Older Drivers’ Perception and Acceptance of In-Vehicle Devices for Traffic Safety and Traffic Efficiency

A multitude of new technologies (ranging from guidance systems to speed-limit exceeding systems and to fatigue detection systems) are emerging, many of which are either explicitly targeted to older drivers or expected to benefit them the most. However, these same older drivers are more likely to find adapting to the use of such technologies challenging. Therefore, understanding older drivers' perception of such devices will allow experts to take the necessary steps to ensure their smoother acceptance and complete success of their deployment. Using Greek drivers' attitude data collected within the scope of an extensive recent survey in 23 European countries (the SARTRE-3 data set), a statistical analysis of the perception of usefulness and acceptance of new technologies by older drivers is presented. The results of the developed ordered logit models provide insight into the human-factors' aspect of the introduction of advanced technologies with respect to these more sensitive segments of the driver population. For example, older respondents are, in general, more supportive of the considered in-vehicle technologies, while female respondents also show a higher willingness to adopt them.

[1]  R. Likert “Technique for the Measurement of Attitudes, A” , 2022, The SAGE Encyclopedia of Research Design.

[2]  S. Zeger,et al.  Longitudinal data analysis using generalized linear models , 1986 .

[3]  Matthew G Karlaftis,et al.  An empirical investigation of European drivers' self-assessment. , 2003, Journal of safety research.

[4]  Geert Wets,et al.  Analysis of road risk per age and gender category : a time series approach , 2006 .

[5]  Sophia Vardaki,et al.  Investigation of Actual and Perceived Behavior of Older Drivers on Freeways , 2008 .

[6]  David A Noyce,et al.  USING OF DRIVING SIMULATORS TO EVALUATE NOVEL TRAFFIC CONTROL DEVICES: PROTECTED/PERMISSIVE LEFT-TURN SIGNAL DISPLAY ANALYSIS , 2003 .

[7]  Shauna L. Hallmark,et al.  Factors Related to More Severe Older Driver Traffic Crash Injuries , 2002 .

[8]  Anuj K. Pradhan,et al.  The Use of Eye Movements to Evaluate the Effects of Driver Age on Risk Perception in an Advanced Driving Simulator , 2003 .

[9]  M. Ben-Akiva,et al.  Discrete choice analysis , 1989 .

[10]  Hamish A Deery,et al.  Hazard and Risk Perception among Young Novice Drivers , 1999 .

[11]  Ronald R. Mourant,et al.  In-Vehicle Alerting System for Older and Younger Drivers: Does Experience Count? , 2004 .

[12]  D C Webster,et al.  THE CHARACTERISTICS OF SPEEDERS , 2000 .

[13]  Ragnhild J. Davidse,et al.  OLDER DRIVERS AND ADAS: Which Systems Improve Road Safety? , 2006 .

[14]  Neil D. Lerner,et al.  Driver Strategies for Engaging in Distracting Tasks Using In-Vehicle Technologies , 2008 .

[15]  Deborah A. Boehm-Davis,et al.  Effects of Age and Congestion Information Accuracy of Advanced Traveler Information Systems on User Trust and Compliance , 1998 .

[16]  C. Antoniou,et al.  Classification of driver-assistance systems according to their impact on road safety and traffic efficiency , 2002 .

[17]  Michelle M. Porter,et al.  Are Rear-Checking Behaviors Determined by Range of Motion in Older Drivers? , 2006 .

[18]  P. McCullagh,et al.  Multivariate Logistic Models , 1995 .

[19]  Michael D. Pawlovich,et al.  Impact of Left-Turn Phasing on Older and Younger Drivers at High-Speed Signalized Intersections , 2007 .

[20]  J P Cauzard,et al.  European drivers and road risk: SARTRE 3 reports: part 1: report on principal analyses , 2004 .

[21]  A. J. Richardson Simulation Study of Estimation of Individual Specific Values of Time by Using Adaptive Stated-Preference Survey , 2001 .

[22]  Bryan J Katz,et al.  Determining colors for traffic control devices at transponder-controlled tollbooth lanes with a sign simulator , 2006 .

[23]  S Pohlmann,et al.  Orientation in road traffic. Age-related differences using an in-vehicle navigation system and a conventional map. , 1994, Accident; analysis and prevention.

[24]  William N. Venables,et al.  Modern Applied Statistics with S , 2010 .

[25]  R D Wittink,et al.  SARTRE: SOCIAL ATTITUDES TO ROAD TRAFFIC RISK IN EUROPE. TOWARDS A NEW POLICY-RELEVANT UNDERSTANDING OF EUROPE'S DRIVERS , 1994 .

[26]  Geert Wets,et al.  Analysis of Road Risk by Age and Gender Category , 2007 .

[27]  Nina M. Silverstein,et al.  Use of video intervention to increase elders' awareness of low-cost vehicle modifications that enhance driving safety and comfort , 2005 .

[28]  Kenneth W. Gish,et al.  DRIVER BEHAVIOR AND PERFORMANCE USING AN INFRARED NIGHT VISION ENHANCEMENT SYSTEM , 2002 .

[29]  A. Williams,et al.  Driver age and crash involvement. , 1989, American journal of public health.

[30]  Rosa Alice DeRamus The Effect of Driver Age on Scanning Behaviors in Risky Situations , 2006 .

[31]  Linda Ng Boyle,et al.  Drivers' attitudes toward imperfect distraction mitigation strategies , 2006 .

[32]  Tami Toroyan,et al.  Global Status Report on Road Safety: Time for Action , 2009 .

[33]  Neil D. Lerner,et al.  Use of Advanced In-Vehicle Technology by Younger and Older Early Adopters. Selected Results From Five Technology Surveys , 2008 .

[34]  Sjaanie Narelle Koppel,et al.  The Case For and Against Mandatory Age-Based Assessment of Older Drivers , 2006 .