase driving safety compared to practicing eco-driving without them.

Environmental, altruistic, or monetary benefits? A longitudinal online experiment on how framed behavioral consequences affect self-reported eco-driving of German vehicle owners

Article

Feb 2023

How does eco-driving make us feel? Considering the psychological effects of eco-driving

Article

May 2022
APPL ERGON

Despite both the environmental and financial benefits of eco-driving being well known, the psychological impact of engaging in eco-driving behaviours has received less attention within the literature. It was anticipated that being asked to engage in eco-driving behaviours not only has an impact on vehicle fuel usage, but also on the driver, both in terms of their overall mood and willingness to re-engage with the task at a later time. Results from a simulated driving study suggest that although eco-driving was beneficial in reducing fuel consumption, being asked to eco-drive had a negative effect on overall journey time and mood. Engaging in eco-driving did however have a positive effect on self-esteem, suggesting potential longer term psychological benefits of adopting this behaviour.

Adjusting the need for speed: assessment of a visual interface to reduce fuel use

Article

Full-text available

Oct 2020

Previous research has identified that fuel consumption and emissions can be considerably reduced if drivers engage in eco-driving behaviours. However, the literature suggests that individuals struggle to maintain eco-driving behaviours without support. This paper evaluates an in-vehicle visual interface system designed to support eco-driving through recommendations based on both feedforward and feedback information. A simulator study explored participants’ fuel usage, driving style, and cognitive workload driving normally, when eco-driving without assistance and when using a visual interface. Improvements in fuel-efficiency were observed for both assisted (8.5%) and unassisted eco-driving (11%), however unassisted eco-driving also induced a significantly greater rating of self-reported effort. In contrast, using the visual interface did not induce the same increase of reported effort compared to everyday driving, but itself did not differ from unassisted driving. Results hold positive implications for the use of feedforward in-vehicle interfaces to improve fuel efficiency. Accordingly, directions are suggested for future research. Practitioner Summary: Results from a simulator study comparing fuel usage from normal driving, engaging in unassisted eco-driving, or using a novel speed advisory interface, designed to reduce fuel use, are presented. Whilst both unassisted and assisted eco-driving reduced fuel use, assisted eco-driving did not induce workload changes, unlike unassisted eco-driving. Abbreviations: CO2: carbon dioxide; NASA-TLX: NASA task load index; RMS: root-mean-square; MD: mean difference

Classification and Study of Impacts on Fuel Economy of Heavy-duty Vehicles

Thesis

Full-text available

Aug 2017

The demand of fuel consumption in transportation sector is increasing and will continue to increase even with the advances in technology. The rising prices of fuel in transportation operations have drawn the attention of the logistics managers to control and reduce the amount of fuel used in either way. The drivers are an important component of the transportation sector who contribute a major role in fuel-saving options. The study of the driver’s motivations, strategies and driving patterns on fuel consumption and fuel-control has become inevitable to explore. A multi-dimensional approach to identify extra fuel usage, drivers’ intensions to comply with fuel-saving behaviors, and modeling of fuel consumption based on driving patterns of heavy-duty vehicles is requisite of the time to explore the multi-fold dimensions related with fuel consumption in transportation sector. This thesis consists of mainly three parts. In the first part, a fuel management policy is proposed to classify cases of extra fuel consumption to accurately identify the blamed-party who is responsible for extra fuel consumption. An Incident Scenario Matrix Approach (ISMA) is designed with three main blamed-parties; self-blame, other-blame and circumstance-blame with definite factors as driving behavior, driving conditions, vehicle and accessibility to classify extra fuel consumption cases in logistics firms working with fixed fuel policy. This study can be used as a milestone as a fuel policy for logistics firms working with similar fuel control policies. In the second part, eco-driving motivations of Thai drivers to adopt ecodriving behaviors are observed according to their marital status and education level. The response is recorded in self-scoring fashion with three different goals (1) changing driving behaviors to become eco-drivers after necessary information about eco-driving (2) adopting eco-driving behaviors when they are asked to be in competition with fellow drivers, (3) and impacts of reward or penalty system on their behavioral response to act as eco-drivers. Correlation and ANOVA testing are performed to find the best combination of motivational goals to become eco-driver in different goals and change in behavioral response. The difference in behavioral response is also calculated to check if it is statistically significant or not. Results showed that young and educated drivers manifested strong motivations to become eco-driver in given contextual goals. In the last part, impacts of driving patterns of heavy-duty vehicle drivers on fuel-consumption are discussed. The parameters which are included in driving styles are; distance travelled, instantaneous speed, speed profiles, braking patterns, accelerating patters, and engine idle time. Three different kinds of trucks are included in the study to observe the effects of defined parameters on fuel consumption. The attempts to develop regression modals with acceptable R2 value and p-value are made to observe the impacts of these parameters on fuel-consumption in real-world driving conditions.

Self-reported inclination of heavy-duty vehicle drivers to adopt eco-driving in different motivation contexts

Article

Full-text available

Mar 2019

Eco-driving is an emerging field of research. Due to its positive dimensions on fuel-economy and environmental emissions, it is becoming a well-known concept in transportation industry. Behavioral responses of drivers’ readiness to adopt eco-driving are studied. Questionnaires are collected from 87 truck drivers working for a logistics firm in Thailand. Eco-driving was introduced using three different strategies; changing driving behavior, competition with fellow drivers, and reward or penalty systems. A five-point Likert scaling system is adopted to record their self-evaluation scoring to practice eco-driving in given contextual motivations. Results are reported in the form of eco-driving scores and Statistical evaluations to check if the difference in behavioral response is statistically significant. Statistically significantly different results showed that in-relationship (score 3.75) and high school drivers (score 4.38) manifested strong motivations in penalty or reward systems while high school drivers exhibited great inclinations in changing their driving behavior (score 3.89).

Old habits die hard? The fragility of eco-driving mental models and why green driving behaviour is difficult to sustain

Article

Feb 2018
TRANSPORT RES F-TRAF

Tangible incentives, training and feedback systems have been shown to reduce drivers’ fuel consumption in several studies. However, the effects of such tools are often short-lived or dependent on continuous cues. Several studies found that many drivers already possess eco-driving mental models, and are able to activate them, for instance when an experimenter asks them to “drive fuel-efficiently”. However, it is unclear how sustainable mental models are. The aim of the current study was to investigate the resilience of drivers’ eco-driving mental models following engagement with a workload task, implemented as a simplified version of the Twenty Questions Task (TQT). Would drivers revert to ‘everyday’ driving behaviours following exposure to heightened workload? A driving simulator experiment was conducted whereby 15 participants first performed a baseline drive, and then in a second session were prompted to drive fuel-efficiently. In each drive, the participants drove with and without completing the TQT. The results of two-way ANOVAs and Wilcoxon signed-rank tests support that they drive more slowly and keep a more stable speed when asked to eco-drive. However, it appears that drivers fell back into ‘everyday’ habits over time, and after the workload task, but these effects cannot be clearly isolated from each other. Driving and the workload task possibly invoked unrelated thoughts, causing eco-driving mental models to be deactivated. Future research is needed to explore ways to activate existing knowledge and skills and to use reminders at regular intervals, so new driver behaviours can be proceduralised and automatised and thus changed sustainably.

Drivers’ self-perceptions about being an eco-driver according to their concern for the environment, beliefs on eco-driving, and driving behavior

Article

Nov 2017
TRANSPORT RES A-POL

Technological progress has allowed motorized transportation to make a step toward more sustainable mobility but remains one of the main causes of air pollution in France. One way to help reduce the detrimental impact of motorized road transportation is to lead drivers, particularly car-dependent ones, to adopt eco-driving. However numerous drivers do not abide by highway laws or display driving-anger behaviors, which are in opposition to eco-driving. Unfortunately, few people practice eco-driving and many new adopters often have trouble maintaining this driving style. What is more, most studies on this issue have focused on eco-driving gains, the ability of people to put it into effect, and/or the continuous decline in the number of people who practice eco-driving. They usually do not take into account people’s self-perceptions about their driving style, nor the associated beliefs. The aim of the present self-report study was twofold: identify drivers’ self-perceptions about being an eco-driver, and determine how these self-perceptions about being an eco-driver or not are linked to eco-driving-friendly behaviors, levers favoring eco-driving (concern for the environment), and brakes on eco-driving (driving anger and road violations), according to gender. An online survey was carried out with 300 French drivers (127 men) ages 19–83. In our sample, 11.3% of the drivers said they felt they were eco-drivers (G1); 50% said they feel trying to eco-drive (G2); 9.7% said they had never heard of eco-driving and 25% said they knew about eco-driving but didn’t do it (G3, felt they were not eco-driver), and 4% said they felt they had abandoned eco-driving (G4). The differences between the first three groups (G1 vs. G2/G3) were in line with their eco-driving self-perceptions: G1 had higher scores on three eco-driving-friendly behavior scale components and on environmental conservation, and lower scores on one factor of the driving-anger scale. Also in line with the groups’ eco-driving self-perceptions, G2’s scores were higher than G3’s scores on one eco-driving friendly behavior component. A gender-by-group interaction was found for G1 vs. G3 on one eco-driving friendly behavior component, with a larger increase in the men’s than the women’s scores on eco-driving self-perceptions. Finally, violation scores, once again, were higher for men than for women on the speed and anger subscales. The findings of this study are discussed with respect to improving eco-driving learning.

Effective and Acceptable Eco-Driving Guidance for Human-Driving Vehicles: A Review

Article

Full-text available

Jun 2022
Int J Environ Res Publ Health

Eco-driving guidance refers to courses, warnings, or suggestions provided to human drivers to improve driving behaviour to enable less energy use and emissions. This paper reviews existing eco-driving guidance studies and identifies challenges to tackle in the future. We summarize two categories of current guidance systems, static and dynamic, distinguished by whether real-world driving records are used to generate behaviour guidance or not. We find that influencing factors, such as the content of suggestions, the display methods, and drivers’ socio-demographic characteristics, have varied effects on the guidance results across studies. Drivers are reported to have basic eco-driving knowledge, while the question of how to motivate the acceptance and practice of such behaviour, especially in the long term, is overlooked. Adaptive driving suggestions based on drivers’ individual habits can improve the effectiveness and acceptance while this field is under investigation. In-vehicle assistance presents potential safety issues, and visualized in-vehicle assistance is reported to be most distractive. Given existing studies focusing on the operational level, a common agreement on the guidance design and associated influencing factors has yet to be reached. Research on the systematic and tactical design of eco-driving guidance and in-vehicle interaction is advised.

Effective and Acceptable Eco-Driving Guidance for Human-Driving Vehicles: A Review

Preprint

Full-text available

Mar 2022

Ecodriving guidance includes courses or suggestions for human drivers to improve driving behaviour, reducing energy use and emissions. This paper presents a systematic review of existing eco-driving guidance studies and identifies challenges to tackle in the future. A standard agreement on the guidance design has not been reached, leading to difficulties in designing and implementing eco-driving guidance for human drivers. Both static and dynamic guidance systems have a great variety of guidance results. In addition, the influencing factors, such as the suggestion content, the displaying methods, and drivers socio-demographic characteristics, have opposite effects on the guidance result across studies, while the reason has not been revealed. Drivers motivation to practice eco behaviour, especially long-term, is overlooked. Besides, the relationship between users acceptance and system effectiveness is still unclear. Adaptive driving suggestions based on drivers habits can improve the effectiveness, while this field is under investigation.

Individual Variable Speed Limit Trajectory Control Considering Stochastic Arriving Patterns

Preprint

Full-text available

Jan 2022

Connected vehicles enabled by communication technologies have the potential to improve traffic mobility and enhance roadway safety such that traffic information can be shared among vehicles and infrastructure. Fruitful speed advisory strategies have been proposed to smooth connected vehicle trajectories for better system performance with the help of different carfollowing models. Yet, there has been no such comparison about the impacts of various carfollowing models on the advisory strategies. Further, most of the existing studies consider a deterministic vehicle arriving pattern. The resulting model is easy to approach yet not realistic in representing realistic traffic patterns. This study proposes an Individual Variable Speed Limit (IVSL) trajectory control problem at a signalized intersection and investigates the impacts of three popular car-following models on the IVSL. Both deterministic and stochastic IVSL models are formulated, and their performance is tested with numerical experiments. Results show that, compared to the benchmark (i.e., without speed control), the proposed IVSL strategy with a deterministic arriving pattern achieves significant improvements in both mobility and fuel efficiency across different traffic levels with all three car-following models. The improvement of the IVSL-Gipps’ model is the most remarkable. When the vehicle arriving patterns are stochastic, the IVSL improves travel time, fuel consumption, and system cost by 8.95%, 19.11%, and 11.37%, respectively, as compared to the benchmark without speed control.

Past behavior as a predictor of eco-driving practices: The case of a sustained intervention in a Mexican transportation company

Article

Jul 2021

Freight transportation is one of the main contributors to global CO2 emissions. In this article, we study the effect of eco-driving practices on fuel efficiency and CO2 emissions. We also explore the effect of a sustained intervention supporting eco-driving on the adoption of eco-driving practices among professional drivers. Transportation companies usually invest resources to train, coach, and reward drivers who practice eco-driving; therefore, our study aims to provide insights into the impact of these efforts. We conducted a comprehensive statistical analysis on data collected from 55 drivers in 150 trips, using GPS records (e.g., geolocation, speed, revolutions per minute) and direct observations, for one of the largest Mexican retailers that operates its own transportation fleet. Our results show that eco-driving contributes to fuel savings at an average of 27.8%, as indicated by the difference in consumption between the high-proficiency and medium-proficiency drivers and low-proficiency drivers, and an average reduction of 13 kg of CO2 per route.

Local determinants of driving behaviours: Installation Theory interventions to reduce fuel consumption among truck drivers in Colombia

Article

Full-text available

Jan 2021

Eco-driving has been linked to considerable reductions in negative externalities and costs for transportation companies, employees and communities (including fuel consumption, safety and emission benefits). Nevertheless, some of the biggest challenges to its implementation are related to promoting behavioural change among drivers. This paper presents the results of three behavioural field interventions that were successful to improve fuel efficiency in heavy freight transportation. The interventions brought further improvement even though the target company already had strong training, incentive, control and feedback procedures in place. The Installation Theory framework and the Subjective Evidence-Based Ethnography (SEBE) technique were used to systematically analyse determinants of driving behaviours, and to design cost-effective behavioural interventions based on social norms. The effects of three interventions were then tested using a pre-test post-test control group design among 211 drivers of the company. Results show significant decreases in average monthly fuel consumption of up to 4% in month 1 and up to 4.5% in month 3. Our findings show (with certain qualifications), that the Installation Theory framework and social norm interventions can be a cost-effective method to improve fuel efficiency in road freight transport companies, even when strong training, incentive, control and feedback procedures are already in place.

A systematic review of definitions of motor vehicle headways in driver behaviour and performance studies

Article

Feb 2021
TRANSPORT RES F-TRAF

Headway is a safety measure commonly used to investigate driving behaviour and driver performance. Its purpose is to reflect the following distance or time between a leading and following vehicle in traffic. It is therefore associated with drivers’ response time, such as in braking or swerving, during safety critical events. In the literature, distance and time headway are defined in different ways, despite standard definitions in the traffic engineering literature, which prompted this systematic review of headway definitions across a range of study designs, in order to recommend approaches to improve the accuracy and reproducibility of headway definitions used in road safety contexts. PRISMA guidelines were followed to search four databases (EMBASE, COMPENDEX, SCOPUS and MEDLINE) for studies that reported on headways or discussed methodological approaches. The search and filtering of abstracts identified 110 articles for a qualitative synthesis. Four broad approaches to measuring headways were detected: studies using simulation, roadside external features, on-road features, and on-vehicle features. Studies were coded as to whether they included written explanation, mathematical statements, or pictorial depictions of headway. Only 49.6% of studies contextualised headway sufficiently for reproducibility. Reproducibility is crucial for accurate interpretation of research findings and comparisons across studies. It is recommended that headway definitions should a) exclude vehicle or parts of vehicle lengths, b) include reference points (e.g., bumper/axle/rear), c) have a consistent terminology, and d) include the accuracy of headway measuring devices to report the precision of a study’s findings.

Modelling Eco-Driving Support System for Microscopic Traffic Simulation

Article

Full-text available

Dec 2019
J ADV TRANSPORT

Microscopic traffic simulation is an ideal tool for investigating the network level impacts of eco-driving in different networks and traffic conditions, under varying penetration rates and driver compliance rates. The reliability of the traffic simulation results however rely on the accurate representation of the simulation of the driver support system and the response of the driver to the eco-driving advice, as well as on a realistic modelling and calibration of the driver’s behaviour. The state-of-the-art microscopic traffic simulation models however exclude detailed modelling of the driver response to eco-driver support systems. This paper fills in this research gap by presenting a framework for extending state-of-the-art traffic simulation models with sub models for drivers’ compliance to advice from an advisory eco-driving support systems. The developed simulation framework includes among others a model of driver’s compliance with the advice given by the system, a gear shifting model and a simplified model for estimating vehicles maximum possible acceleration. Data from field operational tests with a full advisory eco-driving system developed within the ecoDriver project was used to calibrate the developed compliance models. A set of verification simulations used to illustrate the effect of the combination of the ecoDriver system and drivers’ compliance to the advices are also presented.

The golden rules of ecodriving? The effect of providing hybrid electric vehicle (HEV) drivers with a newly developed set of ecodriving-tips

Article

Jul 2019

To advance eco-driving skills in hybrid electric vehicle (HEV) drivers, and thus facilitate fuel efficient driving behavior, a set of 15 ecodriving-tips was developed and tested. In part 1, car owner manuals and telephone interviews with HEV expert ecodrivers were analyzed to extract ecodriving-related statements. As the owner manual statements were too generic to be used for the content generation of the ecodriving-tips, only their style was used for formulation purposes at a later stage. The interview statements were used for the content generation, and thus condensed into a concise set of 15 ecodriving-tips. This set was then formulated in three versions. Version 1 was based on the “no context, no details” formulation style extracted from the owner manuals. Version 2 and 3 were psychologically-grounded: Version 2 was based on the concept of implementation intentions, and therefore contained “if-then-plans”. For Version 3, these “if-then-plans” were coupled with technical explanations to additionally target the improvement of drivers’ mental models. Eventually, to ensure technical correctness, all three versions were reviewed by a HEV powertrain expert. In part 2, a longitudinal field study with two points of measurement was conducted to test the three versions in a randomized controlled design. For this, HEV drivers were recruited and randomly assigned to one of three groups. At baseline, each group received and evaluated a different version of the ecodriving-tips and was then asked to test the tips over the next 31 days. At follow-up, all groups, again, evaluated the ecodriving-tips. At both points of measurement self-reported fuel consumption was assessed. To sum up, 81 participants evaluated the tips as largely positive, both at baseline and follow-up. Furthermore, participants who received Version 3 of the ecodriving-tips (implementation intentions and technical explanations) significantly reduced their fuel consumption by 4% on average over time.

A simulator evaluation of in-vehicle human machine interfaces for eco-safe driving

Article

Dec 2018

In-vehicle human machine interfaces (HMI) represent a promising approach for informing drivers what they should do to adopt an eco-safe driving style, which is associated with reduced fuel consumption and improved safety. However, there is limited understanding of the driver acceptance of various types of in-vehicle HMIs and the impact of such systems on driving behaviour. Forty drivers participated in a simulated driving experiment to evaluate three variations of an eco-safe in-vehicle HMI: visual advice only; visual feedback only; or visual advice and feedback. To evaluate the impact of the different HMIs, subjective and objective measures were analysed, including fuel consumption, eco-safe driving behaviour, driver acceptance, and workload. Results indicate that all system types were associated with the relatively high levels of driver acceptance, with the advice only system accepted the most. While all system types produced relatively low levels of workload for drivers, systems involving feedback significantly increased the workload associated with using the interface. The findings suggest that the combined advice and feedback system has the potential to simultaneously reduce fuel consumption and improve eco-safe driving behaviour. Specifically, both advice and feedback appeared to be critical in encouraging positive changes in eco-safe driving behaviour. Our contribution can inform the design and development of future in-vehicle HMIs to improve eco-safe driving style that are accepted by drivers and have minimal adverse impacts on driver workload.

Driving Behaviour and Sustainable Mobility—Policies and Approaches Revisited

Article

Full-text available

Apr 2018

Climate change is receiving increasing attention in recent years. The transportation sector contributes substantially to increased fuel consumption, greenhouse gas (GHG) emissions, and poor air quality, which imposes a serious respiratory health hazard. Road transport has made a significant contribution to this effect. Consequently, many countries have attempted to mitigate climate change using various strategies. This study analysed and compared the number of policies and other approaches necessary to achieve reduced fuel consumption and carbon emission. Frequency aggregation indicates that the mitigation policies associated with driving behaviours adopted to curtail this consumption and decrease hazardous emissions, as well as a safety enhancement. Furthermore, car-sharing/carpooling was the least investigated approach to establish its influence on mitigation of climate change. Additionally, the influence of such driving behaviours as acceleration/deceleration and the compliance to speed limits on each approach was discussed. Other driving behaviours, such as gear shifting, compliance to traffic laws, choice of route, and idling and braking style, were also discussed. Likewise, the influence of aggression, anxiety, and motivation on driving behaviour of motorists was highlighted. The research determined that driving behaviours can lead to new adaptive driving behaviours and, thus, cause a significant decrease of vehicle fuel consumption and CO2 emissions.

How Do Hybrid Electric Vehicle Drivers Acquire Ecodriving Strategy Knowledge?

Conference Paper

May 2017
Lect Notes Comput Sci

Hybrid electric vehicles (HEVs) have the potential to accomplish high energy efficiency (i.e., low fuel consumption) given that drivers apply effective ecodriving control strategies (i.e., ecodriving behavior). However, HEVs have a relatively complex powertrain and therefore require a considerable knowledge acquisition process to enable optimal ecodriving behavior. The objective of the present research was to examine the acquisition of ecodriving strategy knowledge in HEV drivers who are successful in achieving a relatively high energy efficiency. To this end, we recruited 39 HEV drivers with above-average fuel efficiencies and collected interview data on the ecodriving strategy acquisition process. Drivers reported the acquisition of different types of knowledge as important for ecodriving, namely specific strategy knowledge and general technical system knowledge. They acquired this knowledge both with system-interaction (e.g., actively testing specific strategies, continuous monitoring of energy consumption) and without system-interaction (e.g., internet forums, consulting experts). This learning process took drivers on average 6.4 months or 10062 km. The results show the high diversity of the means that HEV drivers use to develop their ecodriving knowledge and the considerable time it takes HEV drivers to develop their ecodriving strategies.

Enhancing eco-safe driving behaviour through the use of in-vehicle human-machine interface: A qualitative study

Article

Full-text available

Jun 2017
TRANSPORT RES A-POL

Background: The widespread reliance on motor vehicles has negative effects on both the environment and human health. The development of an innovative in-vehicle human machine interface (HMI) has the potential to contribute to reducing traffic pollution and road trauma. Aim: A qualitative study, using a driver-centred design approach, was carried out to test how best to provide ecological and safe (eco-safe) driving advice and feedback to drivers on their driving style via an in-vehicle HMI. Method: A total of 34 drivers (52.9% males), aged 19–61 years, participated in focus groups which explored concepts from the Technology Acceptance Model (Davis, 1989). Findings: Main themes emerging from the focus groups were: (i) perceived importance of eco-safe driving behaviour; (ii) perceived usefulness of eco-safe in-vehicle HMIs; (iii) intentions to use an eco-safe in-vehicle HMI; (iv) perceptions toward eco-safe in-vehicle HMI design characteristics; and (v) potential problems associated with using eco-safe in vehicle HMIs. Implications: This study provides the foundation to inform the design and development of an evidence-based in-vehicle eco-safe HMI with high levels of driver acceptance.Recommendations for future research are also discussed.

Individual variable speed limit trajectory planning considering stochastic arriving patterns

Article

Full-text available

Dec 2022

Connected vehicles enabled by communication technologies have the potential to improve traffic mobility and enhance roadway safety such that traffic information can be shared among vehicles and infrastructure. Fruitful speed advisory strategies have been proposed to smooth connected vehicle trajectories for better system performance with the help of different car-following models. Yet, there has been no such comparison about the impacts of various car-following models on the advisory strategies. Further, most of the existing studies consider a deterministic vehicle arriving pattern. The resulting model is easy to approach yet not realistic in representing realistic traffic patterns. This study proposes an Individual Variable Speed Limit (IVSL) trajectory planning problem at a signalized intersection and investigates the impacts of three popular car-following models on the IVSL. Both deterministic and stochastic IVSL models are formulated, and their performance is tested with numerical experiments. The results show that, compared to the benchmark (i.e., without speed control), the proposed IVSL strategy with a deterministic arriving pattern achieves significant improvements in both mobility and fuel efficiency across different traffic levels with all three car-following models. The improvement of the IVSL with the Gipps’ model is the most remarkable. When the vehicle arriving patterns are stochastic, the IVSL improves travel time, fuel consumption, and system cost by 8.95%, 19.11%, and 11.37%, respectively, compared to the benchmark without speed control.

The Analysis of Classification and Spatiotemporal Distribution Characteristics of Ride-Hailing Driver’s Driving Style: A Case Study in China

Article

Full-text available

Aug 2022
Int J Environ Res Publ Health

Monitoring the driving styles of ride-hailing drivers is helpful for providing targeted training for drivers and improving the safety of the service. However, previous studies have lacked analyses of the temporal variation as well as spatial variation characteristics of driving styles. Understanding the variations can also help authorities formulate driver management policies. In this study, trajectory data are used to analyze driving styles in various temporal and spatial scenarios involving 34,167 drivers. The k-means method is used to cluster sample drivers. In terms of driving style time-varying, we found that only 31.79% of drivers could maintain a stable driving style throughout the day. Spatially, we divided the research area into two parts, namely, road segments and intersections, to analyze the spatial driving characteristics of drivers with different styles. The speed distribution, the acceleration and deceleration distributions are analyzed, results indicated that aggressive drivers display more aggressive driving styles in road segments, and conservative drivers exhibit more conservative driving styles at intersections. The findings of this study provide an understanding of temporal and spatial driving behavior factors for ride-hailing drivers and offer valuable contributions to ride-hailing driver training and road safety management.

Encouraging Eco-Driving Behavior: Driver Response to Different Types of In-Vehicle Eco- Driving Feedback

Thesis

Full-text available

Dec 2021

Yiyi Wang

The success of the change towards frequently undertaking eco-driving behavior is highly dependent on the individual drivers and appropriate in-vehicle feedback systems that drivers respond to. This work uses the data coming from 822 individuals who participated an online survey over a two-month period using 14 graphics of different types of in-vehicle eco-driving feedback interfaces and finds that researcher-identified eco-drivers are those ICEV drivers with strong environmental beliefs, and self-identified eco-drivers are those who have higher level of education, lower income, and strong environmental beliefs. This variation in researcher-identified and self-identified eco-drivers by demographics, vehicle characteristics, and motivational factors suggests an intention-behavior gap that self-identified eco-drivers are not those who are actually engaging in frequent eco-driving behaviors. Beyond the identification of eco-drivers, the use of in-vehicle eco-driving feedback itself plays an important role in encouraging eco-driving behavior. This work finds that eco-drivers are more likely than non-eco-drivers to be influenced by the use of eight different types of feedback. In the analyses of a causal chain leading from intentions to behavior, eco-driving intentions account for up to 22.4% of the variance in models explaining self-reported eco-driving behavior. The use of Biophilic Rewards and Eco-Driving Coach feedback types were found to play the most important role in motivating drivers to eco-drive. Ultimately, this research develops an integrated theoretical framework to better understand the role of the use of in-vehicle eco-driving feedback in encouraging eco-driving behavior. It posits that feedback design attributes are relevant in whether and how drivers perceive information and the impact on driver response towards frequent eco-driving behavior. It also provides direction for further research to expand on themes surrounding social norms, and a framework to undertake experimental fieldwork in the future.

The Indicator of GDI Engine Operating Mode and Its Influence on Eco-Driving

Article

Full-text available

Feb 2022

Elements of car construction, especially the information available on a dashboard, can stimulate the way of driving. The experiment described in the paper aimed to examine how the information provided by the indicator, which informs about the operational mode of a gasoline direct injection (GDI) engine, can contribute to eco-driving and the possible learning of acceleration pedal operation by a driver. The analysis of the fuel injection process affected by driver behaviour was an essential part of the experiment. The experiment was divided into two parts. The first one (nine tests) consisted of driving without access to the indicator information. In the second part, the information on the mode of the engine run was available for the driver. The results confirmed that the information about the type of fuel mixture used for the supply of the GDI engine facilitates an economical driving style (about 10% fuel savings) and motivates the driver to engage in eco-driving.

Ecological Adaptive Cruise Control of Plug-In Hybrid Electric Vehicle With Connected Infrastructure and On-Road Experiments

Article

Full-text available

Dec 2021
J DYN SYST-T ASME

This paper examines both mathematical formulation and practical implementation of an ecological adaptive cruise controller (ECO-ACC) with connected infrastructure. Human errors are typical sources of accidents in urban driving, which can be remedied by rigorous control theories. Designing an ECO-ACC is, therefore, a classical research problem to improve safety and energy efficiency. We add two main contributions to the literature. First, we propose a mathematical framework of an online ECO-ACC for Plug-in Hybrid Electric Vehicle (PHEV). Second, we demonstrate ECO-ACC in a real-world which includes other human drivers and uncertain traffic signals on a 2.6 [km] length of the corridor with 8 signalized intersections in Southern California, USA. The demonstration results show, on average, 30.98% of energy efficiency improvement and 8.51% additional travel time.

Aligning stakeholders’ mental models on carsharing system using remote focus group method

Article

Full-text available

Dec 2021
TRANSPORT RES D-TR E

The novelties of new mobility solutions, such as carsharing, may instill different expectations and understanding of the concepts among stakeholders. These differences in their ‘mental models’ can hamper the wider implementation of the concept and delay a transition toward a more sustainable transport system. In this study, we implemented a participatory group modeling building approach (GMB) to explore the differences and to integrate the mental models of stakeholders concerning the carsharing operation in Bangkok, Thailand. Through the process, we identified apparent differences in how participants visioned a successful carsharing operation and created an initial shared understanding in the form of a causal loop diagram. The qualitative model included attributes influencing the success of carsharing and possible policy interventions. The results illustrated the effectiveness of GMB as a participatory approach for transport planning.

Biased energy efficiency perception based on instantaneous consumption displays – Indication for heuristic energy information processing

Article

Jul 2021
APPL ERGON

Instantaneous consumption displays (ICDs) can be used as central information source to perceive the energy efficiency of manoeuvre-level driving. A key question is whether drivers who use ICDs can accurately derive energy efficiency differences of different driving strategies based on ICDs. There is reason to assume that drivers' consumption judgements may be biased, similar to driving-related phenomena like the time-saving bias. Therefore, the aim of the present research was to examine drivers’ accuracy in deriving average consumption from dynamic ICD sequences. Participants viewed videos of a schematic ICD in a controlled experiment where the maximum instantaneous consumption systematically varied over time. Participants (N = 55) overestimated the average consumption values. The empirical ranking of the sequences did significantly correlate with the heuristic but not with the correct efficiency ranking. The current study incorporated multilevel modelling due to the nested structure of the data. The estimation difference was greater with higher peak height and shorter peak duration. The effect of peak height on estimation difference weakened with longer peak duration. In sum, the results indicate that ICDs can create biased perceptions of energy efficiency and that drivers seem to use simplifying heuristics. Knowledge and affinity for technology interaction appear to relate to biased estimations, whereas the intensity of prior experience with consumption displays seems irrelevant. Further studies should test other interfaces with debiasing potential such as manoeuvre-based aggregation or fading-trace approaches. Moreover, studies are needed that enable modelling of the effects of more natural temporal-spatial visual attention distribution (e.g. in a driving simulator setting).

Cut through traffic to catch green light: Eco approach with overtaking capability

Article

Full-text available

Feb 2021
TRANSPORT RES C-EMER

This research presents an enhanced eco-approach controller with overtaking capability. The proposed controller overcomes the shortcomings of the conventional eco approach and is able to: i) overtake slowly-moving vehicles for the ecological purpose; ii) optimize the travel duration approaching an intersection; iii) guarantee both fuel saving and vehicle’s mobility; iv) consider stochasticity of surrounding traffic; v) functional under partially connected and automated environment. It takes full advantage of connected vehicle technology by taking in real-time vehicle and infrastructure information as optimization input. The problem is formulated as an optimal control problem and is solved by GPOPS. The nonlinear bicycle model is adopted as the system dynamics to realize CAV’s longitudinal and lateral coupling control, and linearized to reduce the computational burden. The stochasticity of surrounding traffic is considered as a probability distribution that is transformed into a linear chance constraint. Quantitative evaluation is conducted to compare the proposed controller against human drivers and the conventional eco approach which only has longitudinal automation. The evaluation results demonstrate that the proposed controller improves the fuel efficiency by 4.13–70.12%, and outperforms two baseline controllers by 6.06–36.73% in terms of fuel saving. The range is caused by the different arrival time of the ego CAV. In addition, the simulation experiment in VISSIM is conducted to analyze how background traffic flow influences the performance of the proposed controller.

A Review of Driving Simulation Technology and Applications

Article

Full-text available

Jan 2021

Driving simulation has become a very useful tool for vehicle design and research in industry and educational institutes. This paper provides a review of driving simulator components, including the vehicle dynamics model, the motion system, and the virtual environment, and how they interact with the human perceptual system in order to create the illusion of the driving. In addition, a sample of current state-of-the-art vehicle simulators and algorithms are described. Finally, current applications are discussed, such as driver-centered studies, chassis and powertrain design, and autonomous systems development.

Eco-routing problem considering fuel consumption and probabilistic travel time budget

Article

Jan 2020
TRANSPORT RES D-TR E

Road transportation is one of the major sources of greenhouse gas emissions. To reduce energy consumption and alleviate this environmental problem, this study aims to develop an eco-routing algorithm for navigation systems. Considering that both fuel consumption and travel time are important factors when planning a trip, the proposed routing algorithm finds a path that consumes the minimum amount of gasoline while ensuring that the travel time satisfies a specified travel time budget and an on-time arrival probability. We first develop link-based fuel consumption models based on vehicle dynamics, and then the Lagrangian-relaxation-based heuristic approach is proposed to efficiently solve this NP-hard problem. The performance of the proposed eco-routing strategy is verified in a large-scale network with real travel time and fuel consumption data. Specifically, a sensitivity analysis of fuel consumption reduction for travel demand and travel time buffer is discussed in our simulation study.

The Energy Interface Challenge. Towards Designing Effective Energy Efficiency Interfaces for Electric Vehicles

Conference Paper

Sep 2019

The design of effective energy interfaces for electric vehicles needs an integrated perspective on the technical and psychological factors that together establish real-world vehicle energy efficiency. The objective of the present research was to provide a transdisciplinary synthesis of key factors for the design of energy interfaces for battery electric vehicles (BEVs) that effectively support drivers in their eco-driving efforts. While previous research tends to concentrate on the (visual) representation of common energy efficiency measures, we focus on the design of action-integrated metrics and indicators for vehicle energy efficiency that account for the perceptual capacities and bounded rationality of drivers. Based on this rationale, we propose energy interface examples for the most basic driving maneuvers (acceleration, constant driving, deceleration) and discuss challenges and opportunities of these design solutions.

ACC Design for Safety and Fuel-efficiency: The Acceptance of Safety Margins when adopting different Driving Styles

Article

Full-text available

May 2020
Cognit Tech Work

For Adaptive Cruise Control (ACC) systems to be accepted and used safely, the transitions from cruise control mode to necessary driver intervention need to be obvious to the driver. Previous research shows that drivers have natural boundaries for acceptable values for time headway and time to collision to a car in front, which define at what point they are likely to step on the brake pedal. These boundaries can define an intuitive limit for ACC engagement. However, such boundaries may not be the same for all drivers, and not even for the same driver, whose goals may vary. The present research aimed to measure mental model boundaries in the context of different goals with a motorway cut-in scenario in a driving simulator. Participants drove in three conditions, after being asked to ‘drive safely, ‘drive fuel-efficiently’ and after no specific instructions. The results show that both the safe and eco-driving instructions led drivers to brake at longer safety margins. These findings indicate that, as drivers follow different goals, e.g. as they are reminded to drive safely or eco-friendly, their preferences for operational limits of ACCs may change. This needs to be taken into account for design decisions, e.g. by using ‘safe’ and ‘eco’ modes when driving.

How driving experience and consumption related information influences eco-driving with battery electric vehicles – Results from a field study

Article

Apr 2019
TRANSPORT RES F-TRAF

Battery electric vehicles (BEVs) are a promising form of future mobility. However, current BEV drivers have to interact with quite small ranges because of the relatively small battery sizes and relatively long charging periods. One important coping resource to overcome this barrier is to use the available driving range as efficiently as possible by successfully using several eco-driving strategies. Eco-driving can reduce energy consumption and enhance a BEV’s driving range. Several eco-driving strategies can be adopted from internal combustion engine vehicles, but specific strategies for driving BEVs, such as efficient use of the regenerative braking need to be learnt. We examine the influence of pre-drive theoretical eco-driving training (i.e., consumption related information, eco-driving tips) versus practical BEV driving experience on self-reported eco-driving behaviour, knowledge, knowledge certainty rating and eco-driving acceptance. Experienced BEV drivers (N = 20), untrained non-BEV (N = 23), and a third group consisting of non-BEV drivers who received pre-drive theoretical eco-driving training (N = 20) undertook a BEV test drive in a critical range situation. First time experience of a critical range situation and the pre-drive theoretical eco-driving training both had positive effects on non-BEV drivers’ self-reported eco-driving knowledge, knowledge certainty rating and acceptance. Compared to untrained non-BEV drivers, both experienced BEV drivers and trained non-BEV drivers reported enhanced eco-driving behaviour in the critical range situation.

A simulator study of the effect of incentive on adoption and effectiveness of an in-vehicle human machine interface

Article

Dec 2018

Introduction: Rapid developments in transportation technologies, such as in-vehicle human-machine interfaces (HMI), have the potential to improve driving behaviour. However, the use of such approaches is typically voluntary and there are numerous barriers to their widespread implementation. The aim of the current paper is to evaluate the impact of monetary incentive combined with competition with other drivers on adoption and effectiveness of an eco-safe in-vehicle HMI. Moreover, this research assess intentions to use and willingness to purchase the in-vehicle HMI, both of which play crucial roles in sustained voluntary uptake of in-vehicle HMIs. Method: Forty drivers participated in a driving simulator experiment and questionnaires. Three variations of an eco-safe driving in-vehicle HMI were evaluated (advice only, feedback only, combined advice and feedback), followed by an incentive-based condition. Results: The findings revealed the 4.7% reduction in fuel consumption with an addition of incentive and competition with other drivers associated with the use of in-vehicle HMI on eco-safe driving behaviour. Moreover, there was some evidence to suggest that a range of extrinsic and intrinsic incentives may be beneficial for increasing intentions to use such a system. Conclusions: We conclude that the addition of incentives may be more effective in encouraging greater intentions to use the in-vehicle HMI, compared to improving eco-safe driving behaviour associated with system use. Practical applications: This research provides valuable knowledge towards enhancing the current understanding of the nature and features of eco-safe in vehicle HMIs. Such information provides a foundation for the design and development of novel in-vehicle systems, incorporating the influence of competition with other drivers and incentives to enhance the motivation to use in-vehicle systems and consequently, improve drivers' fuel efficiency and safe driving behaviour.

Environmental Effect of Bus Priority Measures Applied on a Road Network in Santiago, Chile

Article

Full-text available

Jul 2018
TRANSPORT RES REC

Air pollution is at the highest levels ever and there is currently a worldwide initiative by transport engineers and urban planners to redesign public transport modes and cities to become more sustainable and environmentally friendly. The environmental impact of everyday activities is more apparent in developing cities which take longer to adapt to advanced methods of running public transport modes. This study aims to investigate the reduction of bus energy consumption and carbon emissions through bus priority measures in a bus route in the city of Santiago, Chile. Two bus priority schemes are tested in this study: Bus Only Lanes and Bus Signal Priority. The microscopic traffic simulator TSIS-CORSIM is used to quantify the environmental impact of these schemes. The results have shown that both schemes lead to lower fuel consumption and emissions, especially for the bus service. The environmental improvements are mostly apparent at traffic flows below 1000 veh/h, with clear benefits for both the bus service and passenger cars when dedicated bus lanes are included in the road infrastructure.

Green Driver: Travel Behaviors Revisited on Fuel Saving and Less Emission

Article

Full-text available

Jan 2018

Road transportation is the main energy consumer and major contributor of ever-increasing hazardous emissions. Transportation professionals have raised the idea of applying the green concept in various areas of transportation, including green highways, green vehicles and transit-oriented designs, to tackle the negative impact of road transportation. This research generated a new dimension called the green driver to remediate urgently the existing driving assessment models that have intensified emissions and energy consumption. In this regard, this study aimed to establish the green driver's behaviors related to fuel saving and emission reduction. The study has two phases. Phase one involves investigating the driving behaviors influencing fuel saving and emission reduction through a systematic literature review and content analysis, which identified twenty-one variables classified into four clusters. These clusters included the following: (i) FEf1, which is driving style; (ii) FEf2, which is driving behavior associated with vehicle transmission; (iii) FEf3, which is driving behavior associated with road design and traffic rules; and (iv) FEf4, which is driving behavior associated with vehicle operational characteristics. The second phase involves validating phase one findings by applying the Grounded Group Decision Making (GGDM) method. The results of GGDM have established seventeen green driving behaviors. The study conducted the Green Value (GV) analysis for each green behavior on fuel saving and emission reduction. The study found that aggressive driving (GV = 0.16) interferes with the association between fuel consumption, emission and driver's personalities. The research concludes that driver's personalities (including physical, psychological and psychosocial characteristics) have to be integrated for advanced in-vehicle driver assistance system and particularly, for green driving accreditation.

Eco-driving behavior tendency among Indonesian people: a preliminary study

Article

Full-text available

Dec 2017

Eco-driving behavior can be triggered by many aspects such as economic and environmental awareness. In Indonesia this issue received less attention from citizen, whereas it has significant roles in reducing greenhouse gas emission. This paper initiated a study about eco-driving tendency behavior among Indonesian people, the objective is to see whether current behavior support or not, and does the differences between gender and age exist. Adopted on-line study method using an online form questionnaire" 27 questions developed consist of 8 items related to individual data, 19 items related to perception and driving behavior. The respond measures using 5 scale option answers (i.e. strongly disagree, disagree, quite agree, agree, and strongly agree). Based on average respondents' answers, can be concluded that the tendency of behavior somewhat supports to in line with eco-driving behavior. After Q15 and Q18 omitted based on Pearson-product moment correlation, further analysis results showed that most of respondents categorized into mild tendency behavior (109 respondents). However, a mild tendency among female respondents are higher than male, and the strong tendency of males is higher than female respondents. Based on gender, there are no significant tendency behavior differences between male and female (p-value = 0, 320), and also among age groups (30y, 31-40y, 41-50y, and >50y), even though age >50 have a lower tendency to the behavior compare to other groups.

Driving Automation: A Human Factors Perspective

Book

Full-text available

Jan 2023

Eco-Driving: A Scientometric and Bibliometric Analysis

Article

Dec 2022
IEEE T INTELL TRANSP

The fuel efficiency of the transportation sector has become a key factor to reduce greenhouse gas emissions and fuel consumption in response to the negative impacts of global warming. As an approach to energy saving and environmental sustainability, eco-driving has attracted considerable research interest in the past decades. This review aims to provide a comprehensive review of the research on eco-driving using methodologies of literature bibliometrics and content analysis through VOSviewer software. The following keywords “ecological-driving”“, ecological-routing”“, ecological-bus”“, ecological-car”“, ecological-vehicle”“, eco-driving”“, eco-routing”“, eco-driver”“, eco-bus”“, eco-car” and “eco-vehicle” are used for paper retrieval. The query was conducted on January 20, 2021. The results take account of all journal articles, proceedings papers, and reviews without time limitation. Finally, a total of 767 documents were retrieved as total publications, which were viewed over the period 2001–2020 based on the Web of Science (WoS) Core Collection database. The publication year, leading countries, leading sources, leading institutions, leading authors, document citation, and document co-citation were analyzed to explore the primary trends. The In-depth analysis reveals five clusters of keywords, and the review of relevant studies on eco-driving from five different perspectives is carried out to identify potential trends and future research hot spots of eco-driving.

Realisierung einer Aufgabenanalyse unter simulierten Spurwechselbedingungen - Erfassung kognitiver Fahranforderungen

Thesis

Aug 2017

Julia Bühring

This exploratory investigation focused on driving related cognitions during lane change maneuvers. Participants experimentally executed appropriate maneuvers performing two different types of lane change on a simulated two-lane highway, which was developed as part of the EU research project AutoMate (Automation as accepted and trusted TeamMate to enhance traffic safety and efficiency) by the German Aerospace Center (DLR). Aim of the investigation was to set up and identify driving cognitions as well as underlying goals for lane change maneuvers on the simulated route. For this purpose, the driver-vehicle interaction was modeled using the Cognitive-Perceptual-Motor-GOMS (CPM-GOMS) method derived from the GOMS family (Goals, Operators, Methods, Selection Rules). The formal data analysis was supplemented by asking participants to verbalize their thoughts during the trials, a method commonly referred to as "thinking aloud". This method allowed the recording of the drivers’ cognitive processes and set goals during task performance. The sample consisted of nine subjects, whose verbalization of thoughts revealed numerous cognitive operators and goals during data analysis. Thinking aloud was found to be a reliable instrument in the detection of cognitive processes, and to be applicable without noticeably affecting task performance. However, these results should be replicated using other instruments for corresponding data acquisition, for example eye tracking combined with driving data, to allow drawing of more generalizable implications. In conclusion, findings regarding verbalization ability, objectivity of cognitive operators and goals, classification of lane-change times and phase-time, as well as defining time periods of operators are discussed. This work has potential to serve as basis for the expansion of a CPM-GOMS.

The role of self-concordance for self-reported strategic, tactical, and operational eco-driving

Article

Jan 2022
TRANSPORT RES F-TRAF

Although most people are aware of the harmful CO2 emissions produced by the transport sector threatening life on earth now and in the future, they do not eco-drive. Eco-driving improves the vehicle’s fuel or energy economy and reduces greenhouse gas emissions. We investigated the motivational predictors of eco-driving based on the theory of self-concordance (i.e., the consistency between a behavior/goal with the person’s pre-existing values and interests). Data from a cross-sectional online survey with 536 German drivers revealed that self-reported eco-driving was significantly predicted by sustained effort towards eco-driving, which in turn was predicted by self-concordance variables. Therefore, individuals pursuing eco-driving out of strong interest or deep personal beliefs (i.e., autonomous motivation) as opposed to external forces or internal pressures (i.e., controlled motivation) reported greater effort towards this behavior. Furthermore, biospheric striving coherence, i.e., the coherence between personal valuable biopsheric values (i.e., values addressing the well-being of the environment/biosphere) and eco-driving, significantly predicted effort towards eco-driving. In sum, our results suggest that autonomous rather than controlled motives and coherence between behavior and intrinsic rather than extrinsic values are relevant predictors for eco-driving. We discuss implications for future strategies and interventions fostering eco-driving in the long term.

Assisted Eco-Driving: A Practical Guide to the Design and Testing of an Eco-Driving Assistance System (EDAS)

Book

Full-text available

Oct 2021

Quantifying the impact of driving style changes on light-duty vehicle fuel consumption

Article

Sep 2021
TRANSPORT RES D-TR E

Modifying driving styles can help to reduce the energy use and emissions of driving without requiring changes to infrastructure or vehicle technology. Here, we evaluate the energy consumption and duration of trips before and after driving style changes. These modifications are made using emissions-friendly driving style heuristics that are easily implementable by drivers and do not require real-time feedback or on-board diagnostics. We use a data-driven approach to apply these heuristics to a representative baseline of U.S. drive cycles. The simulated driving-style improvements provide an average fuel savings per trip of 6%, alongside a 1.5% increase in trip duration. Decelerating early and reducing highway speeds can each contribute substantially to fuel savings. Accelerating more gradually contributes less. The percentage fuel savings are relatively consistent across locations and vehicle classes. These findings can inform several decision-makers, including drivers aiming to reduce fuel consumption, car manufacturers or software developers designing driving style feedback, and policy makers examining emissions savings opportunities.

Mental Model of Driving Wizards When Simulating an Automated Drive

Conference Paper

Oct 2020

When prototyping automated vehicles using the WoZ methodology, the driving behavior simulated by driving wizards significantly shapes participants’ experience during the experiment. Therefore, driving wizards should be provided with instructions regarding the automated driving behavior. However, they are currently instructed in different ways. It is hypothesized that different instructions lead to differing mental models and consequently to a differing realization of the automated driving behavior to be simulated. A study using a right-hand drive vehicle was conducted where participants acted as driving wizards. Three different instructions were tested at two test times (3x2 within-subjects design, N = 14). As a result, a set of rules, that driving wizards may use when simulating an automated driving style, was developed. Using qualitative & quantitative guidelines as instructions might lead to a more homogeneous mental model between several driving wizards as well as for the same driving wizard at different points in time.

Entwicklung und Validierung einer Fahrsimulationsumgebung für Interface-Testing im Kontext Elektromobilität

Poster

Full-text available

Mar 2019

Bisherige Forschung hat gezeigt, dass die Art und Weise, wie Informationen über Energieverbräuche wahrgenommen und verarbeitet werden, einen bedeutenden Einfluss auf die Energieeffizienz der Fahrweise von Fahrern hat. Die optimale Gestaltung von Energie-Interfaces ist daher ein zentraler Bereich im Design von Nutzerschnittstellen im Fahrzeugkontext. Neue Interface-Möglichkeiten durch mobile Displays sowie Trends wie Elektrifizierung und Automatisierung stellen hierbei neue Designherausforderungen dar. In diesem Rahmen werden effiziente Testverfahren von neuen Fahrzeuganzeigen auf Usability und Verhaltenswirksamkeit immer wichtiger. Mit dem IMIS-Fahrsimulator wird eine Testumgebung für Nutzerstudien zu neuen Fahrzeuginterfaces in Elektrofahrzeugen entwickelt. Ziel ist es, mittels Anpassungen der Software BeamNG.research und der entsprechenden Hardware die Fahrsimulationsumgebung an ein reales Fahrzeug anzunähern, um eine möglichst realistische Fahrsimulation zu realisieren. Hierfür werden nicht nur ein Elektrofahrzeug mit angepasstem Energiemodell integriert, sondern auch eine Anpassung an die Maße eines realen Fahrzeugs, z. B. hinsichtlich Sitzposition und Lenkradwinkel, vorgenommen. Die Anpassungen werden in einer Nutzerstudie validiert und erste Ergebnisse aus den Validierungsstudien präsentiert.

Onboard energy-efficient operations and decision-making of ship crews

Thesis

Full-text available

Oct 2019

Mourad Zoubir

Objective: To reduce the energy-efficiency gap in shipping, further research on the human factors of energy-efficient operations (EEO) is required. This work aimed to apply methods from Franke et al. (2016) into this new context and to explore new avenues of research. Methods: A systematic literature study, cross-sectional interviews (n = 14) on board of a shipping vessel and an online survey (n = 74) were used. Thematic analysis was conducted on interview material, while knowledge, mental models, motivating and hinder factors, and crew members perceived influence on energy efficiency were examined in the online survey. Results: Strain was perceived as a hinderance to EEO, while seafarers were motivated by their shipping company, environmental concerns or when possessing knowledge on energy efficiency. Knowledge predicted mental models of EEO. Discussion: External stakeholders have a potential to decrease hinderances (such as strain and uncertainty) to and increase motivation for EEO via improved communication and improved interfaces. Existing institutions onboard can be used to increase knowledge.

Two-layer pointer model of driving style depending on the driving environment

Article

Oct 2019
TRANSPORT RES B-METH

This paper deals with the task of modeling the driving style depending on the driving environment. The model of the driving style is represented as a two-layer mixture of normal components describing data with two pointers: outer and inner. The inner pointer indicates the actual driving environment categorized as “urban”, “rural” and “highway”. The outer pointer through the determined environment estimates the active driving style from a fuel economy point of view as “low consumption”, “middle consumption” and “high consumption”. All of these driving styles are assumed to exist within each driving environment due to the two-layer model. Parameters of the model and the driving style are estimated online, i.e., while driving using a recursive algorithm under the Bayesian methodology. The main contributions of the presented approach are: (i) the driving style recognition within each of urban, rural and highway environments as well as in the case of switching among them; (ii) the two-layer pointer, which allows us to incorporate the information from continuous data into the model; (iii) the potential use of the data-based model for other measurements using corresponding distributions. The approach was tested using real data.

Comparing drivers’ self-perception on driving behaviour changes with real world driving performance data: Lisbon case-study

Article

Apr 2018

Information and communication technologies (ICT) applied to the transportation sector have enabled studying real-world driving behaviour and the impacts of eco-driving training and education on fuel consumption and driving performance. The aim of this paper is to assess drivers’ self-perceptions on their driving performance after an experimental on-road monitoring trial in which they received feedback on performance. Drivers’ self-perceptions on their driving performance were compared with their driving data. Results indicate that majority of drivers considered the information presented in the feedback reports as being important, particularly in what concerned fuel consumption (fuel spent while driving) and aggressiveness (extreme braking and acceleration) indicators. Nonetheless, the same level of importance is not given to indicators that largely influence or not paying any attention to them when driving. Such results might be indicative that participants give preference to fuel efficiency when driving, having the intention to improve fuel consumption, but might find it difficult to understand and apply eco-driving techniques. The majority of drivers perceived their behaviour suffered ‘little’ to ‘some changes’, particularly in fuel consumption and aggressiveness. The comparison with driving data revealed that drivers increased the incidence of unwanted behaviours when they considered that their performance suffered ‘some changes’. On the contrary, decreases in some indicators, such as aggressiveness, speeding and excess rpm, were observed when ‘no changes’ were perceived by the drivers. These results are indicative that drivers are not correctly aware of changes in their performance.

An online estimation of driving style using data-dependent pointer model

Article

Jan 2018
TRANSPORT RES C-EMER

The paper focuses on a task of stochastic modeling the driving style and its online estimation while driving. The driving style is modeled by means of a mixture model with normal and categorical components as well as a data-dependent pointer. The mixture parameters and the actual driving style are estimated with the help of a recursive algorithm under the Bayesian methodology. The main contributions of the presented approach are: (i) the online estimation of the driving style while driving, taking into account data up to the current time instant; (ii) the joint model for continuous and discrete data measured on a vehicle; (iii) the data-dependent model of the driving style conditioned by the values of fuel consumption; (iv) the use of the model both for detection of clusters according to the driving style and prediction of the fuel consumption along with other variables; and (v) the universal modeling with the help of mixtures, which allows us to use different combinations of components and pointer models as well as to specify the initialization approach suitable for the considered problem. Results of the driving style detection in real measurements and comparison with the theoretical counterparts are demonstrated.

A methodology to evaluate driving efficiency for professional drivers based on a maturity model

Article

Dec 2017
TRANSPORT RES C-EMER

Over the last decade, transport companies have tried to reduce fuel consumption using efficient driving programs. In them, motorists have to apply different specific techniques while driving. Thus, to succeed in this learning process there are two key elements: the knowledge of efficient driving techniques and the drivers’ motivation. The latter is a human factor which companies usually bring about by using reward systems. In this case, having a fair evaluation mechanism is the keystone to determine goal fulfilment. This paper presents a complete methodology to evaluate driving efficiency of drivers in professional fleets. The evaluation methodology is based on a continuous process which determines the maturity of the motorist in different aspects, such as the efficiency during the start of the vehicle movement, during motion or in stop events. In addition, the evaluation methodology includes an early-classification method to establish the initial efficiency level of the individual drivers which permits an adaptation of the learning process from the beginning. A dashboard has also been developed to support the evaluation methodology. 880 professional drivers have been evaluated with this methodology. Results show that the evaluation methodology identifies drivers’ weaknesses, to be improved in successive iterations of the learning process.

The activation of eco-driving mental models: Can text messages prime drivers to use their existing knowledge and skills?

Article

Full-text available

Nov 2017
Cognit Tech Work

Eco-driving campaigns have traditionally assumed that drivers lack the necessary knowledge and skills and that this is something that needs rectifying. Therefore, many support systems have been designed to closely guide drivers and fine-tune their proficiency. However, research suggests that drivers already possess a substantial amount of the necessary knowledge and skills regarding eco-driving. In previous studies, participants used these effectively when they were explicitly asked to drive fuel-efficiently. In contrast, they used their safe driving skills when they were instructed to drive as they would normally. Hence, it is assumed that many drivers choose not to engage purposefully in eco-driving in their everyday lives. The aim of the current study was to investigate the effect of simple, periodic text messages (nine messages in 2 weeks) on drivers’ eco- and safe driving performance. It was hypothesised that provision of eco-driving primes and advice would encourage the activation of their eco-driving mental models and that comparable safety primes increase driving safety. For this purpose, a driving simulator experiment was conducted. All participants performed a pre-test drive and were then randomly divided into four groups, which received different interventions. For a period of 2 weeks, one group received text messages with eco-driving primes and another group received safety primes. A third group received advice messages on how to eco-drive. The fourth group were instructed by the experimenter to drive fuel-efficiently, immediately before driving, with no text message intervention. A post-test drive measured behavioural changes in scenarios deemed relevant to eco- and safe driving. The results suggest that the eco-driving prime and advice text messages did not have the desired effect. In comparison, asking drivers to drive fuel-efficiently led to eco-driving behaviours. These outcomes demonstrate the difficulty in changing ingrained habits. Future research is needed to strengthen such messages or activate existing knowledge and skills in other ways, so driver behaviour can be changed in cost-efficient ways.

How Public Education on Ecodriving Can Reduce Both Fuel Use and Greenhouse Gas Emissions

Article

Full-text available

Dec 2012
TRANSPORT RES REC

Ecodriving, the concept of changing driving behavior and vehicle maintenance to affect fuel consumption and greenhouse gas (GHG) emissions in existing vehicles, has recently gained prominence in North America. One ecodriving strategy involves public education with information disseminated on the Internet. This paper presents the results of a study conducted from June to December 2010 that assessed the effectiveness of static, web-based information on ecodriving with controlled stated responses from approximately 100 faculty, staff, and students at the University of California, Berkeley. A comparison of the experimental and control groups revealed that exposure to ecodriving information influenced people's driving behavior and maintenance practices. The experimental group's distributional shift in behavior was statistically significant, particularly for key practices, including lower highway cruising speed, adjustment of driving behavior, and proper tire inflation. Within the experimental group (N = 51), only 16% of respondents significantly changed their maintenance practices whereas 71% altered some driving practices; these data suggest that intentional alteration of driving behavior is easier than is planning better maintenance practices. A comparison of before-and-after surveys revealed that 57% of the experimental group improved their ecodriving behavior and that 43% made no change or worsened. Key characteristics of the drivers who improved included being female, living in smaller households, and owning a newer car with higher fuel economy. Although it was evident that not everyone modified behavior as a result of reviewing the website, even small shifts in behavior attributable to inexpensive dissemination of information could be deemed cost-effective in reducing fuel consumption and emissions.

TRAFISAFE – Feedback for novice drivers

Conference Paper

Full-text available

Jul 2014

Novice car drivers, especially young men, are over-represented in road accident statistics. New ways are needed to reduce their risks, and there is a need to motivate young drivers towards responsible driving. In this paper, we outline the preliminary results of the Trafisafe field trial, in which a new driving style feedback system was tested with 75 novice drivers and their parents. The preliminary results show promising results and the test users have clearly indicated an interest in the feedback service and the Trafisafe concept.

THE RELATIONSHIP BETWEEN FUEL ECONOMY AND SAFETY OUTCOMES

Article

Full-text available

Effect of Using an In-Vehicle Smart Driving Aid on Real-World Driver Performance

Article

Full-text available

Aug 2014
IEEE T INTELL TRANSP

A smart driving system (providing both safety and fuel-efficient driving advice in real time in the vehicle) was evaluated in real-world on-road driving trials to see if any measurable beneficial changes in driving performance would be observed. Forty participants drove an instrumented vehicle over a 50-min mixed-route driving scenario. Two conditions were adopted: one is a control with no smart driving feedback offered and the other is with advice being presented to the driver via a smartphone in the vehicle. Key findings from the study showed a 4.1% improvement in fuel efficiency when using the smart driving aid, importantly with no increase in journey time or reduction in average speed. Primarily, these efficiency savings were enabled by limiting the use of lower gears (facilitated by planning ahead to avoid unnecessary stops) and an increase in the use of the fifth gear (as advised by the in-vehicle system). Significant and important changes in driving safety behaviors were also observed, with an increase in mean headway to 2.3 s and an almost threefold reduction in time spent traveling closer than 1.5 s to the vehicle in front. This paper has shown that an in-vehicle smart driving system specifically developed and designed with the drivers' information requirements in mind can lead to significant improvements in driving behaviors in the real world on real roads with real users.

Proposal of an eco-driving assist system adaptive to driver's skill

Conference Paper

Full-text available

Oct 2011

The purpose of the present study is to develop an eco-driving assist system that is adaptive to a driver's skill and to demonstrate its effectiveness. The eco-driving assist system consists of a visual indicator illustrating the eco-driving. In the proposed adaptive system, the resolution of the indicator and the threshold of eco-driving are changed to adapt to the driver's skill. The proposed eco-driving system was installed in a driving simulator. Changes in driving behavior and the corresponding eco-driving scores, measured over five days, were investigated. As a comparison, experiments were conducted on a system without any level changes (a non-adaptive system) and on one without any assist system. In the results, eco-driving scores were higher with the assist systems than without them. The score with the adaptive system increased through the trial days, while no clear tendency was found with the non-adaptive system.

Comprehending Consumption: The Behavioral Basis and Implementation of Driver Feedback for Reducing Vehicle Energy Use

Article

Full-text available

Jan 2011

Tai Stillwater

A large body of evidence suggests that drivers who receive real-time fuel economy information can increase their vehicle fuel economy by 5%, a process commonly known as ecodriving. However, few studies have directly addressed the human side of the feedback, that is, why drivers would (or would not) be motivated to change their behavior and how to design feedback devices to maximize the motivation to ecodrive. This dissertation approaches the question using a mixed qualitative and quantitative approach to explore driver responses and psychology as well as to quantify the process of behavior change. The first chapter discusses the use of mile-per-gallon fuel economy as a metric for driver feedback and finds that an alternative energy economy metric is superior for real-time feedback. The second chapter reviews behavioral theories and proposes a number of practical solutions for the ecodriving context. In the third chapter the theory of planned behavior is tested against driver responses to an existing feedback system available in the 2008 model Toyota Prius. The fourth chapter presents a novel feedback design based on behavioral theories and drivers' responses to the feedback. Finally, chapter five presents the quantitative results of a natural-driving study of fuel economy feedback. The dissertation findings suggest that behavior theories such as the Theory of Planned Behavior can provide important improvements to existing feedback designs. In addition, a careful analysis of vehicle energy flows indicates that the mile-per-gallon metric is deeply flawed as a real-time feedback metric, and should be replaced. Chapters 2 and 3 conclude that behavior theories have both a theoretical and highly practical role in feedback design, although the driving context requires just as much care in the application. Chapters 4 and 5 find that a theory-inspired interface provides drivers with engaging and motivating feedback, and that integrating personal goal into the feedback is the most motivating theory-based addition. Finally, the behavioral model results in chapter 5 suggest that driver goals not only influence in-vehicle energy use, but are themselves flexible constructs that can be directly influenced by energy feedback.

Vibrotactile pedals: Provision of haptic feedback to support economical driving

Article

Full-text available

Feb 2013
ERGONOMICS

Unlabelled: The use of haptic feedback is currently an underused modality in the driving environment, especially with respect to vehicle manufacturers. This exploratory study evaluates the effects of a vibrotactile (or haptic) accelerator pedal on car driving performance and perceived workload using a driving simulator. A stimulus was triggered when the driver exceeded a 50% throttle threshold, past which is deemed excessive for economical driving. Results showed significant decreases in mean acceleration values, and maximum and excess throttle use when the haptic pedal was active as compared to a baseline condition. As well as the positive changes to driver behaviour, subjective workload decreased when driving with the haptic pedal as compared to when drivers were simply asked to drive economically. The literature suggests that the haptic processing channel offers a largely untapped resource in the driving environment, and could provide information without overloading the other attentional resource pools used in driving. Practitioner summary: Overloaded or distracted drivers present a real safety danger to themselves and others. Providing driving-related feedback can improve performance but risks distracting them further; however, giving such information through the underused haptic processing channel can provide the driver with critical information without overloading the driver's visual channel.

Attitudes towards and perceptions of eco-driving and the role of feedback systems

Article

Full-text available

Feb 2013
ERGONOMICS

Unlabelled: This paper addresses whether eco-driving may be encouraged by providing drivers with feedback, and how eco-driving attitudes fit with other environmental attitudes. Eight focus groups, including fleet drivers, discussed how feedback and other motives might affect driving behaviour. A survey of 350 respondents investigated attitudes towards saving fuel, the role of incentives and use of eco-friendly products. The focus groups' findings show that the environment is a lower priority than comfort and convenience, that feedback might provide a stimulus to eco-driving and that saving money was less important than saving time. The attitude survey showed that price, convenience, attitudes and eco-driving are not conceptually linked together, that convenience is rated as more important than saving money from fuel efficiency and that although the environment is of concern, it is not a high enough priority to increase fuel efficiency. The findings are discussed in relation to the low level of priority given to environmental concerns and the inability of financial incentives presenting significant challenges in terms of changing the subjective norms of the majority of drivers. Practitioner summary: This paper, using focus groups and a questionnaire, aims to understand how feedback devices, attitudes and motivation can improve eco-driving behaviours. The incentive to save money by better fuel economy was found to be insufficient, and roles for feedback devices and how information is presented are identified.

The impact of smart driving aids on driving performance and driver distraction

Article

Full-text available

Nov 2011

In-vehicle information systems (IVIS) have been shown to increase driver workload and cause distraction, both of which are causal factors for accidents. This simulator study evaluates the impact that two prototype ergonomic designs for a smart driving aid have on workload, distraction and driving performance. Scenario complexity was also manipulated as an independent variable. Results showed that real-time delivery of smart driving information did not increase driver workload or adversely affect driver distraction, while also having the positive effect of decreasing mean driving speed in both the simple and complex driving scenarios. Subjective workload was shown to increase with task difficulty, as well as revealing important differences between the two interface designs. The findings are relevant to the development and implementation of smart driving interface designs in the future.Highlights► The delivery of smart driving information did not adversely affect driver workload or distraction. ► Smart driving aids resulted in a reduction in driving speed and acceleration events. ► Headway and journey times were unaffected. ► Users showed reduced workload when driving with an ecologically designed HMI.

The Think Aloud Method - A Practical Guide to Modelling CognitiveProcesses

Book

Full-text available

Jan 1994

Model-Based Human-Centered Task Automation: A Case Study in ACC System Design

Article

Full-text available

Jun 2003
IEEE T SYST MAN CY A

Engineers, business managers, and governments are increasingly aware of the importance and difficulty of integrating technology and humans. The presence of technology can enhance human comfort, efficiency, and safety, but the absence of human-factors analysis can lead to uncomfortable, inefficient, and unsafe systems. Systematic human-centered design requires a basic understanding of how humans generate and manage tasks. A very useful model of human behavior generation can be obtained by recognizing the task-specific role of mental models in not only guiding execution of skills but also managing initiation and termination of these skills. By identifying the human operator's mental models and using them as templates for automating different tasks, we experimentally support the hypothesis that natural and safe interaction between human operator and automation is facilitated by this model-based human-centered approach. The design of adaptive cruise control (ACC) systems is used as a case study in the design of model-based task automation systems. Such designs include identifying ecologically appropriate perceptual states, identifying perceptual triggering events for managing transitions between skilled behaviors, and coordinating the actions of automation and operator.

The Effect of Drivers' Speed on the Frequency of Road Accidents

Article

Jan 2001

Delivering smart driving feedback through a haptic pedal

Article

Jan 2010

This study evaluates the effects of a vibrotactile (or haptic) accelerator pedal on car driving performance and perceived workload using a driving simulator. The stimulus was triggered when the driver exceeded a 50% throttle threshold, past which is deemed excessive in the literature. Results showed a significant decrease in mean and maximum acceleration values, also a reduction in the maximum and excess throttle values when the haptic pedal was active versus a baseline condition. In addition, a further decrease in maximum and excess throttle was observed compared to when participants were simply asked to drive economically. As well as the positive changes to driver behaviour, subjective workload decreased when driving with the haptic pedal. The haptic processing channel offers a largely untapped resource in the driving environment, and could provide information without overloading the other attentional resource pools used in driving.

Annual European Community Greenhouse Gas Inventory, 1990–2007 and Inventory Report

Technical Report

Apr 2007

European Environment Agency

A Virtual Driving System for Enhancing Efficient Driving Style

Article

Apr 2012

This paper proposes a virtual driving system for enhancing efficient driving style. We compared fuel economies and levels of consumable wear on three driving simulation test (none, visual, visual+auditory). The test results show that higher fuel economy can be achieved and consumable wear be reduced when they received feedback from the proposed system compared to driving without eco-driving training.

Providing eco-driving feedback to corporate car drivers: What impact does a smartphone application have on their fuel efficiency?

Article

Sep 2012

The personal transport sector constitutes an important target of energy conservation and emission reduction programs. In this context, eco-feedback technologies that provide information on the driving behavior have shown to be an effective means to stimulate changes in driving in favor of both, reduced costs and environmental impact. This study extends the literature on eco-feedback technologies as it demonstrates that a smartphone application can improve fuel efficiency even under conditions where monetary incentives are not given, i.e. where the drivers do not pay for fuel. The field test, which took place with 50 corporate car drivers, demonstrates an improvement in the overall fuel efficiency by 3.23%. The theoretical contribution underlines the assumption that context-related feedback can favorably influence behavior even without direct financial benefits for the agent. Given the large share of corporate cars, findings are also of high practical importance and motivate future research on eco-driving feedback technologies.

Effect of active effort in eco-driving support system on proficiency of driving skill

Conference Paper

Jan 2012

Eco-driving support systems (EDSSs) are separated into two types; a direct EDSS and an indirect EDSS. The present study performed driving simulator experiments to verify the different influence of two EDSSs on proficiency in eco-driving. We discuss the results from a viewpoint of FUBEN-EKI which was proposed as a novel system design methodology, and then clarify the relationship between the degree of active effort and the proficiency of eco-driving skill.

Eco-driving: An economic or ecologic driving style?

Article

Jan 2014
TRANSPORT RES C-EMER

In this work the trade-off between economic, therefore fuel saving, and ecologic, pollutant emission reducing, driving is discussed. The term eco-driving is often used to refer to a vehicle operation that minimizes energy consumption. However, for eco-driving to be environmentally friendly not only fuel consumption but also pollutant emissions should be considered. In contrast to previous studies, this paper will discuss the advantages of eco-driving with respect to improvements in fuel consumption as well as pollutant gas emissions. Simulating a conventional passenger vehicle and applying numerical trajectory optimization methods best vehicle operation for a given trip is identified. With hardware-in-the-loop testing on an engine test bench the fuel and emissions are measured. An approach to integrate pollutant emission and dynamically choose the ecologically optimal gear is proposed.

Drivers discuss ecodriving feedback: Goal setting, framing, and anchoring motivate new behaviors

Article

Jul 2013

Ecodriving, defined here as the adoption of energy efficient driving styles and practices (primarily moderating accelerations and decelerations, reducing top speeds, and improved maintenance practices), has long been recognized as a potential source of reductions in transportation energy use. Estimates of energy savings attributed to ecodriving range widely, from less than 5% to as high as 20% depending on the driving and experimental context. To explore the effects on ecodriving of interaction between drivers and in-vehicle energy feedback, a customized, interactive energy feedback interface was deployed in a field test with real-world drivers. This paper presents the results of interviews with 46 Plug-in Hybrid Electric Vehicle (PHEV) drivers who were given the ecodriving feedback interface for a multi-week trial including an interface off (baseline) and on (treatment) condition. This paper relies specifically on self-reports of driver motivations and behaviors to better understand what types of information motivated new ecodriving behavior; a future paper will investigate quantitative fuel consumption effects. Driver interviews at the conclusion of the study revealed that the introduction of feedback led three fourths of drivers to change driving styles to maximize on-road efficiency, at least in the short term. In addition, this study finds that the context of the feedback information, provided by a built-in goal or other contextualizing information such as a comparison value, is important for both comprehension and motivation. Personalization of the information allowed different drivers to access pertinent information, increasing the motivational value of the information. Instantaneous performance feedback such as real-time energy economy or power is used primarily for experimentation and learning of new ecodriving behaviors, whereas average performance feedback is used primarily for goal-setting and goal achievement. In addition, the direct comparison of personalized driver goals and average performance created a game-like experience that encouraged high achievement. Finally, the driver interviews revealed that feedback frames driving as a time to act in an efficient manner.

Environmental education technologies in a social void: The case of 'Greendrive'

Article

Dec 2012

Ana Delicado

This article is based on a case study that follows the trajectory of a technological device aimed at environmental education from the engineering laboratory in which it was designed into the contexts in which it is used. ‘Greendrive’ is a driving simulator that accurately reproduces the performance of a vehicle in terms of fuel consumption and greenhouse gases emissions, in order to instill the principles of safe and environmentally friendly driving. The text is divided into three parts. The first part introduces the issue of transport behavior as one of the causes of climate change and the role of eco-driving in reducing emissions. The second part describes how a team of Portuguese engineering researchers developed the driving simulator and how a local authority and a consulting and training company are using it. Finally, the discussion part aims to show that despite the intentions of its creators and their clients, the driving simulator is unlikely, by itself, to generate changes in behavior. An information-deficit approach to environmental education that fails to consider the social embeddedness of human action and disregards the engagement of citizens has a very limited chance of success.

Energy saving and safe driving assistance system for light vehicles: Experimentation and analysis

Article

Apr 2012

This paper presents an EDAS (Eco-Driving Assistance System) to render a light vehicle low fuel consuming while being safe. A fuel consumption modeling, associated to a speed/gear optimization module, is proposed and used to compute the optimal speed profile and gear ratio to inform the driver in order him to eco-drive. An HMI module is presented and the driver behavior is analyzed face to the indications given by this HMI: are the optimal trajectories easy to be followed? Are the HMI outputs understandable and accepted by the driver? Does this HMI information improve the way of driving in terms of safety, low consumption and comfort? Several experimental results obtained with a prototype vehicle and several drivers are presented in order to evaluate the quality of this EDAS. The analysis deals with the gain obtained for the safety (speed overlaps, headway spacing, speed while approaching a road curve), consumption and covering distance aspects, by comparing a driving without any HMI and a driving with the use of the HMI with a given driver (several drivers have tested this EDAS for the analysis). The experimental results show that this kind of EDAS can save until around 10% of gasoline and more than 50% speed overlaps (compared to the legal speed).

Qualitative Data Analysis

Book

Jan 1994

Skills, rules, knowledge: Signals, signs and symbols and other distinctions in humans performance mo

Article

Jan 1983

J. Rasmussen

Skills, Rules, and Knowledge; Signals, Signs, and Symbols, and Other Distinctions in Human Performance Models

Article

Jan 1987
IEEE Trans Syst Man Cybern Syst Hum

Jens Rasmussen

The introduction of information technology based on digital computers for the design of man-machine interface systems has led to a requirement for consistent models of human performance in routine task environments and during unfamiliar task conditions. A discussion is presented of the requirement for different types of models for representing performance at the skill-, rule-, and knowledge-based levels, together with a review of the different levels in terms of signals, signs, and symbols. Particular attention is paid to the different possible ways of representing system properties which underlie knowledge-based performance and which can be characterised at several levels of abstraction-from the representation of physical form, through functional representation, to representation in terms of intention or purpose. Furthermore, the role of qualitative and quantitative models in the design and evaluation of interface systems is mentioned, and the need to consider such distinctions carefully is discussed.

Concurrent Mobile (Cellular) Phone Use and Driving Performance: Task Demand Characteristics and Compensatory Processes

Article

Sep 2000
TRANSPORT RES F-TRAF

This paper reports a simulator-based study of the effects of mobile phone use on driving performance. Changes in heart rate indicated that mobile phone use increases the cognitive demand experienced by drivers with, it is argued, consequent reduction in safety margins. However, experimental results also suggested that participants engaged in a process of risk compensation, with driving speed being slower at times of mobile phone conversation while the number of off-road excursions (OFFS) and collisions remained stable. There also was some evidence that the use of a hand-held mobile phone (when compared to a hands-free system) was associated with poorer driving performance. Implications for `real world' driving are considered.

What characterizes a “free vehicle” in an urban area?

Article

Mar 2002
TRANSPORT RES F-TRAF

Katja Kircher

The concept “free vehicle” is used widely in the transportation research literature, but as yet there is no common standard for a definition. In this article a standard is provided that is based on the assumption that a vehicle can be considered free, when its speed is not influenced by the speed of the vehicle traveling ahead. In order to determine empirically a threshold for free vehicles in urban areas, speed, distance headway, and time headway data of more than 100000 vehicles were analyzed. Analyses showed that the speeds of two vehicles are linearly dependent on time headway for headways up to 6 s. It is important to distinguish between this value and the drivers' preferred headway, which is in the region of 2 s.

Scripts, Plans, Goals, and Understanding: An Inquiry into Human Knowledge Structures

Article

Sep 1978

For both people and machines, each in their own way, there is a serious problem in common of making sense out of what they hear, see, or are told about the world. The conceptual apparatus necessary to perform even a partial feat of understanding is formidable and fascinating. Our analysis of this apparatus is what this book is about. Roger C. Schank and Robert P. Abelson from the Introduction (http://www.psypress.com/scripts-plans-goals-and-understanding-9780898591385)

A Prototype Fuel-efficiency Support Tool

Article

Aug 2001
TRANSPORT RES C-EMER

An effective way to reduce fuel consumption in the short run is to induce a change in driver behaviour. If drivers are prepared to change their driving habits they can complete the same journeys within similar travel times, but using significantly less fuel. In this paper, a prototype fuel-efficiency support tool is presented which helps drivers make the necessary behavioural adjustments.The support tool includes a normative model that back-calculates the minimal fuel consumption for manoeuvres carried out. If actual fuel consumption deviates from this optimum, the support tool presents advice to the driver on how to change his or her behaviour. To take account of the temporal nature of the driving task, advice is generated at two levels: tactical and strategic.Evaluation of the new support tool by means of a driving simulator experiment revealed that drivers were able to reduce overall fuel consumption by 16% compared with ‘normal driving’. The same drivers were only able to achieve a reduction of 9% when asked to drive fuel efficiently without support; thus, the tool gave an additional reduction of 7%. Within a simulated urban environment, the additional reduction yielded by the support tool rose to 14%. The new support tool was also evaluated with regard to secondary effects.

The Computer and the Mind: An Introduction to Cognitive Science

Article

Jan 1988

Phil Johnson-Laird

Methods in the analysis of profile data

Article

Nov 1958

Impact of EcoDriving on emissions

Article

This paper presents results from a study conducted between 2000 and 2002 by the Swedish National Road Administration, MTC and later also TFK to improve the knowledge of the impact the economical driving concept EcoDriving has on emissions. In the study 86 persons, half of these earlier trained in EcoDriving, drove on a route in real traffic with two instrumented cars. Driving patterns and fuel consumption were measured on road. Emissions were measured on dynamometer for complete cycles. The results show no significant differences in emissions between trained and untrained drivers except for CO2. Drivers trained in EcoDriving who in the enquiry stated that they regularly check their fuel consumption and therefore have a motivation for driving economically had lower fuel consumption compared to other trained and untrained drivers. This result shows that both training and motivation is needed to achieve low fuel consumption. Keys-words: ecodriving, ecodrive, driving style, emissions, fuel consumption

Effectance Motivation Reconsidered Toward a Developmental Model

Article

Jan 1978

Susan Harter

Attempted to refine and extend R. White's (1959) model of effectance motivation, with particular emphasis on its developmental implications. This expanded model focuses on the following: the need to isolate components of effectance motivation at different developmental levels, an examination of the effects of failure as well as success, the relationship between task challenge and the degree of pleasure experienced, the role of social agents and the reinforcing environment, the developmental internalization of a self-reward system, the need to examine the relative strength of both intrinsic and extrinsic motivational orientations, certain correlates such as perceived competence and perceived control as consequences and mediators of one's motivational orientation. The need to translate theoretical concepts into researchable formulations which can be empirically tested within a developmental context is emphasized. (45 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)

Verbal Reports as Data

Article

May 1980

Proposes that verbal reports are data and that accounting for them, as well as for other kinds of data, requires explication of the mechanisms by which the reports are generated, and the ways in which they are sensitive to experimental factors (instructions, tasks, etc). Within the theoretical framework of human information processing, different types of processes underlying verbalization are discussed, and a model is presented of how Ss, in response to an instruction to think aloud, verbalize information that they are attending to in short-term memory (STM). Verbalizing information is shown to affect cognitive processes only if the instructions require verbalization of information that would not otherwise be attended to. From an analysis of what would be in STM at the time of report, the model predicts what could be reliably reported. The inaccurate reports found by other research are shown to result from requesting information that was never directly heeded, thus forcing Ss to infer rather than remember their mental processes. (112 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)

Ego and reality in psychoanalytic theory

Article

Jan 1963
Psychol Issues

Robert W. White

The concept of ego energies independent of libidinal and aggressive instincts brings about significant improvements in psychoanalytic ego theory. Following a review of ego psychology, independent ego energies are presented in terms of effectance and competence. There follow sections on reality and its testing, early deviations in ego development, identification as a process of development; self-esteem, sense of competence, and ego strength; and finally, considerations of anxiety, cathexis, and neutralization. (PsycINFO Database Record (c) 2012 APA, all rights reserved)

Acquisition of Cognitive Skill

Article

Jul 1982

John R. Anderson

Proposes a framework for skill acquisition that includes 2 major stages in the development of a cognitive skill: (1) a declarative stage in which facts about the skill domain are interpreted and (2) a procedural stage in which the domain knowledge is directly embodied in procedures for performing the skill. This general framework has been instantiated in the ACT system in which facts are encoded in a propositional network and procedures are encode

How I reduce fuel consumption: An experimental study on mental models of eco-driving

Abstract

No full-text available