Sandstorm animations on rural expressways: The impact of variable message sign strategies on driver behavior in low visibility conditions

Abstract Problem: Evolving sandstorms on rural expressways in desert countries impair drivers' contrast vision and increase the risk of serious crashes due to delayed speed adjustments. Intelligent Transport Systems (ITS) such as Variable Message Signs (VMS) conveying warnings can be activated to address drivers’ speed adaptation before entering a low visibility zone. To improve drivers’ understanding of the hazard, a sandstorm animation visualizing turbulent sand and its consequences was designed and compared with a general warning pictogram, which is applied if no specific weather pictogram is available. Moreover, minimum warning distances of the VMS to the low visibility zone were tested (e.g., 300 m or 500 m). Method Sixty-three participants from the State of Qatar drove in a driving simulator through clear, transition, and low visibility conditions on a rural expressway. A repeated analysis of variances was conducted to examine the impact of the two on-road warning displays on driving behavior. Results The results showed that the sandstorm animation was similarly effective as a generic warning pictogram in reducing driving speeds before entering the transition and low visibility zone, irrespective of being displayed 500 m or 300 m away. However, the sandstorm animation resulted in consistent similar speed reductions within the low visibility zone, whereas the generic warning pictogram did either perform better or worse after several encounters with a sandstorm. Drivers did strongly agree that the animation is clearly referring to the issue of low visibility, which can be beneficial for recurring low visibility conditions. Practical applications: 1.) Displaying a sandstorm animation is beneficial for rural expressway sections with recurring degrading visibility and low traffic densities, whereas a warning pictogram can be more effective in speed reductions if drivers expect additional traffic hazards. 2.) Roadway authorities have the flexibility to activate a VMS sandstorm warning even for minimum warning distances.

[1]  F N Tate,et al.  Evaluating the effects of bilingual traffic signs on driver performance and safety , 2005, Ergonomics.

[2]  Wael K. M. Alhajyaseen,et al.  Analysis of road traffic crashes in the State of Qatar , 2019, International journal of injury control and safety promotion.

[3]  Darja Topolšek,et al.  Examination of driver detection of roadside traffic signs and advertisements using eye tracking , 2016 .

[4]  M. Al-Sudairawi,et al.  Economic Impact and Risk Assessment of Sand and Dust Storms (SDS) on the Oil and Gas Industry in Kuwait , 2019, Sustainability.

[5]  Tom Brijs,et al.  Speed perception and actual speed in a driving simulator and real-world: A validation study , 2019, Transportation Research Part F: Traffic Psychology and Behaviour.

[6]  Xiaohua Zhao,et al.  Effects of connected vehicle-based variable speed limit under different foggy conditions based on simulated driving. , 2019, Accident; analysis and prevention.

[7]  M. Alharthi,et al.  The Impacts of Climate Change on Road Traffic Accidents in Saudi Arabia , 2019, Climate.

[8]  Mohamed Ahmed,et al.  Exploring the Impacts of Adverse Weather Conditions on Speed and Headway Behaviors Using the SHRP2 Naturalistic Driving Study Data , 2017 .

[9]  Fumitaka Kurauchi,et al.  Study on Drivers’ Comprehension of Advanced Graphical Route Information Panel Considering Individual Attributes , 2013, Int. J. Intell. Transp. Syst. Res..

[10]  Tim Horberry,et al.  The human factors of transport signs , 2004 .

[11]  Wolfgang Fastenmeier,et al.  Visual advisory warnings about hidden dangers: Effects of specific symbols and spatial referencing on necessary and unnecessary warnings. , 2018, Applied ergonomics.

[12]  Charles Tijus,et al.  Understanding road signs , 2009 .

[13]  Text and Image in Translation , 2016 .

[14]  Snehanshu Banerjee,et al.  Drivers’ Behavior Analysis under Reduced Visibility Conditions Using a Driving Simulator , 2016 .

[15]  Julian X. L. Wang,et al.  Mapping the Global Dust Storm Records: Review of Dust Data Sources in Supporting Modeling/Climate Study , 2015, Current Pollution Reports.

[16]  Marieke Hendrikje Martens,et al.  Do Familiarity and Expectations Change Perception? Drivers' Glances and Response to Changes , 2007 .

[17]  R. Gibbons,et al.  Visibility of a Color Variable Message Sign in the Fog , 2015 .

[18]  Wael K.M. Alhajyaseen,et al.  Analyzing the impact of human characteristics on the comprehensibility of road traffic signs , 2018 .

[19]  Robert E. Dewar,et al.  Rapid Comprehension of Verbal and Symbolic Traffic Sign Messages , 1979 .

[20]  Don Scott,et al.  Car following decisions under three visibility conditions and two speeds tested with a driving simulator. , 2007, Accident; analysis and prevention.

[21]  Alan H S Chan,et al.  The guessability of traffic signs: effects of prospective-user factors and sign design features. , 2007, Accident; analysis and prevention.

[22]  Samuel G Charlton,et al.  Conspicuity, memorability, comprehension, and priming in road hazard warning signs. , 2006, Accident; analysis and prevention.

[23]  H. Cao,et al.  Characterizing Sand and Dust Storms (SDS) Intensity in China Based on Meteorological Data , 2018, Sustainability.

[24]  M Saffarian,et al.  Why do drivers maintain short headways in fog? A driving-simulator study evaluating feeling of risk and lateral control during automated and manual car following , 2012, Ergonomics.

[25]  Andy Field,et al.  Discovering statistics using IBM SPSS statistics: and sex and drugs and rock 'n' roll, 4th Edition , 2013 .

[26]  Francisco Rebelo,et al.  Behavioral compliance for dynamic versus static signs in an immersive virtual environment. , 2014, Applied ergonomics.

[27]  Carryl L. Baldwin,et al.  Perceived urgency mapping across modalities within a driving context. , 2014, Applied Ergonomics.

[28]  Tom Brijs,et al.  Variable message sign strategies for congestion warning on motorways - A driving simulator study , 2018 .

[29]  Zsolt Sándor,et al.  Effects of Weather Related Safety Messages on the Motorway Traffic Parameters , 2017 .

[30]  David Shinar,et al.  Ergonomic Guidelines for Traffic Sign Design Increase Sign Comprehension , 2006, Hum. Factors.

[31]  Ashley Martin,et al.  Speed choice and driving performance in simulated foggy conditions. , 2011, Accident; analysis and prevention.

[32]  Richard Tay,et al.  Effectiveness of Road Safety Messages on Variable Message Signs , 2010 .

[33]  Christopher Schreiner,et al.  Reducing fog-related crashes on the Afton and Fancy Gap Mountain sections of I-64 and I-77 in Virginia , 2002 .

[34]  Laila Maria Horan.  Exploring the influence of message framing and image valence on the effectiveness of anti-speeding posters , 2015 .

[35]  Wolfgang Fastenmeier,et al.  Accident Analysis and Prevention , 2017 .

[36]  Yang Liu,et al.  Effects of foggy conditions on drivers’ speed control behaviors at different risk levels , 2014 .

[37]  A. D. Talab,et al.  Safety Signs Perception and Adoption with the ISO and ANSI Standards , 2017 .

[38]  Juneyoung Park,et al.  Effects of real-time warning systems on driving under fog conditions using an empirically supported speed choice modeling framework , 2018 .

[39]  Fabrice Vienne,et al.  Driver behaviour in fog is not only a question of degraded visibility – A simulator study , 2017 .

[40]  Nada D Trout,et al.  USE OF GRAPHICS AND SYMBOLS ON DYNAMIC MESSAGE SIGNS: TECHNICAL REPORT , 2009 .

[41]  Tom Brijs,et al.  Dynamic travel information strategies in advance traveler information systems and their effect on route choices along highways , 2020, ANT/EDI40.

[42]  Ismutulla Eli,et al.  Analysis on Physiologic and Psychological Characteristics of Drivers on the Desert Highway Based on Driving Aptitude Test , 2009 .

[43]  J. Shumake-Guillemot,et al.  Global assessment of sand and dust storms , 2016 .

[44]  Rune Elvik,et al.  The Handbook of Road Safety Measures , 2009 .

[45]  Wael K. M. Alhajyaseen,et al.  Introducing a multi-variate classification method: Risky driving acceptance among different heterogeneous driver sub-cultures. , 2020, Journal of safety research.

[46]  D Basacik,et al.  Investigating driver distraction: the effects of video and static advertising: a driving simulator study , 2009 .

[47]  B. R. Cooper,et al.  Assessment of M25 Automatic Fog-Warning System - Final Report , 1993 .

[48]  Wendy Weijermars,et al.  The relationship between road safety and congestion on motorways : a literature review of potential effects. , 2010 .

[49]  Jian Rong,et al.  Evaluation of cooperative systems on driver behavior in heavy fog condition based on a driving simulator. , 2019, Accident; analysis and prevention.

[50]  Juneyoung Park,et al.  Effects of crash warning systems on rear-end crash avoidance behavior under fog conditions , 2018, Transportation Research Part C: Emerging Technologies.

[51]  C. Maccarley,et al.  Highway Traffic Response to Dynamic Fog Warning and Speed Advisory Messages , 2006 .

[52]  Rune Elvik,et al.  A re-parameterisation of the Power Model of the relationship between the speed of traffic and the number of accidents and accident victims. , 2013, Accident; analysis and prevention.

[53]  Mohamed M Ahmed,et al.  Analyzing the effect of fog weather conditions on driver lane-keeping performance using the SHRP2 naturalistic driving study data. , 2019, Journal of safety research.