Evaluation of the impacts of cooperative adaptive cruise control on reducing rear-end collision risks on freeways.

Although plenty of studies have been conducted recently about the impacts of cooperative adaptive cruise control (CACC) system on traffic efficiency, there are few researches analyzing the safety effects of this advanced driving-assistant system. Thus, the primary objective of this study is to evaluate the impacts of the CACC system on reducing rear-end collision risks on freeways. The CACC model is firstly developed, which is based on the Intelligent Driver Model (IDM). Then, two surrogated safety measures, derived from the time-to-collision (TTC), denoting time exposed time-to-collision (TET) and time integrated time-to-collision (TIT), are introduced for quantifying the collision risks. And the safety effects are analyzed both theoretically and experimentally, by the linear stability analysis and simulations. The theoretical and simulation results conformably indicate that the CACC system brings dramatic benefits for reducing rear-end collision risks (TET and TIT are reduced more than 90%, respectively), when the desired time headway and time delay are set properly. The sensitivity analysis indicates there are few differences among different values of the threshold of TTC and the length of a CACC platoon. The results also show that the safety improvements weaken with the decrease of the penetration rates of CACC on the market and the increase of time delay between platoons. We also evaluate the traffic efficiency of the CACC system with different desired time headway.

[1]  Xiqun Chen,et al.  Stabilization of traffic flow based on multi-anticipative intelligent driver model , 2009, 2009 12th International IEEE Conference on Intelligent Transportation Systems.

[2]  Ronghui Liu,et al.  Car-Following Model for Motorway Traffic , 2005 .

[3]  Xiao-Yun Lu,et al.  COOPERATIVE ADAPTIVE CRUISE CONTROL (CACC) DEFINITIONS AND OPERATING CONCEPTS , 2015 .

[4]  Mike McDonald,et al.  PARAMETER ANALYSIS FOR COLLISION AVOIDANCE SYSTEMS , 2002 .

[5]  Steven E Shladover,et al.  Impacts of Cooperative Adaptive Cruise Control on Freeway Traffic Flow , 2012 .

[6]  Wei Wang,et al.  Predicting crash likelihood and severity on freeways with real-time loop detector data. , 2013, Accident; analysis and prevention.

[7]  Dirk Helbing,et al.  Adaptive cruise control design for active congestion avoidance , 2008 .

[8]  Mike McDonald,et al.  Car-following: a historical review , 1999 .

[9]  Steven E Shladover,et al.  Modeling cooperative and autonomous adaptive cruise control dynamic responses using experimental data , 2014 .

[10]  Shinya Kikuchi,et al.  Impacts of shorter perception-reaction time of adapted cruise controlled vehicles on traffic flow and safety , 2003 .

[11]  Gábor Orosz,et al.  Dynamics of connected vehicle systems with delayed acceleration feedback , 2014 .

[12]  Jun Chen,et al.  Using Trajectory Data to Analyze Intradriver Heterogeneity in Car-Following , 2010 .

[13]  D. Ragland,et al.  Surrogate safety measure for evaluating rear-end collision risk related to kinematic waves near freeway recurrent bottlenecks. , 2014, Accident; analysis and prevention.

[14]  Petros A. Ioannou,et al.  Mixed Manual/Semi-Automated Traffic: A Macroscopic Analysis , 2001 .

[15]  L Nilsson,et al.  COLLISON AVOIDANCE SYSTEMS - EFFECTS OF DIFFERENT LEVELS OF TASK ALLOCATION ON DRIVER BEHAVIOUR , 1991 .

[16]  Wei Wang,et al.  Development of a variable speed limit strategy to reduce secondary collision risks during inclement weathers. , 2014, Accident; analysis and prevention.

[17]  Robert Graham,et al.  The Format and Presentation of Collision Warnings , 1997 .

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

[19]  Serge Hoogendoorn,et al.  Calibration of microscopic traffic-flow models using multiple data sources , 2010, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[20]  M M Minderhoud,et al.  Extended time-to-collision measures for road traffic safety assessment. , 2001, Accident; analysis and prevention.

[21]  Haris N. Koutsopoulos,et al.  Do cooperative systems make drivers' car-following behavior safer? , 2014 .

[22]  Zhongke Shi,et al.  The effects of vehicular gap changes with memory on traffic flow in cooperative adaptive cruise control strategy , 2015 .

[23]  Wenzhong Li,et al.  Stability analysis of an extended intelligent driver model and its simulations under open boundary condition , 2015 .

[24]  Vicente Milanés Montero,et al.  Cooperative Adaptive Cruise Control in Real Traffic Situations , 2014, IEEE Transactions on Intelligent Transportation Systems.

[25]  Urbano Nunes,et al.  Multiplatooning Leaders Positioning and Cooperative Behavior Algorithms of Communicant Automated Vehicles for High Traffic Capacity , 2015, IEEE Transactions on Intelligent Transportation Systems.

[26]  Rui Jiang,et al.  First- and second-order phase transitions from free flow to synchronized flow , 2003 .

[27]  Wei Wang,et al.  Reducing the risk of rear-end collisions with infrastructure-to-vehicle (I2V) integration of variable speed limit control and adaptive cruise control system , 2016, Traffic injury prevention.

[28]  Bart van Arem,et al.  Effects of Cooperative Adaptive Cruise Control on traffic flow stability , 2010, 13th International IEEE Conference on Intelligent Transportation Systems.

[29]  Romain Billot,et al.  Linear and Weakly Nonlinear Stability Analyses of Cooperative Car-Following Models , 2014, IEEE Transactions on Intelligent Transportation Systems.

[30]  John C Hayward,et al.  NEAR-MISS DETERMINATION THROUGH USE OF A SCALE OF DANGER , 1972 .

[31]  Mohamed Abdel-Aty,et al.  Split Models for Predicting Multivehicle Crashes during High-Speed and Low-Speed Operating Conditions on Freeways , 2005 .

[32]  Takashi Oguchi,et al.  A Study on Car Following Models Simulating Various Adaptive Cruise Control Behaviors , 2014, Int. J. Intell. Transp. Syst. Res..

[33]  Dirk Helbing,et al.  Jam-Avoiding Adaptive Cruise Control (ACC) and its Impact on Traffic Dynamics , 2005 .

[34]  Helbing,et al.  Congested traffic states in empirical observations and microscopic simulations , 2000, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[35]  Adolf D. May,et al.  Traffic Flow Fundamentals , 1989 .