Safety Impacts of Intervehicle Warning Information Systems for Moving Hazards in Connected Vehicle Environments

Driver inattentiveness is one of the critical factors that contribute to vehicle crashes. The intervehicle safety warning information system (ISWS) is a technology to enhance driver attentiveness by providing warning messages about upcoming hazards under the connected vehicle environments. A novel feature of the proposed ISWS is its capability to detect hazardous driving events, which are defined as moving hazards with a high potential to cause crashes. The study presented in this paper evaluated the potential effectiveness of the ISWS to reduce crashes and to mitigate traffic congestion. The study included a field experiment that documented actual vehicle maneuvering patterns of accelerations and lane changes, which were used to enhance the realism of simulation evaluations. Probe vehicles equipped with customized onboard units, which consisted of a GPS device, accelerometer, and gyro sensor, were used. A microscopic simulator, VISSIM, was used to simulate a driver's responsive behavior after warning messages were delivered. A surrogate safety assessment model was used to derive surrogate safety measures to evaluate the effectiveness of ISWS in terms of traffic safety. The results showed a reduced number of rear-end conflicts when the ISWS's market penetration rate (MPR) and the congestion level of the traffic conditions increased. The reduced number of rear-end conflicts was approximately 84.3%, with a 100% MPR under Level of Service D traffic conditions. Analysis of the standard deviation of speed showed that a reduction of 39.9% was achieved. The outcomes of this study could be valuable to derive smarter operational strategies for ISWS.

[1]  Christopher Nowakowski,et al.  Comparison of Infrastructure and In-Vehicle Driver Interfaces for Left-Turn Warnings , 2008 .

[2]  Tarek Sayed,et al.  Surrogate Safety Assessment Model and Validation: Final Report , 2008 .

[3]  Lutz Eckstein,et al.  Impact Assessment of Adaptive Cruise Control (ACC) and Forward Collision Warning (FCW) Within a Field Operational Test in Europe , 2013 .

[4]  Jae-Joon Lee,et al.  Simulation Model for Studying Impact of Vehicle-to-Vehicle Wireless Communications on Traffic Network Operations , 2010 .

[5]  Soyoung Ahn,et al.  Impact of traffic oscillations on freeway crash occurrences. , 2010, Accident; analysis and prevention.

[6]  Hyungjun Park,et al.  Development and Evaluation of Enhanced IntelliDrive-Enabled Lane Changing Advisory Algorithm to Address Freeway Merge Conflict , 2011 .

[7]  Sheue-Ling Hwang,et al.  Safety Assessment of Different In-Vehicle Interface Designs for Bus Collision Warning Systems , 2008 .

[8]  A Baruya,et al.  THE EFFECTS OF DRIVERS' SPEED ON THE FREQUENCY OF ROAD ACCIDENTS , 2000 .

[9]  Dirk Helbing,et al.  Autonomous Detection and Anticipation of Jam Fronts from Messages Propagated by Intervehicle Communication , 2007 .

[10]  Xu Yang,et al.  Simulation studies of information propagation in a self-organizing distributed traffic information system , 2005 .

[11]  Hyungjun Park,et al.  Integrated Traffic–Communication Simulation Evaluation Environment for IntelliDrive Applications Using SAE J2735 Message Sets , 2011 .

[12]  Taehyung Kim,et al.  Capability-Enhanced Probe Vehicle Surveillance System with Vehicle-to-Vehicle Communications , 2010 .

[13]  Youn-Soo Kang,et al.  Intervehicle Safety Warning Information System for Unsafe Driving Events , 2012 .

[14]  Hariharan Krishnan,et al.  Microscopic Traffic Simulation of Vehicle-to-Vehicle Hazard Alerts on Freeway , 2010 .

[15]  Lars Wischhof,et al.  Information dissemination in self-organizing intervehicle networks , 2005, IEEE Transactions on Intelligent Transportation Systems.

[16]  O Cheol,et al.  Agent-based Speed Management Strategy for Freeway Traffic Safety (Methodology and Evaluation) , 2011 .

[17]  Taoufik Bakri,et al.  EuroFOT Safety impact assessment method and results , 2012 .

[18]  Mustafa Ergen,et al.  Dependence of Cooperative Vehicle System Performance on Market Penetration , 2007 .