Investigating the impact of a novel active gap metering signalization strategy on driver behavior at highway merging sections

Abstract A safe headway to the lead vehicle is important to reduce conflicts with merging vehicles from highway on-ramps. Previous research has outlined the advantage of gap metering strategies to yield sufficient space to merging vehicles and improve highway capacity during peak hours. However, prevailing gap metering systems fail to indicate the minimum required gap and leave it to the drivers’ judgment to adjust their headway. This paper proposes a new Active Gap Metering (AGM) signalization that helps outer lane drivers to adjust their headway to the lead vehicle when approaching highway ramps with incoming vehicles. This AGM signalization represents a combination of pavement markings and an innovative Variable Message Sign (VMS). The AGM system was tested alone and in combination with additional variable speed limits (VSL) in distinct environments of the Doha Expressway in the State of Qatar using a driving simulator. The driving behavior of 64 drivers was analyzed using repeated-measures ANOVA. The results showed that the AGM effectively influenced the drivers’ behavior on the right stream lane. Drivers did gradually increase the distance to the lead vehicle, which resulted in optimal headways to merging on-ramp vehicles. Most importantly, the minimum time-to-collision (TTCmin) to the merging vehicle was increased by an additional 1–1.5 s as compared to no treatment. The proposed AGM signalization can, therefore, be considered by policymakers to influence drivers’ headways at critical merging sections.

[1]  Francesc Soriguera,et al.  Assessment of Dynamic Speed Limit Management on Metropolitan Freeways , 2013, J. Intell. Transp. Syst..

[2]  T. Brijs,et al.  The effect of pavement markings on driving behaviour in curves: a simulator study , 2017, Ergonomics.

[3]  Tom Brijs,et al.  The Use of Gantries and Cantilevers at a Redesigned Intersection: a Simulator Study on Route Choice and Visual Search Behavior , 2017 .

[4]  Alexandra Kondyli,et al.  Driver Behavior at Freeway-Ramp Merging Areas , 2009 .

[5]  Wael K.M. Alhajyaseen,et al.  Traffic safety culture of professional drivers in the State of Qatar , 2019, IATSS Research.

[6]  George F. List,et al.  New Algorithms for Computing the Time-to-Collision in Freeway Traffic Simulation Models , 2014, Comput. Intell. Neurosci..

[7]  Winnie Daamen,et al.  Key Variables of Merging Behaviour: Empirical Comparison between Two Sites and Assessment of Gap Acceptance Theory , 2013 .

[8]  Christer Hydén,et al.  Estimating the severity of safety related behaviour. , 2006, Accident; analysis and prevention.

[9]  Thomas J Triggs,et al.  On-Road Evaluation of Intelligent Speed Adaptation, Following Distance Warning and Seatbelt Reminder Systems: Final Results of the TAC SafeCar Project , 2006 .

[10]  Yan Kuang,et al.  A tree-structured crash surrogate measure for freeways. , 2015, Accident; analysis and prevention.

[11]  Xuedong Yan,et al.  In-depth analysis of drivers' merging behavior and rear-end crash risks in work zone merging areas. , 2015, Accident; analysis and prevention.

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

[13]  Hong Yang,et al.  Estimation of Traffic Conflict Risk for Merging Vehicles on Highway Merge Section , 2011 .

[14]  D. Shinar Traffic Safety and Human Behavior , 2007 .

[15]  David Reeves,et al.  Relationship between Traffic Density, Speed, and Safety and Its Implications for Setting Variable Speed Limits on Freeways , 2012 .

[16]  Marieke Hendrikje Martens,et al.  Linking Behavioral Indicators to Safety: What Is Safe and What Is Not? , 2011 .

[17]  Charisma F. Choudhury,et al.  Transferability of Car-Following Models Between Driving Simulator and Field Traffic , 2017 .

[18]  Dimitri Daucher,et al.  Traffic Operations at an Entrance Ramp of a Suburban Freeway First Results , 2011 .

[19]  Jie Fang,et al.  Gap metering for active traffic control at freeway merging sections , 2017, J. Intell. Transp. Syst..

[20]  Xiao-Yun Lu,et al.  Combining Variable Speed Limits with Ramp Metering for freeway traffic control , 2010, Proceedings of the 2010 American Control Conference.

[21]  Katja Vogel,et al.  A comparison of headway and time to collision as safety indicators. , 2003, Accident; analysis and prevention.

[22]  Juha Luoma,et al.  Effects of variable message signs for slippery road conditions on reported driver behaviour , 2000 .

[23]  Markos Papageorgiou,et al.  Optimal Motorway Traffic Flow Control Involving Variable Speed Limits and Ramp Metering , 2010, Transp. Sci..

[24]  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.

[25]  C. Hydén,et al.  Evaluation of traffic safety, based on micro-level behavioural data: theoretical framework and first implementation. , 2010, Accident; analysis and prevention.

[26]  Serge P. Hoogendoorn,et al.  Empirical Analysis of Merging Behavior at Freeway On-Ramp , 2010 .

[27]  Alexandra Kondyli,et al.  Driver behavior at freeway-ramp merging areas based on instrumented vehicle observations , 2012 .

[28]  Todd Litman,et al.  Autonomous Vehicle Implementation Predictions: Implications for Transport Planning , 2015 .

[29]  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.

[30]  Tom Brijs,et al.  Drivers’ estimation of their travelling speed: a study on an expressway and a local road , 2019, International journal of injury control and safety promotion.

[31]  Anne T McCartt,et al.  Types and characteristics of ramp-related motor vehicle crashes on urban interstate roadways in Northern Virginia. , 2004, Journal of safety research.

[32]  Risto Kulmala,et al.  Effects of variable message signs for slippery road conditions on driving speed and headways , 2000 .

[33]  Amnon Shashua,et al.  Vision-based ACC with a single camera: bounds on range and range rate accuracy , 2003, IEEE IV2003 Intelligent Vehicles Symposium. Proceedings (Cat. No.03TH8683).

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

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

[36]  Thomas E Mulinazzi,et al.  Urban Freeway On-Ramps , 2007 .

[37]  Wolfgang J. Berger,et al.  Comprehension of new instructions for car drivers in merging areas , 2012 .

[38]  Geoff Hyman,et al.  Modelling motorway merge: The current practice in the UK and towards establishing general principles , 2012 .

[39]  Patricia Delhomme,et al.  Factors influencing drivers' reading and comprehension of on-board traffic messages , 2015 .

[40]  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.

[41]  Wael K. M. Alhajyaseen,et al.  Changes in Driving Behavior Across Age Cohorts in an Arab Culture: the Case of State of Qatar , 2018, ANT/SEIT.

[42]  Alois Ferscha,et al.  Traffic flow harmonization in expressway merging , 2012, Personal and Ubiquitous Computing.

[43]  Karel A Brookhuis,et al.  That's close enough--a threshold effect of time headway on the experience of risk, task difficulty, effort, and comfort. , 2010, Accident; analysis and prevention.

[44]  Andy Field,et al.  Discovering statistics using SPSS: and sex and drugs and rock 'n' roll, 3rd Edition , 2009 .

[45]  David Shinar,et al.  Comprehension of traffic signs with symbolic versus text displays , 2013 .

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

[47]  David Shinar,et al.  Minimum and Comfortable Driving Headways: Reality versus Perception , 2001, Hum. Factors.

[48]  Meirav Taieb-Maimon,et al.  Learning Headway Estimation in Driving , 2007, Hum. Factors.

[49]  F. Leeming,et al.  Headway on urban streets: observational data and an intervention to decrease tailgating , 2000 .

[50]  Marieke Hendrikje Martens,et al.  Time and space: The difference between following time headway and distance headway instructions , 2013 .

[51]  Victor L. Knoop,et al.  Lane distribution of traffic near merging zones influence of variable speed limits , 2010, 13th International IEEE Conference on Intelligent Transportation Systems.

[52]  Natasha Merat,et al.  Behavioural changes in drivers experiencing highly-automated vehicle control in varying traffic conditions , 2013 .

[53]  Niklas Strand,et al.  Driver performance in the presence of adaptive cruise control related failures: Implications for safety analysis and fault tolerance , 2013, 2013 43rd Annual IEEE/IFIP Conference on Dependable Systems and Networks Workshop (DSN-W).

[54]  Sonia Amado,et al.  Effects of stimulus type, duration and location on priming of road signs: Implications for driving , 2008 .

[55]  Long T. Truong,et al.  Studying the Safety Impact of Autonomous Vehicles Using Simulation-Based Surrogate Safety Measures , 2018 .

[56]  Atze Dijkstra,et al.  Do Calculated Conflicts in Microsimulation Model Predict Number of Crashes? , 2010 .