Application of vehicle to another entity (V2X) communications for motorcycle crash avoidance

ABSTRACT Information and communication technologies are being massively applied in the automotive field as the basis of the new generation of active safety systems. In this extensive field of technologies, vehicular communications will constitute the core of a large set of advanced driving assistance systems for improving road safety as well as helping to reduce the environmental impact of transport. These communication technologies are currently under deployment, but their mandatory installation in newly manufactured cars is foreseen in the next 5 years. This equipment will enable the new Advanced Driver Assistance Systems (ADAS) system to be installed in these vehicles. Many of these safety applications are currently under development. However, there are some road users who are not commonly included in this vehicular communication ecosystem, specifically, vulnerable road users, such as pedestrians, cyclists, and motorcyclists. Current assistance systems focused on reducing crashes with this user group are based on sensors installed in the vehicles but do not include vehicular communications. In this article, we present a novel Vulnerable Road User (VRU) warning system based on Vehicle-to-Vehicle (V2V) communications, which is capable of detecting a motorcycle circulating in the vicinity of the connected vehicles, launching sound and visual warnings, and using a smartphone as human-machine interface. The system has been designed, implemented, and tested in the laboratory as well as on real roads in real traffic flow.

[1]  Fawzi Nashashibi,et al.  Vehicle to pedestrian communications for protection of vulnerable road users , 2014, 2014 IEEE Intelligent Vehicles Symposium Proceedings.

[2]  Gérard Lachapelle,et al.  Evaluation of GPS-based methods of relative positioning for automotive safety applications , 2012 .

[3]  R. Lot,et al.  An intelligent Frontal Collision Warning system for Motorcycles , .

[4]  A Guarise,et al.  Vulnerable road uses thoroughly addressed in accident prevention: the WATCH-OVER European project , 2007 .

[5]  Peggy Subirats,et al.  A new method for the detection of motorbikes by laser ragefinder , 2011, 2011 International Conference on Communications and Signal Processing.

[6]  Shraga Shoval,et al.  Micro-Simulation Model for Assessing the Risk of Vehicle–Pedestrian Road Accidents , 2015, J. Intell. Transp. Syst..

[7]  William W. Hunter,et al.  White Papers for: “Toward Zero Deaths: A National Strategy on Highway Safety”—White Paper No. 5— Safer Vulnerable Road Users: Pedestrians, Bicyclists, Motorcyclists, and Older Users , 2010 .

[8]  C. Fernández,et al.  Real-time vision-based blind spot warning system: Experiments with motorcycles in daytime/nighttime conditions , 2013 .

[9]  Christopher Edwards,et al.  Understanding Driver Perceptions of a Vehicle to Vehicle (V2V) Communication System Using a Test Track Demonstration , 2011 .

[10]  Roberto Montanari,et al.  Design of Warning Delivery Strategies in Advanced Rider Assistance Systems , 2011 .

[11]  Chirag Warty,et al.  Collaborative Warning System for Dense Vehicular Networks Using MUSIC Algorithm DoA , 2013, 2013 Third International Conference on Advances in Computing and Communications.

[12]  Francesco Biral,et al.  Comparison of two warning concepts of an intelligent Curve Warning system for motorcyclists in a simulator study. , 2012, Accident; analysis and prevention.

[13]  Steven Reed,et al.  SafetyNet Deliverable 5.9; WP5 Methodology Workshop Report , 2008 .

[14]  José Eugenio Naranjo,et al.  Specification and Development of a HMI for ADAS, Based in Usability and Accessibility Principles , 2010 .

[15]  Frank Köster,et al.  A feasibility study on a cooperative safety application for cyclists crossing intersections , 2012, 2012 15th International IEEE Conference on Intelligent Transportation Systems.

[16]  Vicente Milanés Montero,et al.  Controller for Urban Intersections Based on Wireless Communications and Fuzzy Logic , 2010, IEEE Transactions on Intelligent Transportation Systems.

[17]  José Eugenio Naranjo,et al.  GPS and Inertial Systems for High Precision Positioning on Motorways , 2009, Journal of Navigation.

[18]  Glenn R Widmann,et al.  DEVELOPMENT OF COLLISION AVOIDANCE SYSTEMS AT DELPHI AUTOMOTIVE SYSTEMS , 1998 .

[19]  Zhang Lin,et al.  Design and evaluation of V2X communication system for vehicle and pedestrian safety , 2015 .

[20]  Seiichi Mita,et al.  Embedded multi-sensors objects detection and tracking for urban autonomous driving , 2011, 2011 IEEE Intelligent Vehicles Symposium (IV).

[21]  Domitilla Del Vecchio,et al.  Cooperative Collision Avoidance at Intersections: Algorithms and Experiments , 2013, IEEE Transactions on Intelligent Transportation Systems.

[22]  Gabriel-Miro Muntean,et al.  Short paper: On the potential of V2X communications in helping electric bicycles saving energy , 2013, 2013 IEEE Vehicular Networking Conference.

[23]  Byungkyu Brian Park,et al.  Calibrating Communication Simulator for Connected Vehicle Applications , 2016, J. Intell. Transp. Syst..

[24]  Sergiu Nedevschi,et al.  Real-time driving assistant application for Android-based mobile devices , 2014, 2014 IEEE 10th International Conference on Intelligent Computer Communication and Processing (ICCP).

[25]  Li-Chen Fu,et al.  Combining multiple complementary features for pedestrian and motorbike detection , 2013, 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013).

[26]  Steven E. Shladover,et al.  Analysis of Vehicle Positioning Accuracy Requirements for Communication-Based Cooperative Collision Warning , 2006, J. Intell. Transp. Syst..

[27]  Gaurav Bhatia,et al.  Vehicular Networks for Collision Avoidance at Intersections , 2011 .