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This paper presents the Italian Field Operation Test (FOT) to be performed within the European project euroFOT aimed at assessing a wide variety of Intelligent Transport Systems (ITS) across Europe. The Italian FOT in euroFOT is aimed at investigating the Lane Departure Warning system (LDW) equipped on Lancia Delta vehicles, deploying a sample of up to 300 vehicles and using a wide and differentiated set of self-reported questionnaires. Based on subjective responses, objective measures will be constructed using psychometric methods and models. Results will assess subjective user-related aspects and will be referred to LDW impact on driving safety, user acceptance of the system, usefulness and driving behaviour. Because of the psychometric methodology adopted, results are expected to accurately depict the actual impact of this function.
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Field Operational Tests and Naturalistic Driving Studies
Gianfranco Burzio1, Leandro Guidotti2, Guido Perboli3, Michele Settanni4,
Roberto Tadei3, Francesco Tesauri2
1Centro Ricerche FIAT, Strada Torino, 50, 10043 Orbassano (TO), Italy,
2Università di Modena e Reggio Emilia, Engineering Sciences and Methods
Department, via Amendola 2, 42122 Reggio Emilia, Italy,;
3Politecnico di Torino, Department of Control and Computer Engineering, Corso
Duca degli Abruzzi 24, 10129 Torino Italy,;
4Università di Torino, Department of Psychology, via Verdi 10, 10124 Torino,
ABSTRACT: This paper presents the Italian Field Operation Test (FOT) to be
performed within the European project euroFOT aimed at assessing a wide
variety of Intelligent Transport Systems (ITS) across Europe. The Italian FOT
in euroFOT is aimed at investigating the Lane Departure Warning system
(LDW) equipped on Lancia Delta vehicles, deploying a sample of up to 300
vehicles and using a wide and differentiated set of self-reported
questionnaires. Based on subjective responses, objective measures will be
constructed using psychometric methods and models. Results will assess
subjective user-related aspects and will be referred to LDW impact on driving
safety, user acceptance of the system, usefulness and driving behaviour.
Because of the psychometric methodology adopted, results are expected to
accurately depict the actual impact of this function.
1.1 Field Operational Test
The Intelligent Car Initiative (ICI) has identified road safety, energy, efficiency
and traffic congestion as the main challenges currently facing European
transportation. Despite their severity, these issues may be improved with the
use of new in-vehicle technologies recently made available in the market.
Intelligent Transport Systems (ITS) – including both safety and telematic
applications - have been the subject of significant research and development in
Europe in recent years and several models of passenger cars are now
equipped with these systems as optional features (e.g. ACC, FCW, LDW, BLIS,
etc.). However, implementing new technologies implies risks to manufacturers.
Factors such as impact of these systems on traffic safety, markets’ and users’
acceptance are difficult to assess alone from internal testing.
Moving from this preamble, European Commission launched - within the
Seventh Framework Programme (FP7) for research and technological
development – a large programme of Field Operational Tests (FOT) where
Human Centred Design for Intelligent Transport Systems
benefits of ITSs towards traffic safety and users’ acceptance will be largely
tested. In this context, euroFOT research project started (http://www.eurofot- with the main aim to demonstrate the effectiveness and encouraging the
deployment of intelligent vehicle systems on European roads.
1.2 euroFOT project
During the course of 2010, over 1000 vehicles will be tested from 9 European
OEM brands. Several test centres will be set-up across France, Germany, Italy
and Sweden [1]. The goal of euroFOT project is to identify and coordinate an in-
the-field testing of ITSs with the potential for improving the quality and safety of
European road traffic. euroFOT consortium has brought together 28 different
organizations across Europe (e.g. car manufacturers, suppliers, universities,
research institutes and others stakeholders) [1].
In details, euroFOT project will mainly address the following research issues: (i)
performance and capability of the systems; (ii) driver’s interaction with and
reaction to the systems; (iii) impacts of ITSs on safety, efficiency and
environment. In order to reach its objectives, the project is applying the
methodology that was developed in 2008 in the European FESTA project [2].
1.3 Functions to be tested in euroFOT project
Different field testing are expected in this project, focused on 8 distinct
functions. In particular: driver assistance in forward/rear longitudinal control
functions (i.e. Adaptive Cruise Control, Forward Collision Warning, Speed
Regulation System), in lateral control (i.e. Blind Spot Information System, Lane
Departure Warning and Impairment Warning), and finally other advanced
applications such as Curve Speed Warning, Fuel Efficiency Advisor and Safe
Human-Machine Interface [1].
The project will follow three major steps. In the first, the fleets are being
prepared for the trials specifying the functions, defining hypotheses for each of
the functions, setting up data management procedures, and recruiting the
drivers’ samples. Secondly, involving the installation of data loggers and
functionalities into the vehicles. Finally, analyzing data collected from the
vehicle monitoring devices and from the driver himself (the so-called objective
and subjective data).
This paper is focused to describe and highlight the preliminary results of the
Italian test site in the framework of the euroFOT project. The test will investigate
the LDW function available on the Lancia Delta (see Figure 1), namely the
Driving Advisor. In the euroFOT project, other test sites (i.e. German 1 and
Sweden test sites) will also test LDW function using a different experimental
method [1].
Field Operational Tests and Naturalistic Driving Studies
Fig.1. Lancia Delta
2.1 Lancia Lane Departure Warning system
This ADAS (i.e. Advance Driver Assistance System) solution available on the
Lancia Delta, with the market name of Driving Advisor, provides a feedback to
the driver through a torque applied on the steering wheel as soon as the driver
unintentionally is going close or overcome a lane border, when the proper
indicator is not activated (see Figure 2). This system uses a small camera
mounted on the rearing mirror to acquire images of the road in front of the
vehicle, then measuring the vehicle position relatively to the lane borders.
Fig. 2. Lancia Lane Departure Warning system
2.2 Design of Experiment and questionnaires
Italian FOT in the euroFOT project has the objective to select up to 250
customers/drivers of the LDW system and follow them in the first period of use,
i.e. 9 months [1]. During such period, drivers will provide their feedback
answering specific questionnaires or filling forms related to specific events that
happened during the vehicle usage and their subjective evaluation about the
LDW system.
Human Centred Design for Intelligent Transport Systems
The use of subjective data does not guarantee the same level of reliability
provided by objective data gathered from data loggers. Nonetheless, given the
aims of this project, the use of self-reported questionnaires is indicated because
it permits to collect data about phenomena which are not directly observable,
such as LDW user acceptance, driver reactions, subjective mental workload,
users’ trust in the system and so on.
The Design of Experiment (DoE) has been defined in order to improve as much
as possible the subsequent data analysis and to detect if there are significant
correlations between variables (see Figure 5). Therefore questionnaires have
been planned to be filled in by two different groups of users, called LDW Group
and Control Group, respectively. The first one (i.e. LDW Group) involves users
driving their own car (i.e. Lancia Delta) equipped with the LDW system. In a first
period of driving they should not use the LDW system ensuring a baseline
period. In subsequent treatment period the same group of drivers will be able to
use the LDW system and drive normally. This DoE will allow a within subject
analysis in the LDW Group of users in order to detect differences in driving
attitudes and behaviour, use of the system and the user acceptance of it over
the test period. The Control Group involves users driving their own car (i.e.
Lancia Delta) not equipped with the LDW system. Questionnaires will be also
filled in by these users but items related to LDW system use will be not
administered to them. Control Group questionnaires are focused in driving
attitudes and behaviours and in LDW system expectations. The Control Group
and this DoE will allow a between subject analysis with the LDW Group users.
Fig. 3. FOT Design of Experiment
About experimental procedures, five questionnaires are planned (see Figure 4).
They are directed to the vehicle main user. The first one is an introductory
questionnaire in which the major social and demographic characteristics of
drivers, including their driving habits, attitudes and behaviours will be collected.
Some standardized tools could be used to register these drivers’
characteristics. The Driving Behaviour Questionnaire (DBQ) will be used to
register the frequency of driving errors, violations and lapses judged by the
drivers themselves. In DBQ questionnaire the drivers have to base their
judgments on what they remember of their own driving over the past year [3].
The questionnaire will be filled in by drivers as soon as they accept to
participate to the project, well before, if possible, to get the vehicle.
A specific section of the first introduction questionnaire could register the risk
perception of the drivers facing them with a explained contest and asking how
often they engage in a behaviour like that or how likely they are getting in an
accident while doing that. That section is called Sensation Seeking
questionnaire [4]. Another standardized tool that will be used in the second
Field Operational Tests and Naturalistic Driving Studies
questionnaire is the Driving Style Questionnaire (DSQ) that examines how
drivers usually behave in specific situations [5].
Other questionnaires will be filled in by drivers every 2 months. These
questionnaires will detect users' perception about safety, trust, effectiveness,
usefulness and value of the Driving Advisor, in strict accordance with the
FESTA project research hypotheses referred to these functions, and the
corresponding performance indicators, i.e. the quantifiable way to detect how
these hypotheses can be assessed [2].
In the periodical questionnaires the drivers will be asked to fill in a specific post
test questionnaire section. These questionnaires aim to detect the viewpoint of
the user about some aspects of the LDW function like the perceived usability,
the compatibility with the driving task, the perceived system consequences, the
ease of use, the learnability and the perceived efficiency. In these periodical
questionnaires, users could also be asked to evaluate themselves about their
driving performance in the last period [6]. A specific section in the periodical
questionnaires is dedicated to the drivers’ acceptance using Van Der Laan
scale to register the usability of the system [7]. The risk perception of the drivers
is also registered.
A weekly vehicle normal use register will be also provided in order to detect and
manage data about drivers’ car use during the FOT execution. Drivers will be
asked to fill in a form and register some data as how many kilometres they did
in the last week and what was the average speed in that period. A board diary
is finally planned to detect driver particular perception about LDW in a specific
scenario, type of road, driver status and also the description of the event and
the state of the system.
Participants’ responses to questionnaires will be treated using Item Response
Theory (IRT) models, which permit to generate measures from subjective
responses [8].
This assessment has been defined in strict accordance with the FESTA project
research hypotheses referred to these ITSs functions and the corresponding
performance indicators, i.e. the quantifiable way to detect how these
hypotheses can be assessed [2].
Human Centred Design for Intelligent Transport Systems
Fig. 4. Questionnaires planning and timing at a glance
2.3 Testing of research hypotheses
The euroFOT project defined and prioritized research hypotheses for each
function that will be tested. These hypotheses have been derived from FESTA
project [2] and from the consultations between intelligent transport system
experts performed in the framework of euroFOT activities [1]. These
hypotheses are derived also considering system specifications and use cases.
The top research hypotheses defined about LDW function are briefly reported in
the following. Does the LDW decrease and mitigate incidents, near-crashes,
and accidents? Does LDW influences lateral driving performance? Does it
increase the use of turn indicators in lane changing situations? Does LDW
usage increase more and more over time? Does LDW increase night driving?
Does LDW lead to an appropriate driver reaction? Is LDW well accepted by the
driver? Does LDW acceptance/adoption increase with LDW usage?
According to FESTA project, even performance indicators have been defined in
the methodological framework of euroFOT to test the hypotheses (see Figure
In the test of Lancia LDW the repeated rounds of questionnaires will highlight
changes in users’ perceptions over time and, according to the Design of
Experiment defined, allow analysts to test the hypotheses.
Field Operational Tests and Naturalistic Driving Studies
Fig. 5. The FOT chain defined in FESTA project [2]
2.4 Test planning and experimental procedures
All questionnaires are paper-based, but on line questionnaires has been set up
as an option. Users will be allowed to fill in web-based questionnaires
developed through Limesurvey software (
The first draft of the questionnaires has been developed during 2009 and now is
going to be updated and fixed. A help desk contact (i.e. driver liaison centre),
which provides support and all information about the project, has been set up.
In particular, a specific phone number and an email address are available for
drivers that want information about questionnaires and how to fill in them.
On line tool (i.e. Limesurvey) will be also used to translate in digital form the
manually filled paper-based questionnaires. All data collected through
questionnaires will be inserted into a data server and properly analyzed using
the identified statistical algorithms. According to euroFOT consortium, the
preliminary results concerning user acceptance and user-related aspects, the
impact analysis and the Cost-Benefit Analysis (CBA) will be defined at the
beginning of 2010. The guidelines and the Data Analysis Plan will be fixed
during 2010, based on the piloting outcomes (see Table 1 and Figure 6).
Human Centred Design for Intelligent Transport Systems
Table 1 – Piloting overview
Piloting tests start Since October 2009.
Number of vehicles in Piloting tests 10 vehicles with LDW recruited by Fiat.
10 vehicles as piloting Control Group
without LDW recruited by Fiat.
Duration of Piloting test 3 months.
Submission of introduction questionnaire
and some periodical questionnaires to test
core items.
Piloting drivers recruited from New owners of Lancia Delta equipped with
Driving Advisor optional feature (LDW
Fig. 6. - Piloting experimental design and timing of Piloting
After piloting review of questionnaires and test of every operational procedure,
the FOT will start with the recruiting ramping up phase (see Table 2 and Figure
7). Questionnaires will be administered as defined above. As already described,
FOT experimental design includes a within subjects analysis with a baseline
and a LDW treatment period and it also includes a Control Group (i.e. drivers of
Lancia Delta car without LDW system) to ensure a between subjects analysis.
Field Operational Tests and Naturalistic Driving Studies
Table 2 – FOT overview
Type of vehicle Cars.
Location National. All Italy.
Road types All types of roads.
Number of vehicles Up to 300 (including Control Group).
Drivers recruited by Lancia direct contact.
Drivers recruited from New owners of Lancia Delta equipped with
Driving Advisor optional feature (LDW
Incentive Fuel bonus.
Pre selection criteria Contact letter and screening questionnaire.
FOT start From February 2010.
Control Group New owner of Lancia Delta without LDW
Number of Control Group vehicles About 150.
Fig. 7. - FOT experimental design and timing of FOT questionnaires
This FOT will permit an accurate investigation and understanding of the impact
of LDW system in respect to several subjective aspects such as perceived
safety, usefulness, acceptance, driving behaviours and subjective mental
workload. This statistically significant assessment would offer to OEM,
stakeholders and researchers the possibility to consider the results of this
analysis not only limited to a restricted number of subjects but extendable to the
drivers’ universe as a whole.
The complete results will be available at the end of the project, planned in 2011
[1] euroFOT consortium, 'Description of Work v1.5', 2008.
[2] FESTA consortium, 'FESTA Handbook deliverable D6.4', 2008.
[3] Reason, J.T., Manstead, A.S.R., Stradling, S.G., Baxter, J.S. and
Campbell, K. 'Errors and violations on the road: a real distinction?' in
'Ergonomics vol. 33', 1990, pp. 1315-1322.
[4] Arnett, J., 'Sensation seeking: A new conceptualization and a new scale' in
Human Centred Design for Intelligent Transport Systems
'Personality and Individual Differences', 16, 1994, pp. 289-296.
[5] West, R., Elander, J., & French, D., 'Decision making, personality and
driving style as correlates of individual accident risk' in 'TRL Contractor
Report 309', Transport Research Laboratory, Crowthorne, United
Kingdom, 1992.
[6] COMUNICAR consortium, 'COMUNICAR deliverable D6.4', 2002.
[7] Van der Laan, J.D., Heino, A. and De Waard, D., 'A simple procedure for
the assessment of acceptance of advanced transport telematics' in
'Transportation Research Part C Vol. 5', pp.1-10, 1997.
[8] Bond, T. G., Fox, C. M., 'Applying the Rasch Model. Fundamental
Measurement in the Human Sciences. 2nd Edition', Trevor, University of
Toledo, 2007
... For a warning system like LDW, the false alarm rate should be very low, as high rates irritate drivers and lead to system rejection. The exact amount of false alarms acceptable by drivers is still a subject for research [14,15], and some available systems report few false alarms per hour [16] . At 15 frames per second , 1 false alarm per hour means one error in 54,000 frames. ...
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The problem of road or lane perception is a crucial enabler for advanced driver assistance systems. As such, it has been an active field of research for the past two decades with considerable progress made in the past few years. The problem was confronted under various scenarios, with different task definitions, leading to usage of diverse sensing modalities and approaches. In this paper we survey the approaches and the algorithmic techniques devised for the various modalities over the last 5 years. We present a generic break down of the problem into its functional building blocks and elaborate the wide range of proposed methods within this scheme. For each functional block, we describe the possible implementations suggested and analyze their underlying assumptions. While impressive advancements were demonstrated at limited scenarios, inspection into the needs of next generation systems reveals significant gaps. We identify these gaps and suggest research directions that may bridge them.
This study examines braking behaviour of drivers assisted with driving aids in a connected environment compared to when they are driving without it during failed lane-changing attempts that often exerts more pressure on the immediate follower in the target lane in the form of hard decelerations, which increases crash risk. To achieve this aim, the CARRS-Q Advanced Driving Simulator is utilised, where 78 participants faced a failed-lane-changing attempt of a lane-changer from the adjacent lane into two randomised driving conditions: (a) baseline (without driving aids); and (b) connected environment (with driving aids). A descriptive analysis of braking profiles reveals decreased decelerations among drivers in the connected environment, compared to when they are driving in the baseline condition. To model braking behaviour, more specifically the time taken by drivers to reduce their initial speeds to the minimum speeds, a grouped random parameters hazard-based duration model is developed. Factors found to significantly impact the braking behaviour are initial speed, spacing, maximum deceleration, driving condition, driver age, and gender. The developed model reveals that drivers’ braking times may increase or decrease in the connected environment compared to those in the baseline condition. However, a majority of drivers in the connected environment tend to reduce speeds earlier with a lower deceleration rate, exhibiting smoother speed reductions and larger safety margins. A decision tree analysis reveals that middle-aged and male drivers take longer to reduce their speeds in the baseline condition but shorter in the connected environment. This study concludes that followers in the connected environment respond to failed lane-changing attempts more swiftly, thereby increasing safety margins.
Towing capacity affects a vehicle’s towing ability and it is usually costly to buy or even rent a vehicle that can tow certain amount of weight. A widely swaying towing trailer is one of the main causes for accidents that involves towing trailers. This study propose an affordable automated nonlinked towing system (ANTS) that does not require physical connection between the leading vehicle and the trailer vehicle by only using a computer vision system. The ANTS contains two main parts: a leading vehicle which can perform lane detection and a trailer vehicle which can automatically follow the leading vehicle by detecting the license plate of the leading vehicle. The trailer vehicle can adjust its speed according to the distance from the leading vehicle.
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Due to the fast-growing industry of intelligent vehicles the advanced driver assistance system (ADAS) has engrossed a lot of attention of the scholars. One of the biggest hurdles for new autonomous vehicles is to detect curvy lanes, multiple lanes, and lanes with a lot of discontinuity and noise. The purpose of this paper is to analyze the possibilities of image processing techniques for a computer vision application focusing on the problem of lane detection to enable traffic safety and driving comfort. The proposed algorithm is a combination of two sub-algorithms. The first sub-algorithm called Fuzzy Noise Reduction Filter (FNRF); removes the noise and smoothen the sequences of images received by the camera. While the second sub-algorithm aims to detect lane in normal as well as challenging scenarios by applying the concept of Hough Transform (HT) with a capable region of interest. The novelty of the proposed research study is the tracking of the lanes under inclement weather and challenging lightening conditions with improved computational time. The result achieved through our proposed algorithm is satisfactory in video sequences captured on several road types and under very challenging lighting and weather conditions.
Vehicle lane-level localization is a fundamental technology in autonomous driving. To achieve accurate and consistent performance, a common approach is to use LIDAR technology. However, it is expensive and computational demanding, and thus not a practical solution in many situations. This paper proposes a stereovision system, which is low-cost, yet also able to achieve high accuracy and consistency. It integrates a new lane line detection algorithm with other lane marking detectors to effectively identify the correct lane line markings. It also fits multiple road models to improve accuracy. An effective stereo 3D reconstruction method is proposed to estimate vehicle localization. The estimation consistency is further guaranteed by a new particle filter framework, which takes vehicle dynamics into account. Experiment results based on image sequences taken under different visual conditions showed that the proposed system can identify the lane line markings with 98:6% accuracy. The maximum estimation error of the vehicle distance to lane lines is 16cm in daytime 26cm at night, and the maximum estimation error of its moving direction respected to road tangent is 0:06rad in daytime and 0:12rad at night. Due to its high accuracy and consistency, the proposed system can be implemented in autonomous driving vehicles as a practical solution to vehicle lane-level localization.
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A new conception of sensation seeking is presented, along with a new scale [the Arnett Inventory of Sensation Seeking (AISS)]. The new conception emphasizes novelty and intensity as the two components of sensation seeking. Two studies were conducted to validate the new scale. In the first study, the AISS was found to be more strongly related to risk behavior than Zuckerman's Sensation Seeking Scale (SSS) among 116 adolescents aged 16–18 years, although the new scale contains no items related to risk behavior (in contrast to the SSS). In the second study, involving 139 adolescents, similar relations were found between the AISS and risk behavior, and the new scale was also found to be significantly correlated with the Aggression subscale of the California Psychological Inventory (CPI). In addition, adults (N = 38) were found to be lower in sensation seeking than adolescents. In both studies, males were higher in sensation seeking than females.
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In considering the human contribution to accidents, it seems necessary to make a distinction between errors and violations; two forms of aberration which may have different psychological origins and demand different modes of remediation. The present study investigated whether this distinction was justified for self-reported driver behaviour. Five hundred and twenty drivers completed a driver behaviour questionnaire (DBQ) which asked them to judge the frequency with which they committed various types of errors and violations when driving. Three fairly robust factors were identified: violations, dangerous errors, and relatively harmless lapses, respectively. Violations declined with age, errors did not. Men of all ages reported more violations than women. Women, however, were significantly more prone to harmless lapses (or more honest) than men. These findings were consistent with the view that errors and violations are indeed mediated by different psychological mechanisms. Violations require explanation in terms of social and motivational factors, whereas errors (slips, lapses, and mistakes) may be accounted for by reference to the information-processing characteristics of the individual.
Cited over 2500 times, this classic text facilitates a deep understanding of the Rasch model. The authors review the crucial properties of the model and demonstrate its use with a variety of examples from education, psychology, and health. A glossary and numerous illustrations aid the reader's understanding. Readers learn how to apply Rasch analysis so they can perform their own analyses and interpret the results. The authors present an accessible overview that does not require a mathematical background. Highlights of the new edition include: -More learning tools to strengthen readers’ understanding including chapter introductions, boldfaced key terms, chapter summaries, activities, and suggested readings. -Divided chapters (4, 6, 7 & 8) into basic and extended understanding sections so readers can select the level most appropriate for their needs and to provide more in-depth investigations of key topics. -A website at that features free Rasch software, data sets, an Invariance worksheet, detailed instructions for key analyses, and links to related sources. -Greater emphasis on the role of Rasch measurement as a priori in the construction of scales and its use post hoc to reveal the extent to which interval scale measurement is instantiated in existing data sets. -Emphasizes the importance of interval level measurement data and demonstrates how Rasch measurement is used to examine measurement invariance. -Insights from other Rasch scholars via innovative applications (Ch. 9). -Extended discussion of invariance now reviews DIF, DPF, and anchoring (ch. 5). -Revised Rating Scale Model material now based on the analysis of the CEAQ (ch.6). -Clarifies the relationships between Rasch measurement, True Score Theory, and Item Response Theory by reviewing their commonalities and differences (Ch.13). -Provides more detail on how to conduct a Rasch analysis so readers can use the techniques on their own (Appendix B). Intended as a text for graduate courses in measurement, item response theory, (advanced) research methods or quantitative analysis taught in psychology, education, human development, business, and other social and health sciences, professionals in these areas also appreciate the book‘s accessible introduction.
Written in an accessible style, this book facilitates a deep understanding of the Rasch model. Authors Bond and Fox review the crucial properties of the Rasch model and demonstrate its use with a wide range of examples including the measurement of educational achievement, human development, attitudes, and medical rehabilitation. A glossary and numerous illustrations further aid the reader's understanding. The authors demonstrate how to apply Rasch analysis and prepare readers to perform their own analyses and interpret the results. Updated throughout, highlights of the Second Edition include: a new CD that features an introductory version of the latest Winsteps program and the data files for the book's examples, preprogrammed to run using Winsteps;, a new chapter on invariance that highlights the parallels between physical and human science measurement;, a new appendix on analyzing data to help those new to Rasch analysis;, more explanation of the key concepts and item characteristic curves;, a new empirical example with data sets demonstrates the many facets of the Rasch model and other new examples; and an increased focus on issues related to unidimensionality, multidimensionality, and the Rasch factor analysis of residuals. Applying the Rasch Model is intended for researchers and practitioners in psychology, especially developmental psychologists, education, health care, medical rehabilitation, business, government, and those interested in measuring attitude, ability, and/or performance. The book is an excellent text for use in courses on advanced research methods, measurement, or quantitative analysis. Significant knowledge of statistics is not required. © 2007 by Lawrence Erlbaum Associates, Inc. All rights reserved.
There is no standard way of measuring driver acceptance of new technology. A review of the literature shows that there are almost as many methods of assessment of acceptance as there are acceptance studies. The tool for studying acceptance of new technological equipment that is presented here has a major advantage compared with many other studies in that esoteric knowledge of scaling techniques is not required. The technique is simple and consists of nine 5-point rating-scale items. These items load on two scales, a scale denoting the usefulness of the system, and a scale designating satisfaction. The technique has been applied in six different studies in different test environments and analyses performed over these studies show that it is a reliable instrument for the assessment of acceptance of new technology. The technique was sensitive to differences in opinion to specific aspects of in-vehicle systems, as well as to differences in opinion between driver groups. In a concluding section explicit recommendations for use of the scale are given.
Decision making, personality and driving style as correlates of individual accident risk' in 'TRL Contractor Report 309
  • R West
  • J Elander
  • D French
West, R., Elander, J., & French, D., 'Decision making, personality and driving style as correlates of individual accident risk' in 'TRL Contractor Report 309', Transport Research Laboratory, Crowthorne, United Kingdom, 1992.