Article

Eco-driving: An overlooked climate change initiative

Authors:
To read the full-text of this research, you can request a copy directly from the author.

Abstract

The actions individuals can take to mitigate climate change are, in the aggregate, significant. Mobilizing individuals to respond personally to climate change, therefore, must be a complementary approach to a nation's climate change strategy. One action item overlooked in the United States has been changing driver behavior or style such that eco-driving becomes the norm rather than the exception. Evidence to date indicates that eco-driving can reduce fuel consumption by 10%, on average and over time, thereby reducing CO2 emissions from driving by an equivalent percentage. A sophisticated, multi-dimensional campaign, going well beyond what has been attempted thus far, will be required to achieve such savings on a large scale, however, involving education (especially involving the use of feedback devices), regulation, fiscal incentives, and social norm reinforcement.

No full-text available

Request Full-text Paper PDF

To read the full-text of this research,
you can request a copy directly from the author.

... It may be reasonable to assume that all these efforts in sustainable mobility may also have a correspondence at the individual level, i.e., in driver behaviors. For example, adopting an eco-friendly driving style, such as accelerating and decelerating smoothly, anticipating the traffic flow to avoid sudden maneuvers, and maintaining a steady driving pace (Barkenbus, 2010;Dogan et al., 2011) and related behaviors could be evaluated as part of sustainable and positive driver behaviors. These behaviors result in fuel-saving and preventing the possibility of accidents originating from sudden maneuvers; thus, they relate to positive behaviors. ...
... For example, driving at a steady speed relates to fuel-saving and reducing environmental pollution which was the example provided by McKnight and Adams for responsible driving style. Inspired by the eco-driving studies (e.g.,Barkenbus, 2010;Dogan et al., 2011), the eco-friendly driving style emerged as part of positive driver behaviors in this study.In the current study, environmentally sustainable driving behaviors emerged as part of the positive driver behaviors. Specific examples regarding making fuel economy, reducing air pollution, and ensuring the vehicle's and its parts' long service life are all related to sustainable and responsible, thus, positive driver behaviors. ...
... Öte yandan, nezaket ile ilgili pozitif sürücü davranışları sürüş ortamındaki daha naif davranışlarla ilişkilidir.Son yıllarda, çevre ve iklimle ilgili konular sürdürülebilir ulaştırma araştırmasının bir parçası olarak incelenmeye başlanmıştır. Örneğin, hızlanma ve yavaşlama konusunda stabil bir şekilde hareket etme, ani manevralardan kaçınmak için trafik akışını tahmin etme ve istikrarlı bir sürüş hızını koruma gibi çevre dostu bir sürüş tarzını benimsemek(Barkenbus, 2010; Dogan vd., 2011) ve ilgili davranışlar, sürdürülebilir ve pozitif sürücü davranışlarının bir parçası olarak değerlendirilebilir. Bu davranışlar yakıt tasarrufuna yol açar ve ani manevralardan kaynaklanabilecek kazaların olasılığını önler; bu nedenle pozitif davranışlarla ilişkilidirler. ...
Thesis
Full-text available
Studies on positive driver behaviors are limited compared to those on risky driver behaviors. These positive behaviors, often defined narrowly as kindness and helpfulness, also possess a broader scope encompassing safety and eco-friendly tendencies. To address this gap, Study 1 explored the multidimensional nature of positive driver behaviors. Accordingly, the Multidimensional Positive Driver Behavior Questionnaire (M-PDBQ) was developed following semi-structured interviews with 16 drivers. In the main study with 628 participants, the M-PDBQ's factor structure was identified, and its psychometric properties were examined. The M-PDBQ, featuring 53 items, measures positive driver behaviors across three key dimensions: smooth and proactive mobility, environmentally sustainable behaviors, and risk communication. This 3-factor structure confirms the multidimensionality of positive driver behaviors. Moreover, hierarchical regression analyses indicated that factors of the M-PDBQ predict safety outcomes, however, the effect is small. On the other hand, the M-PDBQ factors demonstrated significant associations with driving-related variables, suggesting a potential role of positive driver behaviors in reducing violations and driving anger in traffic. The discussion section proposed a comprehensive definition of positive driver behaviors. The intentionality behind these behaviors was discussed from a theoretical perspective and the expression of them was discussed in a cultural context. The factors and items of the M-PDBQ can be utilized in developing road safety intervention programs aimed at reducing driving anger and violations. Also, road safety messages could focus on promoting positive driver qualities.
... According to Renub Research (2021), the global automotive market is expected to accelerate at a compound annual growth rate of 3.71% from 85.32 million in 2020 to 122.83 million units by 2030. With the rapid growth in the number of road vehicles worldwide, the transportation sector is confronted with the arising challenges of greenhouse gas (GHG) emissions and traffic congestion (Barkenbus, 2010;Sullman et al., 2015). The legislative bodies worldwide have committed to address the alarming climate change challenge and set stringent regulatory standards to reduce the global CO2 emissions from road vehicles (Barkenbus, 2010). ...
... With the rapid growth in the number of road vehicles worldwide, the transportation sector is confronted with the arising challenges of greenhouse gas (GHG) emissions and traffic congestion (Barkenbus, 2010;Sullman et al., 2015). The legislative bodies worldwide have committed to address the alarming climate change challenge and set stringent regulatory standards to reduce the global CO2 emissions from road vehicles (Barkenbus, 2010). Furthermore, the transportation industry is transitioning towards sustainable future mobility solutions, thus resulting in a paradigm shift towards electrified powertrains. ...
... Furthermore, automated energy-optimal longitudinal control in vehicles is studied previously in several works (Sajadi-Alamdari et al., 2019), including ours (Chada et al., 2020(Chada et al., , 2021b. To enhance the energy efficiency in vehicles in a cost-effective manner, an area of research that has received significant attention over the years in both academia and automotive industry, is eco-driving (Barkenbus, 2010). The term eco-driving is referred to as an interim policy to improve the driver's driving style in an energy-efficient manner. ...
Preprint
Full-text available
In this work, a predictive eco-driving assistance system (pEDAS) with the goal to assist drivers in improving their driving style and thereby reducing the energy consumption in battery electric vehicles while enhancing the driving safety and comfort is introduced and evaluated. pEDAS in this work is equipped with two model predictive controllers (MPCs), namely reference-tracking MPC and car-following MPC, that use the information from onboard sensors, signal phase and timing (SPaT) messages from traffic light infrastructure, and geographical information of the driving route to compute an energy-optimal driving speed. An optimal speed suggestion and informative advice are indicated to the driver using a visual feedback. pEDAS provides continuous feedback and encourages the drivers to perform energy-efficient car-following while tracking a preceding vehicle, travel at safe speeds at turns and curved roads, drive at energy-optimal speed determined using dynamic programming in freeway scenarios, and travel with a green-wave optimal speed to cross the signalized intersections at a green phase whenever possible. Furthermore, to evaluate the efficacy of the proposed pEDAS, user studies were conducted with 41 participants on a dynamic driving simulator. The objective analysis revealed that the drivers achieved mean energy savings up to 10%, reduced the speed limit violations, and avoided unnecessary stops at signalized intersections by using pEDAS. Finally, the user acceptance of the proposed pEDAS was evaluated using the Technology Acceptance Model (TAM) and Theory of Planned Behavior (TPB). The results showed an overall positive attitude of users and that the perceived usefulness and perceived behavioral control were found to be the significant factors in influencing the behavioral intention to use pEDAS.
... In the global fight against air pollution and its negative climate change effects, the large-scale adoption of eco-driving can be a contributor. Prior literature has stressed that eco-driving can reduce fuel consumption by 10%, on average and over time, thereby reducing CO 2 emissions from driving by an equivalent percentage [9]. Eco-driving is defined as the implementation of ecologically beneficial driving techniques like keeping the speed down, efficient gear shifting, anticipatory, calm, and steady driving, and efficient braking [10]. ...
... Eco-driving is defined as the implementation of ecologically beneficial driving techniques like keeping the speed down, efficient gear shifting, anticipatory, calm, and steady driving, and efficient braking [10]. Apart from reducing air pollution and greenhouse gas emissions, eco-driving has other beneficial effects, such as improving road safety and reducing fuel costs [9,11,12]. In the automotive market, company car drivers are an important target. ...
... More research is needed to better understand how societies can achieve large-scale adoption of eco-driving. This probably requires educational efforts and social norm reinforcement [9]. Digitally administered driving feedback systems may be helpful to contribute to this objective and speed up the process, but it remains unclear how feedback influences eco-driving in a setting where drivers have no financial stake in reducing their fuel consumption. ...
Article
Full-text available
In the global fight against climate change, stimulating eco-driving could contribute to the reduction of CO2 emissions. Company car drivers are a main target in this challenge as they represent a significant market share and are typically not motivated financially to drive more fuel efficiently (and thus more eco-friendly). As this target group has received little previous research attention, we examine whether digitally administered feedback and coaching systems can trigger such company car owners to drive eco-friendly. We do so by using respondents (employees of a financial services company (N = 327)) that voluntarily have a digital device (‘dongle’) installed in their company car, which monitors and records driving behavior-related variables. In a longitudinal real-life field study, we communicate eco-driving recommendations (e.g., avoid harsh braking, accelerate gently, etc.) to the respondent drivers via a digital (computer) interface. Over a 21-week time frame (one block of seven weeks before the intervention, seven weeks of intervention, and seven weeks after the intervention), we test whether eco-driving recommendations in combination with personalized, graphical ‘eco-score index evolution’ feedback increase eco-driving behavior. We also experimentally evaluate the impact of adding social comparison elements to the feedback (e.g., providing feedback on a person’s eco-driving performance compared to that of the same car brand users). Structural Equation Modeling (in MPlus 8.4) is used to analyze data. Our results show that digitally administered personal performance feedback increases eco-driving behavior both during and after the feedback intervention. However, we do not observe increased effects when social comparison information is added to the feedback. As this latter element is surprising, we conclude with a reflection on possible explanations and suggest areas for future research. We contribute to the sustainable eco-driving literature by researching an understudied group: company car drivers. More specifically, we contribute by demonstrating the effectiveness of digitally administered personal performance feedback on eco-driving for this group and by observing and reflecting on the (in)effectiveness of feedback containing social comparison information.
... In 1978, the FES was estimated to account for a staggering 50% of the petrol used in the USA [12]. A later study in 2010 [13] calculated a 10% reduction in fuel consumption to amount to 3.3 million tons of CO 2 and cost 7.5 to 15.0 billion US dollars (USD) annually. Addressing the fundamental causes of FES and reasons for policy failures is critical to addressing them. ...
... Some of these programs are Smart Cities [25], Georgia Regional Transportation Authority (GRTA) buses, the Metropolitan Atlanta Rapid Transit Authority (MARTA) [26], the DECAT program out of Colorado [27], the GasCAP program out of California [28], and Drive Clean Across Texas, 2001 [29]. Other studies [30] have evaluated the impact of eco-driving education [31] and training in various European eco-driving programs, noting a CO 2 reduction ranging from 5.8-30% [13,32,33]. The potential for reduction in fuel use, emissions, and fiscal savings by increasing ecodriving is thus substantial. ...
... Eco-driving has been defined as [a] systematic way of driving a car that can reduce fuel consumption, emissions, accident rates, and increase energy efficiency [35]. It involves driving strategies such as vehicle selection and maintenance, tactical decisions such as route selection, and driving practices which improve vehicle fuel economy [11,13,35,36,37]. The intent is to ensure the most efficient use of the engine possible. ...
Article
div>In the United States (USA), transportation is the largest single source of greenhouse gas (GHG) emissions, representing 27% of total GHGs emitted in 2020. Eighty-three percent of these came from road transport, and 57% from light-duty vehicles (LDVs). Internal combustion engine (ICE) vehicles, which still form the bulk of the United States (US) fleet, struggle to meet climate change targets. Despite increasingly stringent regulatory mechanisms and technology improvements, only three US states have been able to reduce their transport emissions to the target of below 1990 levels. Fifteen states have made some headway to within 10% of their 1990 baseline. Largely, however, it appears that current strategies are not generating effective results. Current climate-change mitigation measures in road transport tend to be predominantly technological. One of the most popular measures in the USA is fleet electrification, receiving regulatory and fiscal encouragement from 45 US states and federal bills. However, zero-emission vehicles (ZEVs) might not be the climate change panacea for the transport sector. ZEVs are facing adoption issues ranging from affordability, equity, and charging infrastructure to vehicle class availability limitations. Despite increasing sales, US electric vehicle (EV) adoption has been behind the curve with a current market penetration of 4.5%. Outside of ZEVs, emission reduction in the US road transport sector has been sluggish. In road transport, which contributes the bulk of traffic-related air pollution (TRAP), there are clear gaps between policy targets, technology-based expectations, and actual results. For a sector that is struggling to meet climate change targets, broadening its scope of climate change mitigation measures for road transport would be useful. Driver behavior may be an underexplored strategy. Eco-driving is a known strategy and has been attributed to reducing TRAP by up to 50% (through nontechnological means) in various studies in the USA and across the world. If technological eco-driving measures are included, they can improve fuel economy in excess of 100%. But the extent to which it is included in driver education and licensing protocols in US states is unclear. This study, therefore, evaluates eco-driving in state-sponsored non-commercial Driving License Manuals (DLMs). Provisions in state DLMs were assessed based on the intent of the prescribed practices (collision safety, environmental exposure, or both), the extent to which these were included, and the strength of the recommended mechanisms (prescriptive or regulatory). The scores were converted into Grades A–D. The results are revealing. Despite thirty-three US states (66%) with extant climate change commitments, almost the same percentage (62%) of states received a “D” grade and entirely omitted to mention driver influence on fuel consumption and emissions. Only five states (10%) received an “A” grade with substantive eco-driving measures in their DLMs. There is thus significant scope for eco-driving content in DLMs, which can range from the state’s communicating climate change commitments to how drivers influence fuel consumption through their driving practices to empowering drivers with strategies they can adopt to save fuel and money and reduce emissions. This inclusion has the potential to improve vehicular fuel economy and help states meet their climate change goals. Driver education is the first step. Eco-driving principles can be further bolstered through subsequent inclusion in the driver training and testing phases of driver licensing.</div
... According to Renub Research (2021), the global automotive market is expected to accelerate at a compound annual growth rate of 3.71% from 85.32 million in 2020 to 122.83 million units by 2030. With the rapid growth in the number of road vehicles worldwide, the transportation sector is confronted with the arising challenges of greenhouse gas (GHG) emissions and traffic congestion (Barkenbus, 2010;Sullman et al., 2015). The legislative bodies worldwide have committed to address the alarming climate change challenge and set stringent regulatory standards to reduce the global CO2 emissions from road vehicles (Barkenbus, 2010). ...
... With the rapid growth in the number of road vehicles worldwide, the transportation sector is confronted with the arising challenges of greenhouse gas (GHG) emissions and traffic congestion (Barkenbus, 2010;Sullman et al., 2015). The legislative bodies worldwide have committed to address the alarming climate change challenge and set stringent regulatory standards to reduce the global CO2 emissions from road vehicles (Barkenbus, 2010). Furthermore, the transportation industry is transitioning towards sustainable future mobility solutions, thus resulting in a paradigm shift towards electrified powertrains. ...
... Furthermore, automated energy-optimal longitudinal control in vehicles is studied previously in several works (Sajadi-Alamdari et al., 2019), including ours (Chada et al., 2020(Chada et al., , 2021b. To enhance the energy efficiency in vehicles in a cost-effective manner, an area of research that has received significant attention over the years in both academia and automotive industry, is eco-driving (Barkenbus, 2010). The term eco-driving is referred to as an interim policy to improve the driver's driving style in an energy-efficient manner. ...
Article
Full-text available
In this work, a predictive eco-driving assistance system (pEDAS) with the goal to assist drivers in improving their driving style and thereby reducing the energy consumption in battery electric vehicles (BEVs) while enhancing the driving safety and comfort is introduced and evaluated. pEDAS in this work is equipped with two model predictive controllers (MPCs), namely reference-tracking MPC and car-following MPC, that use the information from onboard sensors signal phase and timing (SPaT) messages from traffic light infrastructure, and geographical information of the driving route to compute an energy-optimal driving speed. An optimal speed suggestion and informative advice are indicated to the driver using a visual feedback. Moreover, the warning alerts during unsafe car-following situations are provided through an auditory feedback. pEDAS provides continuous feedback and encourages the drivers to perform energy-efficient car-following while tracking a preceding vehicle, travel at safe speeds at turns and curved roads, drive at energy-optimal speed determined using dynamic programming in freeway scenarios, and travel with a green-wave optimal speed to cross the signalized intersections at a green phase whenever possible. Furthermore, to evaluate the efficacy of the proposed eco-driving assistance system, user studies were conducted with 41 participants on a dynamic driving simulator. The objective analysis revealed that the drivers achieved mean energy savings up to 10%, reduced the speed limit violations, and avoided unnecessary stops at signalized intersections by using pEDAS. Finally, the user acceptance of the proposed pEDAS was evaluated using the Technology Acceptance Model (TAM) and Theory of Planned Behavior (TPB). The results showed an overall positive attitude of users and that the perceived usefulness and perceived behavioral control were found to be the significant factors in influencing the behavioral intention to use pEDAS.
... Furthermore, our observation is that a majority of studies are small-scale (e.g., one or two intersections or a few intersections in a route) and mainly focus on technical questions that concern how to eco-drive Sun et al. (2020); Yang et al. (2016Yang et al. ( , 2020. But the fundamental socio-technical question of whether to ecodrive, which requires going beyond a few intersections-based analyses, remains unanswered Barkenbus (2010). Our aim of this work is to contribute a large-scale prospective analysis of eco-driving at signalized intersections, highlighting city-scale emission benefits and uncovering insights that may influence widespread adoption-factors that are often elusive in smaller-scale studies. ...
... Our aim of this work is to contribute a large-scale prospective analysis of eco-driving at signalized intersections, highlighting city-scale emission benefits and uncovering insights that may influence widespread adoption-factors that are often elusive in smaller-scale studies. Such an analysis provides a scientific basis for informed decision-making, strategic planning of infrastructure, and technology development Barkenbus (2010). ...
Preprint
Full-text available
The sheer scale and diversity of transportation make it a formidable sector to decarbonize. Here, we consider an emerging opportunity to reduce carbon emissions: the growing adoption of semi-autonomous vehicles, which can be programmed to mitigate stop-and-go traffic through intelligent speed commands and, thus, reduce emissions. But would such dynamic eco-driving move the needle on climate change? A comprehensive impact analysis has been out of reach due to the vast array of traffic scenarios and the complexity of vehicle emissions. We address this challenge with large-scale scenario modeling efforts and by using multi-task deep reinforcement learning with a carefully designed network decomposition strategy. We perform an in-depth prospective impact assessment of dynamic eco-driving at 6,011 signalized intersections across three major US metropolitan cities, simulating a million traffic scenarios. Overall, we find that vehicle trajectories optimized for emissions can cut city-wide intersection carbon emissions by 11-22%, without harming throughput or safety, and with reasonable assumptions, equivalent to the national emissions of Israel and Nigeria, respectively. We find that 10% eco-driving adoption yields 25%-50% of the total reduction, and nearly 70% of the benefits come from 20% of intersections, suggesting near-term implementation pathways. However, the composition of this high-impact subset of intersections varies considerably across different adoption levels, with minimal overlap, calling for careful strategic planning for eco-driving deployments. Moreover, the impact of eco-driving, when considered jointly with projections of vehicle electrification and hybrid vehicle adoption remains significant. More broadly, this work paves the way for large-scale analysis of traffic externalities, such as time, safety, and air quality, and the potential impact of solution strategies.
... A. Overview C ONVENTIONAL internal combustion engine vehicles consume a lot of fossil fuels while accelerating and release many emission pollutants while decelerating and idling, especially around urban signalized intersections. Urban ecological driving (eco-driving) aims to regulate trajectories of connected automated vehicles (CAVs) or affect driver behaviors of manually-driven vehicles (MVs) so that the vehicles traverse road links and signalized intersections without sharp decelerations, fast accelerations, and unnecessary stops to minimize the energy consumption and pollutive emission [1], [2], [3], [4]. ...
... However, if t mt f falls in a red phase in Fig. 3b, t f is set equal to t g to prevent the CAV from encountering a red light at the intersection. 2 Note that t f determined above is the earliest time that the CAV can pass through the intersection without stopping. ...
Article
Full-text available
The connected automated vehicles (CAVs) are envisioned to be implemented most likely on electric vehicles, while traditional fuel-powered manually-driven vehicles (MVs) would probably still dominate the automobile market in the next decade. In this context, this paper addresses urban eco-driving of CAVs in mixed traffic and heterogeneous power conditions. The paper aims to develop a practical and deployable eco-driving strategy for CAVs in mixed traffic flow of CAVs and MVs under realistic and complex traffic conditions. Several typical eco-driving scenarios were studied in detail. In a nutshell, the eco-driving strategy for each CAV was determined by solving a typical two-point boundary value problem with minimum electric energy consumption in urban traffic conditions with small market penetration rates (MPRs) of CAVs. A rolling-horizon scheme was applied to implement the eco-driving strategy to handle uncertain/unpredictable disturbances of preceding MVs and the interference of junction queues to the eco-driving maneuvers of CAVs. The paper also studied how eco-driving for electrified CAVs would affect MVs’ fuel consumptions. Simulation studies were carried out on urban arterial roads of multiple signalized intersections in various scenarios of demand and MPR to verify the energy savings effect of the proposed eco-driving strategy. The results showed that via eco-driving electrified CAVs each had a potential of reducing energy consumption by 40%-61%, meanwhile leading to 5%-34% fuel savings on average for each following MV. Further issues concerning the energy saving mechanism of electrified CAVs, impacts of MVs cut-in from adjacent lanes, and passenger comfort were also examined.
... IntersectionZoo bridges this gap by decoupling the modeling complexity of real-world tasks from the experimental process, allowing researchers to focus on algorithmic advancements. This approach, in turn, holds the potential to improve eco-driving, which is known for its impact on climate change mitigation goals (Barkenbus, 2010), with the automotive industry actively pursuing robust eco-driving controllers. This aligns with the growing interest in application-driven research in machine learning, promising a mutually beneficial outcome for all communities involved (Rolnick et al., 2024). ...
Preprint
Despite the popularity of multi-agent reinforcement learning (RL) in simulated and two-player applications, its success in messy real-world applications has been limited. A key challenge lies in its generalizability across problem variations, a common necessity for many real-world problems. Contextual reinforcement learning (CRL) formalizes learning policies that generalize across problem variations. However, the lack of standardized benchmarks for multi-agent CRL has hindered progress in the field. Such benchmarks are desired to be based on real-world applications to naturally capture the many open challenges of real-world problems that affect generalization. To bridge this gap, we propose IntersectionZoo, a comprehensive benchmark suite for multi-agent CRL through the real-world application of cooperative eco-driving in urban road networks. The task of cooperative eco-driving is to control a fleet of vehicles to reduce fleet-level vehicular emissions. By grounding IntersectionZoo in a real-world application, we naturally capture real-world problem characteristics, such as partial observability and multiple competing objectives. IntersectionZoo is built on data-informed simulations of 16,334 signalized intersections derived from 10 major US cities, modeled in an open-source industry-grade microscopic traffic simulator. By modeling factors affecting vehicular exhaust emissions (e.g., temperature, road conditions, travel demand), IntersectionZoo provides one million data-driven traffic scenarios. Using these traffic scenarios, we benchmark popular multi-agent RL and human-like driving algorithms and demonstrate that the popular multi-agent RL algorithms struggle to generalize in CRL settings.
... The main purpose of Eco-driving is to generate realtime speed advice for connected vehicles to enable them to adjust their velocities or driving behavior and perform particular actions to minimize fuel consumption and reduce their delays. In a multitude of research works, it is indicated that the eco-driving approaches are able to decrease fuel consumption and greenhouse gas (GHG) emissions by almost 10% on average [10]. ...
Article
Full-text available
It is interesting to realize that traffic intersections provide an essential mechanism to handle traffic flows in different directions while ironically traffic bottlenecks, gridlocks, and accidents tend to occur in the vicinity of the intersections. Meanwhile, with the recent developments in internet of things (IoT) technologies, there is a great potential for integrating them for improving operational efficiencies of road infrastructure and connected autonomous vehicles (CAVs). This paper aims to leverage the capabilities of both autonomous intersection manager (AIM) and CAVs for more energy-saving and safe-traffic management. A mixed-traffic environment where human-driven vehicles (HDVs) and CAVs sharing the same road is considered. A two-layer framework is adopted to handle signal and vehicle controls effectively. The first layer is a signal control layer where the AIM receives the traffic network states, trains with the data through machine learning (ML), and outputs a set of optimal green times for each intersection phase. The second layer is a decentralized-vehicle control layer where the CAVs receive the signal phase and timing (SpaT) information from the AIM to compute the optimal speed values. The proposed solution helps the CAVs to minimize idling at red signals or to speed up to safely arrive at and pass through a green signal. Our proposed framework is designed to optimize intersection efficiency and minimize vehicle average delay and fuel consumption. All experiments have been conducted in a microscopic traffic simulation environment, the PTV-VISSIM, simulating real-world dynamics of vehicles and drivers’ behaviors based on decades of field-data.
... Otherwise, it could be another tax implemented to expand the government revenue collection, while pressing deprived individuals. Similarly, studies have reported that eco-driving could diminish fuel consumption by 10%, thus, it could be a worthy strategy towards climate mitigation [31]. Furthermore, such evidence should complement the local evidence identi ed on behavioural attitudes of citizens on climate change mitigation, when developing policies with the involvement of stakeholders; government, public institutions and private corporations. ...
Preprint
Full-text available
Three focus group discussions (FGD) were conducted among residents already practising climate change mitigative activities, low-income urban communities and rural residents to identify the behavioural attitudes on climate mitigation in households in the district of Colombo. Eight adult residents aged 18 years or above were purposively selected for each discussion. The principal investigator conducted all discussions with the assistance of a note-taker, using a semi-structured FGD guide. The thematic analysis was carried out to identify the beahvioural attitudes. Of the 24 participants, 14 were men and 10 were women, while 10 were < 40 years of age. Views on the existance of climate change were based on recent increase in temperature and natural disasters. Behavioural attitudes on climate change mitigation were generated under several themes: causes for climate change, perceptions on vulnerability to effects of climate change, negative attitudes towards climate mitigation, new technologies used for climate mitigation, carbon tax, green test and views on government responsibilities towards climate mitigation. The findings showed that behavioural attitudes are more driven by poor scientific knowledge, poverty and cultural beliefs which should be addressed by mitigative actions.
... Several investigations Liimatainen, 2011;Meseguer et al., 2015;D'agostino et al., 2014) have demonstrated that irrespective of the vehicle type, driving habits such as speed management, favored acceleration rate, and vehicle stability significantly influence fuel consumption. Enhanced Driving Assistant Systems (ADAS) can be designed to offer more accurate and intelligent eco-driving guidance by effectively identifying connections between driving conduct and fuel consumption (Bengler et al., 2004;Barkenbus, 2010). ...
... Economic driving technology is a method to improve energy efficiency by controlling vehicle speed. Because of its advantages such as low application cost, wide application range and good energy-saving effect, it has been widely concerned by automobile manufacturers, researchers and drivers in recent years (Barkenbus, 2010;Su et al., 2019). In addition, the booming intelligent transportation system (ITS) in recent years has also provided strong support for the development of ecodriving technology. ...
Article
Full-text available
The energy efficiency of intelligent networked connected electric vehicle (EV) is directly related to its velocity. Aiming at the influence of real-time traffic flow information on road speed interval, a two-layer speed planning method is proposed. The upper layer extracts the road speed interval according to the traffic flow information, and based on cellular automata and confidence interval theory, traffic information rules are introduced, and a road speed interval extraction method considering traffic density information is established. The lower layer is used to obtain energy-optimal cruising velocity profile. Taking the road speed interval as the variable boundary constraint, a dynamic programming algorithm that changes the state quantity boundary in real time is designed, which realizes the efficient acquisition of the energy-optimized velocity trajectory. To verify the effectiveness of proposed approach, the simulation model is formulated based on using collected real traffic information. The simulation results demonstrate that, compared with the conventional constant speed cruising strategy and dynamic programming (DP) strategy based on road speed interval, the strategy proposed in this study not only improves energy efficiency and reduces computing time significantly, but also can predict the traffic conditions ahead to avoid large fluctuations in velocity. Besides, the biggest significance of this study is the designed economic velocity planning algorithm based on real-time traffic density information improves the adaptability of intelligent networked connected EV control strategy to actual traffic conditions, and extends the optimization dimension of eco-driving.
... For one thing, the driving cost to the individuals and the companies can be reduced. For another, when developing energy-efficient driving strategies, safety conditions are also included, so as to reduce accidents and traffic fatalities [51]. Hence, the goal of energy-efficient driving technology is to help the driver choose a CO2-reduction driving strategy under some safety and law conditions [50]. ...
Article
Full-text available
The transportation sector remains a major contributor to greenhouse gas emissions. The understanding of energy-efficient driving behaviors and utilization of energy-efficient driving strategies are essential to reduce vehicles’ fuel consumption. However, there is no comprehensive investigation into energy-efficient driving behaviors and strategies. Furthermore, many state-of-the-art AI models have been applied for the analysis of eco-friendly driving styles, but no overview is available. To fill the gap, this paper conducts a thorough literature review on ecological driving behaviors and styles, and analyzes the driving factors influencing energy consumption and state-of-the-art methodologies. With a thorough scoping review process, thirty-seven articles with full text were assessed, and the methodological and related data are compared. The results show that the factors that impact driving behaviors can be summarized into eleven features including speed, acceleration, deceleration, pedal, steering, gear, engine, distance, weather, traffic signal, and road parameters. This paper finds that supervised/unsupervised learning algorithms and reinforcement learning frameworks have been popularly used to model the vehicle’s energy consumption with multi-dimensional data. Furthermore, the literature shows that the driving data are collected from either simulators or real-world experiments, and the real-world data are mainly stored and transmitted by meters, controller area networks, onboard data services, smartphones, and additional sensors installed in the vehicle. Based on driving behavior factors, driver characteristics, and safety rules, this paper recommends nine energy-efficient driving styles including four guidelines for the drivers’ selection and adjustment of the vehicle parameters, three recommendations for the energy-efficient driving styles in different driving scenarios, and two subjective suggestions for different types of drivers and employers.
... The energy 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 [1][2][3]. As a method of energy conservation and environmental sustainability, eco-driving has attracted considerable research interest over the past two decades [4][5][6]. Eco-driving is an emerging research field, and its definition is not yet strictly defined. However, it generally refers to the practice of driving vehicles in a way that improves fuel economy [7][8][9]. ...
Article
Full-text available
In this study, we focused on the eco-driving of electric vehicles (EVs). The target vehicle is an electric bus developed by our research team. Using the parameters of the bus and speed pattern optimization algorithm, we derived the EV’s eco-driving speed pattern. Compared to the eco-driving of internal combustion engine vehicles (ICVs), we found several different characteristics. We verified these characteristics with actual vehicle driving test data of the target bus, and the results confirmed its rationality. The EV’s eco-driving method can improve electricity consumption by about 10–20% under the same average speed.
... De acuerdo con Barkenbus [17] sugiere que la conducción ecológica logra reducir el consumo de combustible en un 10 %, en promedio y con el tiempo, reduciendo así las emisiones de CO 2 derivadas de la conducción en un porcentaje equivalente. Por su parte, Mensing et al. [18] descubrieron que, debido al mayor tiempo empleado en el funcionamiento del motor con alta aceleración, se incrementan las emisiones y el consumo de combustible. ...
Article
Full-text available
En los últimos años, el ambiente se ha visto afectado a causa de la contaminación producida por los vehículos. El presente proyecto de investigación tuvo como objetivo determinar la incidencia del aire acondicionado (A/C) en el índice de consumo de combustible vehicular en el cantón Shushufindi, por medio de pruebas reales de tráfico, modo de conducción eficiente y empleo de gasolina extra y súper, para la selección de la mejor alternativa. El estudio se realizó en una ruta de mayor flujo de vehículos, especialmente en la hora normal (9 a. m.) y pico (5 p. m.) que comprende 16.17 km, para ello se utilizó el combustible Extra (85 octanos) y Súper (92 octanos). La toma de datos se ejecutó mediante un sistema OBD2 ELM 327. Los resultados obtenidos en la caracterización del ciclo mixto representativo de 9 a. m. se obtuvo una velocidad máxima de 81 km/h y una velocidad media de 39 km/h en un tiempo de recorrido de 1446 s; mientras que el ciclo mixto de 5 p. m. la velocidad máxima es de 70 km/h y una velocidad media de 37 km/h con un tiempo de recorrido de 1632 s. El menor índice de consumo de combustible se evidenció en el horario normal, sin A/C y combustible extra (T3) siendo sus valores entre 0.0584 – 0.060 (L/km), y en el horario normal, sin A/C y combustible súper (T7) que se encuentran entre 0.0561-0.0585 (L/km).
... Hjorthol and Fyhri (2009) reveal that most of the organized activities take place outside the immediate environment and that the most typical transportation for these activities is automobile. The human activity that contributes the most to air pollution is individual vehicle and automobile use (Barkenbus, 2010). It is known that a significant part of the amount of carbon footprint that causes climate change is the reason for transportation distances and this situation is caused by intensive personal vehicle use (Mehrotra et al., 2011). ...
Article
Full-text available
The most important factor in the emergence and growth of climate change and environmental problems is people’s transportation preferences. In this context, the aim of the research is to calculate the carbon footprint of individuals participating in camping activities in Turkey and Lithuania in the summer of 2022. In the study, the emission factors of preferred airplanes, urban buses and personal vehicles were used in the carbon footprint calculation process. In this research, the distance travelled by the individuals participating in the camping activities in Turkey and Lithuania in the summer period of 2022 with the travel vehicles they prefer for transportation was used. The total distance travelled in a summer period is 330,015 km in Turkey, the total distance travelled in a summer period is 132,331 km in Lithuania. In the analysis of the data set obtained through the official institutions from both countries and in the calculation of the carbon footprint, the emission factors of the preferred aircraft, urban buses and personal vehicles were used. According to the analysis, the total carbon footprint calculated for both countries is 73.54 tons. While the carbon footprint calculated for Turkey is 46.51 tons; for Lithuania, it is 23.83 tons. Depending on the travels made in Turkey, the average per capita carbon footprint is 10.70 kg, while in Lithuania it is 4.38 kg. The average per capita carbon footprint calculated for both countries is 15.08 kg. Regardless of their travel preference, the travels of people in both countries cause carbon footprints and contribute to the global climate change problem. It is seen that airway vehicles are used in Turkey due to the distances being much longer and this situation enlarges the carbon footprint. In Lithuania, the prominent carbon source is individual vehicle use.
... The well-known ecodriving techniques include proper maintenance of the vehicle, reducing the mass and aerodynamic drag, operating the vehicle at the appropriate speed and gear level to obtain the engine's optimum efficiency point, avoiding sudden starts and stops, accelerating quickly and smoothly as well as decelerating gradually when it is necessary, anticipating the surrounding environment, and so on. Barkenbus (2010) reported that these fuel efficient driving techniques reduce fuel consumption by 10% on average. A study using 19,230 driving patterns collected in real traffic was carried out by Ericsson (2001) to identify independent driving pattern factors and Fuel consumption is greatly influenced by road gradients. ...
Article
This paper explores the possibility of using recorded road slope data in order to reduce fuel consumption for off-road construction vehicles such as articulated haulers. Road gradients have strong influence on the fuel consumption of a vehicle. This effect is even more significant on construction vehicles due to their large mass and heavy load. In this study, a control algorithm based on model predictive control and dynamic programming is formulated and solved to find an optimal gear shift sequence and time of shifting. The fuel consumption model of an articulated hauler is formulated with a dynamic model and used together with the travel time in the objective function to balance the trade-off between these two aspects. The proposed control algorithm is simulated on a typical road stretch on the construction work site with frequent steep up- and downhill. Simulation shows that both fuel consumption and travel time can be reduced simultaneously. In addition, the optimal gear shift sequence resembles the behaviour of an experienced driver.
... Concept of Corporate Social Responsibility (CSR) that was introduced during the latter half of twentieth century also often played the green card with high probability of alienating customers when the policy of the corporation was at odds with what was presented through communication [5]. However, more and more individuals, companies and activists were using tools and practices of public relations [6] to convey a message and incite actions important not only for environmental protection but also for adaptation of new beliefs, habits and behaviors that could improve different important environmental and social issues. ...
Article
Full-text available
Public education campaigns and strategically used public relations tactics could enhance broad goals of environmental protection and restoration through building awareness and enticing to action. In case study of Boranka, one of the most successful non-profit ecological campaigns it is presented how by using element of green marketing, smart PR strategies, easy-to-use tools and engaging, emotinal story a number of people could be brought together into collective eco-friendly action. Over the course of four years Boranka resulted in more than 100,000 new trees that have been planted in burned areas throughout Croatia with more than 8,500 volunteers participating in seeding activities while over the HRK 2,170,000 (over the €288,000) was collected in funds and almost HRK 5,000,000 (about €664,000) in material goods, services and advertising space.
... Energy conservation: Improved energy efficiency and the rational use of energy should be supported by government programs. This can include industrial [114], agricultural [115], transportation [116,117], sustainable cities [118], residential [119] and at the household level [120] energy efficiency in the developed world as well as the developing world [121]. Energy efficiency, however, is not enough to bring emissions to acceptable levels [122]. ...
Preprint
Full-text available
When attempting to quantify future harms caused by carbon emissions and to set appropriate energy policies, it has been argued that the most important metric is the number of human deaths caused by climate change. Several studies have attempted to overcome the uncertainties associated with such forecasting. In this article, approaches to estimating future human deaths tolls from climate change are compared and synthesized, and implications for energy policy are considered. Several studies are consistent with the “1000-ton rule,” according to which a future person is killed every time 1000 tons of fossil carbon are burned (order-of-magnitude estimate). If warming reaches or exceeds 2°C this century, mainly richer humans will be responsible for killing roughly 1 billion mainly poorer humans through anthropogenic global warming. Such mass manslaughter is clearly unacceptable. On this basis, relatively aggressive energy policies are summarized that would enable immediate and substantive decreases to carbon emissions. The limitations to such calculations are outlined and future work is recommended to accelerate the decarbonization of the global economy while minimizing the number of sacrificed human lives.
... Hjorthol and Fyhri (2009) reveal that most of the organized activities take place outside the immediate environment and the most typical means of transportation to these activities are air and road transport. The human activity that contributes the most to environmental degradation, especially in sports branches with a busy competition schedule such as basketball, is the preference of land and air transportation vehicles (Barkenbus, 2009). ...
Article
Full-text available
Today, the sports industry is one of the most important sources of concern due to its negative environmental effects. Especially due to the intense competition schedule, teams and fans have to travel constantly. In this context, the aim of this study, which aims to fill the gap in the literature, is to calculate the carbon footprints of the teams in the Turkish and Lithuanian national basketball leagues based on their travels in the 2021–22 season. The research was limited to Turkey and Basketball national basketball league teams. In the study, the travel distances of the teams in both countries during the 2021–22 basketball season were used as a data set. In the study, the values used in the carbon footprint calculation of 2022 by the United Kingdom Government GHG Conversion Factors for Company Reporting and accepted as the IPCC carbon dioxide emission factor were used. While the carbon footprint, which is obtained by multiplying the emission factor directly by the distance covered by the vehicle type, is presented in tons; The average value calculated for each person was calculated in kg. In the sports sector, basketball is one of the most important sources of transportation-related carbon footprint due to its being one of the team sports and its intense competition schedule. According to the results of this research conducted specifically for Turkey and Lithuania, the total carbon footprint calculated for both countries is 53,029 tons. To make an assessment for both countries, in order to reduce travel based on sports; Arranging league calendars to include less travel, dissemination of green and clean energy-using (electric) vehicles, raising the awareness of club managers, developing environmental assessment policies specific to basketball federations, and increasing cooperation through awareness and training activities seem feasible for sustainable environment and basketball goals.
... Although fossil fuels are burned in the production of lithium-ion batteries needed for electric cars (Beak et al., 2020), driving an electric car reduces fuel consumption, and subsequently carbon-dioxide output, by 10 percent over time (Barkenbus, 2010). Not only are battery-powered electric vehicles more eco-friendly, they are also more cost-effective, which may help motivate people to make the switch (Hao et al., 2017). ...
... Energy conservation: Improved energy efficiency and the rational use of energy should be supported by government programs. This can include industrial [122], agricultural [123], transportation [124,125], sustainable cities [126], residential [127] and at the household level [128] energy efficiency in the developed world as well as the developing world [129]. Energy efficiency, however, is not enough to bring emissions to acceptable levels [130]. ...
Article
Full-text available
When attempting to quantify future harms caused by carbon emissions and to set appropriate energy policies, it has been argued that the most important metric is the number of human deaths caused by climate change. Several studies have attempted to overcome the uncertainties associated with such forecasting. In this article, approaches to estimating future human death tolls from climate change relevant at any scale or location are compared and synthesized, and implications for energy policy are considered. Several studies are consistent with the “1000-ton rule,” according to which a future person is killed every time 1000 tons of fossil carbon are burned (order-of-magnitude estimate). If warming reaches or exceeds 2 °C this century, mainly richer humans will be responsible for killing roughly 1 billion mainly poorer humans through anthropogenic global warming, which is comparable with involuntary or negligent manslaughter. On this basis, relatively aggressive energy policies are summarized that would enable immediate and substantive decreases in carbon emissions. The limitations to such calculations are outlined and future work is recommended to accelerate the decarbonization of the global economy while minimizing the number of sacrificed human lives.
... The application of DRL to the above methods has achieved good results in vehicle-following control; however, in the speed control of fuel cell buses, driving economy is also important and cannot be ignored. At present, scholars have promoted the theory of ecological driving [39], paying more attention to the interaction between the vehicle itself and the traffic environment to achieve the safe driving of the vehicle while also saving energy and protecting the environmental [40]. ...
Article
Full-text available
In the vehicle-to-everything scenario, the fuel cell bus can accurately obtain the surrounding traffic information, and quickly optimize the energy management problem while controlling its own safe and efficient driving. This paper proposes an energy management strategy (EMS) that considers speed control based on deep reinforcement learning (DRL) in complex traffic scenarios. Using SUMO simulation software (Version 1.15.0), a two-lane urban expressway is designed as a traffic scenario, and a hydrogen fuel cell bus speed control and energy management system is designed through the soft actor–critic (SAC) algorithm to effectively reduce the equivalent hydrogen consumption and fuel cell output power fluctuation while ensuring the safe, efficient and smooth driving of the vehicle. Compared with the SUMO–IDM car-following model, the average speed of vehicles is kept the same, and the average acceleration and acceleration change value decrease by 10.22% and 11.57% respectively. Compared with deep deterministic policy gradient (DDPG), the average speed is increased by 1.18%, and the average acceleration and acceleration change value are decreased by 4.82% and 5.31% respectively. In terms of energy management, the hydrogen consumption of SAC–OPT-based energy management strategy reaches 95.52% of that of the DP algorithm, and the fluctuation range is reduced by 32.65%. Compared with SAC strategy, the fluctuation amplitude is reduced by 15.29%, which effectively improves the durability of fuel cells.
... The behavior exhibited by drivers reinforces their degree of awareness and comprehension. According to Barkenbus (2010), drivers can enhance their understanding and adoption of environmentally friendly habits by using sustainable driving techniques and observing the subsequent positive environmental outcomes. Raising awareness, taking action, and providing reinforcement are instrumental in promoting sustainable transportation and mitigating carbon emissions (Outay, 2019). ...
... Previous research utilized clustering algorithms to distinguish between various driving styles (e.g., aggressive, conservative, and moderate) and subsequently compared electricity consumption across these styles (Barkenbus 2010;Bengler et al. 2014;Reverdiau et al. 2021). However, due to the variations in defining driving styles, its applicability in providing both general and detailed recommendations for energy-saving driving techniques remains limited. ...
Article
Full-text available
Electric buses (EBs) are gaining popularity worldwide as a more sustainable and eco-friendly alternative to diesel buses (DBs). Electricity-saving driving plays a crucial role in minimizing an EB’s energy consumption, subsequently leading to an extended driving range. This study proposes a machine learning–based framework for identifying electricity-saving EB driving behaviors during various driving stages, including running on road segments, entering bus stops/intersections, and exiting bus stops/intersections. The proposed random forest (RF) model effectively evaluates the energy consumption level using EB drivers’ historical driving data under different scenarios. Specifically, the electricity consumption factor (ECF), as the evaluation index, is divided into three categories to determine the implicit relationship between driving behavior and energy consumption. The results indicate that the classification accuracy of RF models surpasses 90%, which highlights the effectiveness in accurately identifying energy-efficient EB driving behaviors. In addition, the Shapley additive explanations (SHAP) and partial dependency plots (PDPs) are utilized to visualize and interpret the results of RF models. A speed interval of 30–40 km/h is identified as the most energy-efficient range for EB running on a road segment. Findings from this study can be applied to targeted optimization of electricity-saving driving strategies in different driving scenarios to improve the overall efficiency and sustainability of the transportation system.
... The authors explain the better efficiency of experienced drivers with a different usage of the gas pedal. Barkenbus (2010) summarizes fuel-efficient driving behavior (so-called eco-driving) with the following aspects: moderate acceleration, early gear-shifting, anticipative driving, maintaining an even driving pace, driving at or below the speed limit, and eliminating excessive idling. ...
Article
Full-text available
Eco-riding assistance systems on electrified powered two-wheelers aim at decreasing energy consumption. However, the efficiency of such systems depends on the riders' behavior. Therefore, the present paper evaluates an eco-riding assistance system giving recommendations for regenerative braking, coasting, and sailing regarding compliance, transfer effects, energy consumption, and acceptance. N = 31 participants had to complete a test course including highway, rural roads, and urban riding in a purpose-built E-scooter simulator. A between-subjects study design with three groups was chosen to determine possible effects: (1) Control condition without any assistance; (2) Basic condition with recommendations triggered by vehicle-or map-based data; (3) Comprehensive condition with recommendations based on vehicle-, map-, and Vehicle-to-everything (V2X)-based data. Due to the multitude of sensors, the comprehensive condition received more recommendations than the basic condition. The riders of the basic and comprehensive condition received no recommendations on the last section of the test course to assess possible transfer effects. Riders with assistance ride slower and sail more often than the control group. This is valid also for sections without riding recommendations. Overall, the riders with assistance have a lower energy consumption on sections with coasting recommendations (Basic condition: 18.2 % less energy consumption; Comprehensive condition: 12.8 %) and on sections without any eco-riding assistance (Basic condition: 9.5 %; Comprehensive condition: 8.2 %). The frequency of recommendations has no effect on the efficiency as the basic condition and the comprehensive condition show comparable riding behavior and do not differ regarding energy consumption. Finally, all the participants rate all three recommendation types as positive. Altogether, the results endorse the benefit of eco-riding assistance for electrified powered two-wheelers concerning energy efficiency and provide indications for the design of such systems.
Chapter
Full-text available
We recommend providing state-supported financial incentives and benefits for vehicle insurance policies using telematics. To achieve this policy recommendation, we propose the following: (1) Provision for financial incentives and benefits by the state for vehicle insurance policies using telematics across the European Union member states; (2) Conduct comprehensive social cost–benefit analysis (CBA) to assess policy feasibility, either at a European Union or at a national level; (3) Advocate for European Union-level policy implementation supported by a centralized fund to promote telematics via insurance policies, aligning with the EU Green Deal and Vision Zero targets; and (4) Showcase benefits of interdisciplinary collaboration involving experts from transportation engineering, economics, psychology, and law for policy design and evaluation.
Article
Full-text available
We have proposed a three-pronged approach to identify sustainable practices during road construction: (1) Route segmentation and identification of drive phases, including loading and dumping stages; (2) Use of Digital Elevation Models (DEM) and digital terrain models(DTM) acquired by UAVs to measure progress of construction from volumetric changes; and (3) Use of vegetation indices derived from satellite imagery to calculate changes in carbon stock. The paper introduces a novel technique for identifying driving phases for heavy trucks based only on GPS data. We also delve into how these approaches can serve as the foundational elements in the creation of digital twins tailored to the construction industry.
Chapter
This study investigates the relationship between drivers’ electrodermal activity (EDA) and their eco-driving behaviours through real-time monitoring. Electrodermal activity, a physiological marker of sympathetic nervous system arousal, reflects emotional and cognitive states, providing a valuable window into drivers’ internal experiences. EDA and driving data were collected for 48 trips from 10 different drivers. Cluster analysis and the Pearson correlation coefficient was used to uncover potential patterns between driver EDA and their driving behaviour as measured using a driving score. The results follow the Yerkes-Dodson Law. Driving performance increase with EDA arousal, but only to a point. The investigation has implications for enhancing road safety, as it contributes to our understanding of how drivers’ emotional states influence their on-road performance. Additionally, it holds promise for developing innovative in-car systems that can adapt to drivers’ changing emotional states, promoting safer and more comfortable driving experiences. Ultimately, this study bridges the gap between psychophysiology and transportation, shedding light on the often-overlooked emotional aspects of driving behaviour.
Article
Objective The effects of three prototypical designs of energy consumption displays on energy-specific situation awareness were examined. Background Energy efficiency is crucial for the sustainability of technical systems. However, without accurate situation awareness of energy dynamics (energy dynamics awareness, EDA) it can be challenging for humans to optimize the use of energy resources of electric vehicles (EVs) through their behavior. Method We examined three prototypical energy display designs that varied by their informational value to support EDA. Furthermore, we investigated the differential effects on EDA measured by (1) a newly constructed scale (experienced EDA), (2) estimating energy consumption, and (3) identifying efficient trips in an online experiment. Participants ( N = 82) watched standardized driving scenes (videos) of EV trips presenting the energy displays. Results We found a strong effect of display type on experienced EDA, with the trace display being the most supportive. The EDA scale showed excellent internal consistency. The consumption estimation and efficient trip identification indicators were not affected by the display type. Conclusion The study indicates that experienced EDA is immediately affected by displays with higher information value, but performance might need more time and training. More research is needed to investigate the cognitive processes related to EDA and to examine how distinct display elements enhance EDA. Application Results from this research can be used as guidance for the design of energy displays, especially in EVs. The EDA scale can be used as an evaluation measure in the human-centered design process of energy displays.
Article
Full-text available
In recent years the environment has been affected by pollution produced by vehicles. The objective of this research project was to determine the incidence of air conditioning (A/C) in the vehicular fuel consumption index in the Shushufindi canton, through real traffic tests, Efficient driving mode and the use of Extra and Super gasoline, for the selection of the best alternative. The study was carried out on a route with a greater flow of vehicles, especially during normal (9:00 am) and beak (5:00 pm) hours, which comprises 16.17 km; for which used gasoline Extra (85 octane) and Super (92 octane). Data collection was carried out using an OBD2 ELM 327 system. The results obtained in the characterization of the representative mixed cycle at 9:00 am, a maximum speed of 81 km/h and an average speed of 39 km/h were obtained in a time of 1446 s route; while the mixed cycle at 5:00 pm the maximum speed is 70 km/h and an average speed of 37 km/h with a travel time of 1632 s. The lowest fuel consumption index was evidenced in normal hours, without A/C and Extra fuel (T3) with values between 0.0584 - 0.060 (L/km), and in normal hours, without A/C and super fuel (T7) that are between 0.0561- 0.0585 (L/km).
Article
This paper presents an adaptive leading cruise control strategy for the automated vehicle (AV) and first considers its impact on the following human-driven vehicle (HDV) with diverse driving characteristics in the unified optimization framework for improved holistic energy efficiency. The car-following behaviors of HDV are statistically calibrated using the Next Generation Simulation dataset. In a typical single-lane car-following scenario where AVs and HDVs share the road, the longitudinal speed control of AVs can substantially reduce the energy consumption of the following HDV by avoiding unnecessary acceleration and braking. Moreover, apart from the objectives including car-following safety and traffic efficiency, the energy efficiencies of both AV and HDV are incorporated into the reward function of reinforcement learning (RL). The specific driving pattern of the following HDV is learned in real-time from historical speed information to predict its acceleration and power consumption in the optimization horizon. A comprehensive simulation is conducted to statistically verify the positive impacts of AV on the holistic energy efficiency of the mixed traffic flow with uncertain and diverse human driving behaviors. In freeway driving scenarios, simulation results indicate that the holistic energy efficiency is improved by an average of 6.03% and 6.41% compared to the reference control algorithms, specifically, RL without HDV consideration and model predictive control. These improvements highlight the significance of our approach in optimizing energy efficiency for mixed traffic on freeways.
Chapter
The paper is devoted to the problem of information provision of energy-efficient automatic control of vehicles on highways. Comprehensive measures are proposed for the transmission of data flow to on-board controllers of vehicles, which makes it possible to avoid radio signal interference. The main technical means of the proposed system are unmanned aerial vehicles equipped with emitters and direction finders of radio signals, which are able to communicate with motor vehicles, with each other, as well as with immovable roadside infrastructure objects. These objects play the role of markers for the automatic flight of drones along the highway and means of saving fragments of the data stream. Every vehicle on the highway has access to the 3D trajectory and road conditions at least 4 km ahead on the chosen route, thanks to the use of markers with a constant distance between them and drones that fly precisely along the highway, against the direction of traffic. Simulation modeling of information system functioning with different numbers of markers was carried out. The deviation of the average cruising speed forecast from the value obtained as a result of simulation was determined. It was established that the accuracy of forecasting significantly depends on the horizon and the number of markers. Reducing the horizon to less than 1 km and the number of markers to less than 25 is impractical, as the error can exceed 50%. At the same time, the highest prediction accuracy was achieved at the level of 2.8%.
Article
To suppress CO2 emissions through policies and technology development, eco-driving techniques are required to be actively practiced as an effective method to improve fuel efficiency. Among the methods to practice eco-driving, the active eco-mode is a function that changes the driving mode of a vehicle by the driver’s choice. This study aims to analyze the effect of driving modes (normal-mode, eco-mode) on CO2 emissions through on-road tests under different driving conditions. The eco-mode activation under normal temperature conditions emitted relatively less CO2 emissions than the normal-mode driving. Under high-temperature conditions, fuel economy deteriorated since an additional load was required for heating, ventilating, and air conditioning (HVAC) system operation. However, when using the eco-mode, the control of the HVAC system was integrated with the effect of powertrain logic, which achieved a higher reduction rate of CO2 emissions than the normal temperature condition. In particular, the impact of reducing fuel consumption was confirmed in the urban section with many stops and departures, which is determined to result from a combination of gear shifting and acceleration pedal filtering strategies. Meanwhile, the eco-mode logic has not been applied much in rural and motorway sections.
Chapter
The effort to accelerate social life and to ensure the balance of production and consumption and the widespread use of mass media brought a significant improvement in human life.
Article
This article proposes a locally convergent, computationally efficient model predictive controller with mode switching decisions for the eco-driving problem of electric trucks. The problem is formulated as a bi-level program where the high-level optimises the speed trajectory and operation mode implicitly, while the low-level computes an explicit policy for power distribution of two electric machines. The alternating direction method of multipliers (ADMM) is employed at the high-level to obtain a locally optimal solution considering both speed optimisation and integer switching decisions. Simulation results indicate that the ADMM operates the powertrain with 0.9%0.9 {\%} higher total cost and 0.86%0.86 {\%} higher energy consumption than the global optimum obtained by dynamic programming for a quantised version of the same problem. Compared to a benchmark solution that maintains a constant velocity, the ADMM, running in a model predictive control framework (ADMM_MPC), operates the powertrain with a 8.77%8.77 {\%} lower total cost and 10.3%10.3 {\%} lower energy consumption, respectively. The average time for each ADMM_MPC update is 4.6ms4.6 \,\mathrm{ms} on a standard PC, indicating its suitability for real-time control. Simulation results also show that the prediction errors of speed limits and road slope in ADMM_MPC cause only 0.12%0.12 {\%}0.56%0.56 {\%} performance degradation.
Article
Full-text available
Tested the hypothesis that providing immediate feedback to homeowners concerning their daily rate of electricity usage would be effective in reducing electricity consumption. In the 29 physically identical 3-bedroom homes used in the study, central air conditioning was the largest single source of electricity usage during the summer. Accordingly, it was possible to predict the household's expected electricity consumption in terms of the average daily outdoor temperature. Feedback was expressed as a percentage of actual consumption over predicted consumption, and it was displayed to the homeowners 4 times/wk for approximately 1 mo. Results confirm the hypothesis. Before feedback began, the feedback and control groups were consuming electricity at approximately equal rates. During the feedback period, the feedback group used 10.5% less electricity. The effectiveness of the feedback procedure is discussed in terms of its cuing, motivational, and commitment functions. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Article
Full-text available
The individual and household sector generates roughly 30 to 40 percent of U.S. greenhouse gas emissions and is a potential source of prompt and large emissions reductions. Yet the assumption that only extensive government regulation will generate substantial reductions from the sector is a barrier to change, particularly in a political environment hostile to regulation. This Article demonstrates that prompt and large reductions can be achieved without relying predominantly on regulatory measures. The Article identifies seven "low-hanging fruit:" actions that have the potential to achieve large reductions at less than half the cost of the leading current federal legislation, require limited up-front government expenditures, generate net savings for the individual, and do not confront other barriers. The seven actions discussed in this Article not only meet these criteria, but also will generate roughly 150 million tons in emissions reductions and several billion dollars in net social savings. The Article concludes that the actions identified here are only a beginning, and it identifies changes that will be necessary by policymakers and academicians if these and other low-hanging fruit are to be picked.
Article
Full-text available
Individuals are the largest source of dioxin emissions, contribute almost one-third of all ozone precursor emissions, and are a far larger source of several other air toxics than all large industrial sources combined. Thus, after more than 30 years of regulation largely directed at industry, individual behavior has emerged as a leading source of pollution. Professor Michael P. Vandenbergh argues that treating individual behavior as a discrete source of pollution can lead to the development of viable, innovative regulatory instruments that have the prospect of achieving pollution reductions at a relatively low cost. The creation of an individual toxic release inventory, for example, is one such tool. Drawing on the work of norms scholars and leading social psychologists, Professor Vandenbergh argues that environmental norm activation theory can identify the information that is most likely to induce changes to environmental behavior and can help policymakers develop new tools for inducing such change.
Article
Full-text available
This article reviews and evaluates the effectiveness of interventions aiming to encourage households to reduce energy consumption. Thirty-eight studies performed within the field of (applied) social and environmental psychology are reviewed, and categorized as involving either antecedent strategies (i.e. commitment, goal setting, information, modeling) or consequence strategies (i.e. feedback, rewards). Particular attention is given to the following evaluation criteria: (1) to what extent did the intervention result in behavioral changes and/or reductions in energy use, (2) were underlying behavioral determinants examined (e.g. knowledge, attitudes), (3) to what extent could effects be attributed to the interventions and, (4) were effects maintained over longer periods of time? Interestingly, most studies focus on voluntary behavior change, by changing individual knowledge and/or perceptions rather than changing contextual factors (i.e. pay-off structure) which may determine households’ behavioral decisions. Interventions have been employed with varying degrees of success. Information tends to result in higher knowledge levels, but not necessarily in behavioral changes or energy savings. Rewards have effectively encouraged energy conservation, but with rather short-lived effects. Feedback has also proven its merits, in particular when given frequently. Some important issues cloud these conclusions, such as methodological problems. Also, little attention is given to actual environmental impact of energy savings. Often, an intervention's effectiveness is studied without examining underlying psychological determinants of energy use and energy savings. Also, it is not always clear whether effects were maintained over a longer period of time. Recommendations are given to further improve intervention planning and to enhance the effectiveness of interventions.
Article
Full-text available
Continuous-display, electricity-use monitors provide more comprehensive electricity cost information than previously considered initiatives. This study analyzes the effect of monitor-provided information on consumers' monthly peak period, off-peak period, and total electricity consumption using an ANCOVA framework. Results indicate that monitoring did not induce conservation but did significantly contribute to shifting electricity use from peak to off-peak periods.
Article
Reducing the risk of catastrophic climate change will require leveling off greenhouse gas emissions over the short term and reducing emissions by an estimated 60-80% over the long term. To achieve these reductions, we argue that policymakers and regulators should focus not only on factories and other industrial sources of emissions but also on individuals. We construct a model that demonstrates that individuals contribute roughly one-third of carbon dioxide emissions in the United States. This one-third share accounts for roughly 8% of the world's total, more than the total emissions of any other country except China, and more than several continents. We contend that it is desirable, if not imperative, that governments address emissions from individual behavior. This task will be difficult because individual behaviors, including idling cars and wasting electricity, are resistant to change, even when the change is rational. Mindful of the costs, we propose measures that have a high likelihood of success. We draw on norms theory and empirical studies to demonstrate how legal reforms can tie the widely held abstract norm of personal responsibility to the emerging concrete norm of carbon neutrality. We suggest that these legal reforms could push carbon neutrality past a tipping point, directly influencing many carbon-emitting individual behaviors and building the public support necessary for policymakers to address the remaining sources.
Article
Historically, a sectoral approach (based on the industrial, transportation, commercial, and residential sectors) has shaped the way we frame and analyze issues of energy conservation and CO2 mitigation. This sectoral categorization, however, is limited in its capacity to reveal the total impacts of consumer activities on energy use and its related environmental impacts. In this paper, we propose an alternative paradigm, called the Consumer Lifestyle Approach (CLA), to explore the relationship between consumer activities and environmental impacts in the US. Estimates based on our methodology reveal that more than 80% of the energy used and the CO2 emitted in the US are a consequence of consumer demands and the economic activities to support these demands. Direct influences due to consumer activities (home energy use and personal travel) are 4% of the US GDP, but account for 28% and 41% of US energy use and CO2 emissions, respectively. Indirect influences (such as housing operations, transportation operations, food, and apparel) involve more than twice the direct energy use and CO2 emissions. Characterization of both direct and indirect energy use and emissions is critical to the design of more effective energy and CO2 emission policies. It may also help erode the false dichotomy of “them versus us” (industrial polluters versus consumers) references to the locus of responsibility for control of energy use and CO2 emissions.
Article
The transition from oil to electricity for personal transportation is underway with virtually every automaker now seeking to produce an electrical automobile, of some form, under its brand. The pace of this transition, however, is dependent upon both technical and institutional changes. Electricity has the opportunity to play both a disruptive role in transportation and a transformational role in renewable energy, to the benefit of moderating climate change. In transportation, electricity can be both a cleaner and cheaper fuel than petroleum. Moreover, automobile batteries can play a pivotal role in enhancing the use of renewable energies in our daily lives. Development of the full potential of this transformation awaits the formulation of an innovative and clever business plan or value package that integrates the automobile industry with a changing electricity sector.
Article
The idea of driver energy conservation awareness was formalized as a training program (DECAT) by the Department of Energy in the late 1970's. This report reviews the curriculum of that program, its basis in engineering tests and principles, its past activities and achievements, and its potential, and makes recommendations for a renewed program. There is ample evidence that typical drivers can reduce fuel consumption by at least 10% by the way they maintain and operate their vehicles. The original DOE program was reasonably successful in reaching motor vehicle fleets, especially in government. Challenges for a new DECAT program include increasing its outreach to the general motoring public, fostering research and transfer to the marketplace of effective driver feedback devices, and incorporating DECAT training into the driver education and licensing process, nationwide. Depending on the effectiveness of DECAT, motor fuel savings could range up to 10 billion gallons annual.
Article
This article develops a conceptual framework for advancing theories of environ- mentally significant individual behavior and reports on the attempts of the author's research group and others to develop such a theory. It discusses defini- tions of environmentally significant behavior; classifies the behaviors and their causes; assesses theories of environmentalism, focusing especially on value-belief-norm theory; evaluates the relationship between environmental concern and behavior; and summarizes evidence on the factors that determine environmentally significant behaviors and that can effectively alter them. The article concludes by presenting some major propositions supported by available research and some principles for guiding future research and informing the design of behavioral programs for environmental protection. Recent developments in theory and research give hope for building the under- standing needed to effectively alter human behaviors that contribute to environ- mental problems. This article develops a conceptual framework for the theory of environmentally significant individual behavior, reports on developments toward such a theory, and addresses five issues critical to building a theory that can inform efforts to promote proenvironmental behavior.
Article
Despite the large contribution of individuals and households to climate change, little has been done in the US to reduce the CO2 emissions attributable to this sector. Motor vehicle idling among individual private citizens is one behavior that may be amenable to large-scale policy interventions. Currently, little data are available to quantify the potential reductions in emissions that could be realized by successful policy interventions. In addition, little is known about the motivations and beliefs that underlie idling. In the fall of 2007, 1300 drivers in the US were surveyed to assess typical idling practices, beliefs and motivations. Results indicate that the average individual idled for over 16Â min a day and believed that a vehicle can be idled for at least 3.6Â min before it is better to turn it off. Those who held inaccurate beliefs idled, on average, over 1Â min longer than the remainder of the sample. These data suggest that idling accounts for over 93Â MMt of CO2 and 10.6 billion gallons (40.1 billion liters) of gasoline a year, equaling 1.6% of all US emissions. Much of this idling is unnecessary and economically disadvantageous to drivers. The policy implications of these findings are discussed.
Article
The development and manufacture of hybrid vehicles, which combine a conventional engine, and a battery-powered electric motor to achieve improved fuel economy and performance, are discussed. A full-fledged hybrid car, such as a Toyota Prius travels twice the distance that of an average American car on a gallon of gas. A full-fledged hybrid vehicle provides fuel economy of 60 percent, which is achieved from regenerative braking, that captures as electrical power much of the energy lost as frictional heat. Another benefit of the hybrid vehicles is that the efficient use of gasoline results in lower emissions of carbon dioxide, which is the primary greenhouse gas.
Impact of in-car instruments on driver behavior. Presentation at the Eco-Drive Workshop
  • K Kurani
Kurani, K., 2007. Impact of in-car instruments on driver behavior. Presentation at the Eco-Drive Workshop, Paris, November 22–23.
Transportation Energy Data Book Hybrid vehicles gain traction
  • Ed Article In Press Romm
  • J J Frank
Oak Ridge National Laboratory (ORNL), 2008. Transportation Energy Data Book, 27th ed. ARTICLE IN PRESS Romm, J.J., Frank, A.A., 2006. Hybrid vehicles gain traction. Scientific American 29 (4) April. Saynor, B., 2008. Energy Saving Trust—Ford Ecodriving Challenge 2008, November 12. ScanGauge, 2009 (found at: /http://www.scanguage.comS).
How technology can help trim auto insurance
  • M P Mcqueen
McQueen, M.P., 2008. How technology can help trim auto insurance. The Wall Street Journal, June 26. NIVD, 2008. Shaping Tomorrow's Drivers Today (found at: /http://www. drive2survive.orgS).
Utilities turn their customers green, with envy. The New York Times
  • L Kaufman
Kaufman, L., 2009. Utilities turn their customers green, with envy. The New York Times, January 31.
Energy reduction and environmental sustainability in surface transportation
  • T G Hodges
Hodges, T.G., 2009. Energy reduction and environmental sustainability in surface transportation. Testimony before the Subcommittee on Highways and Transit of the House Transportation and Infrastructure Committee, January 27.
Ford's fusion hybrid woos consumers
  • J B White
White, J.B., 2009. Ford's fusion hybrid woos consumers. The Wall Street Journal, January 6.
Residents in 3 communities try to outdo each other in the Energy Smackdown. The Boston Globe
  • D Copeland
Copeland, D., 2008. Residents in 3 communities try to outdo each other in the Energy Smackdown. The Boston Globe, August 17.
10 eco-driving tactics save gas
  • B Siuru
Siuru, B., 2008. 10 eco-driving tactics save gas (found at: /http://www.greencar. com/features/10-eco-driving-tactics-save-gas.phpS).
The behavior wedge: the potential for short-term greenhouse gas emissions reductions from household behavioral change in the United States
  • T Dietz
  • G Gardner
  • J Gilligan
  • P Stern
  • M Vandenbergh
Dietz, T., Gardner, G., Gilligan, J., Stern, P., Vandenbergh, M., 2009. The behavior wedge: the potential for short-term greenhouse gas emissions reductions from household behavioral change in the United States. Proceedings of the National Academy of Sciences (PNAS) 106(42), Oct. 20. Ehrhardt-Martinez, K., 2008. Behavior, energy and climate change: policy directions, program innovations, and research paths (an ACEEE report), November. Ecodrive.org, 2009 (found at: /http://www.ecodrive.orgS).
Nissan to put lead-foot gauge on all models
  • C Woodyard
Woodyard, C., 2007. Nissan to put lead-foot gauge on all models. USA Today, August 22. van den Berg, J., 2007. Ecodriving as a policy to reduce emissions. Presentation at the November 2007 IEA Workshop on Ecodriving, November 22.
GreenRoad and admiral partner to launch first ‘Pay How you Drive’ insurance scheme
  • Greenroad
GreenRoad, 2009. GreenRoad and admiral partner to launch first 'Pay How you Drive' insurance scheme. Press Release, February 9.
Ecodriving communication campaigns with the EU (a presenta-tion at the November IEA Workshop on Ecodriving)
  • P Wilbers
Wilbers, P., 2007. Ecodriving communication campaigns with the EU (a presenta-tion at the November IEA Workshop on Ecodriving), November 22.
Driver Efficiency Program Manual Transportation Energy Data Book, Edition 27 Light-duty automotive technology and fuel economy trends: 1975 through
  • Toyota
Toyota, 2008. Driving with the eco-driving indicator: helping you get better fuel economy (found at: /http://blog.lexus.com/2008/01/driving-with-th.htmlS), January 4. US Department of Energy (USDOE), 1980. Driver Efficiency Program Manual, May. US Department of Energy (USDOE), 2008. Transportation Energy Data Book, Edition 27. US Environmental Protection Agency (USEPA), 2008. Light-duty automotive technology and fuel economy trends: 1975 through 2008 (found at /http:// www.epa.gov/otaq/fetrends.htmS), September. US Environmental Protection Agency (USEPA), 2009. Greenhouse Gas Equivalen-cies Calculator, at /http://www.epa.gov/cleanenergy/energy-resources/calcu lator.htmlS.
Behavior and climate change (a presentation to the Vanderbilt Research Network Workshop)
  • L Lutzenhiser
Lutzenhiser, L., 2007. Behavior and climate change (a presentation to the Vanderbilt Research Network Workshop), August 24.
Denver's driving change program reduces vehicular CO 2 emissions (found at: /http://www.enviance.com/about-enviance/PressReleaseView.as px?id=53S) Ford tests show eco-driving can improve fuel economy by an average of 24 percent
  • Enviance
Enviance, 2009. Denver's driving change program reduces vehicular CO 2 emissions (found at: /http://www.enviance.com/about-enviance/PressReleaseView.as px?id=53S), January, 27. Ford Motor Company, 2008. Ford tests show eco-driving can improve fuel economy by an average of 24 percent, August 27.
Ford eco-driving: best practice training and evaluation
  • W Hennig
Hennig, W., 2008. Ford eco-driving: best practice training and evaluation, November 12.
Denver's driving change program reduces vehicular CO2 emissions
  • Enviance
Energy Saving Trust-Ford Ecodriving Challenge
  • B Saynor
Driving with the eco-driving indicator: helping you get better fuel economy
  • Toyota
Behavior, energy and climate change: policy directions, program innovations, and research paths (an ACEEE report
  • K Ehrhardt-Martinez
Hypermiling: quest for ultimate fuel economy
  • N Chapnick
Ecodriving as a policy to reduce emissions. Presentation at the
  • J Van Den Berg