A novel, modular validation framework for collision avoidance of automated vehicles at road junctions

This paper presents a new validation method for automated driving systems at road junctions. The method comprises the clustering of critical traffic scenarios at junctions as well as a simulation and evaluation framework to validate those scenarios. The safety performance indicators selected and implemented in the framework can be seen as a new reference for conducting virtual tests at junctions. The applicability of the framework is demonstrated by an experiment based on a selected car-to-car collision scenario. Considering the current progression of automated transport, this work is highly relevant for virtual testing procedures and is an important step towards approval and certification of automated vehicles.

[1]  Ulrich Sander,et al.  Opportunities and limitations for intersection collision intervention-A study of real world 'left turn across path' accidents. , 2017, Accident; analysis and prevention.

[2]  Richard J. Beckman,et al.  A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a Computer Code , 2000, Technometrics.

[3]  Philippe Nitsche,et al.  Pre-crash scenarios at road junctions: A clustering method for car crash data. , 2017, Accident; analysis and prevention.

[4]  Durga Toshniwal,et al.  Analysing road accident data using association rule mining , 2015, 2015 International Conference on Computing, Communication and Security (ICCCS).

[5]  Paolo Falcone,et al.  Collision avoidance at intersections: A probabilistic threat-assessment and decision-making system for safety interventions , 2014, 17th International IEEE Conference on Intelligent Transportation Systems (ITSC).

[6]  S. M. Sohel Mahmud,et al.  Application of proximal surrogate indicators for safety evaluation: A review of recent developments and research needs , 2017 .

[7]  Qingfeng Huang,et al.  An adaptive peer-to-peer collision warning system , 2002, Vehicular Technology Conference. IEEE 55th Vehicular Technology Conference. VTC Spring 2002 (Cat. No.02CH37367).

[8]  Hwasoo Yeo,et al.  Identifying major accident scenarios in intersection and evaluation of collision warning system , 2017, 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC).

[9]  Jonathan M Hankey,et al.  A method for evaluating collision avoidance systems using naturalistic driving data. , 2008, Accident; analysis and prevention.

[10]  Matthias Althoff,et al.  Comparison of Markov Chain Abstraction and Monte Carlo Simulation for the Safety Assessment of Autonomous Cars , 2011, IEEE Transactions on Intelligent Transportation Systems.

[11]  Ernst Stadlober,et al.  Virtual Stochastic Testing of Advanced Driver Assistance Systems , 2016 .

[12]  Majid Sarvi,et al.  Calculating time-to-collision for analysing right turning behaviour at signalised intersections , 2012 .

[13]  Dot Hs,et al.  Development of an FCW Algorithm Evaluation Methodology With Evaluation of Three Alert Algorithms , 2009 .

[14]  Nils Lubbe,et al.  Market penetration of intersection AEB: Characterizing avoided and residual straight crossing path accidents. , 2018, Accident; analysis and prevention.

[15]  Das Amrita,et al.  Mining Association Rules between Sets of Items in Large Databases , 2013 .

[16]  Lutz Eckstein,et al.  Evaluation of Automated Road Vehicles , 2014 .

[17]  Omar Bagdadi,et al.  Estimation of the severity of safety critical events. , 2013, Accident; analysis and prevention.

[18]  Jeffery Archer,et al.  Indicators for traffic safety assessment and prediction and their application in micro-simulation modelling : a study of urban and suburban intersections , 2005 .

[19]  Andreas Moser,et al.  Reconstruction of Twenty Staged Collisions with PC-Crash's Optimizer , 2001 .

[20]  Said M. Easa,et al.  Proposed collision warning system for right-turning vehicles at two-way stop-controlled rural intersections , 2014 .

[21]  Halil Beglerovic,et al.  Model-based safety validation of the automated driving functio highway pilot , 2017 .

[22]  Andrés Aparicio,et al.  ASSESS deliverable D1.4, Safety impact assessment of integrated vehicle safety systems , 2012 .

[23]  Andreas Pütz,et al.  System validation of highly automated vehicles with a database of relevant traffic scenarios , 2017 .

[24]  James A Misener Cooperative Intersection Collision Avoidance System (CICAS): Signalized Left Turn Assist and Traffic Signal Adaptation , 2010 .

[25]  Damith C. Ranasinghe,et al.  An Evaluation Framework , 2008 .

[26]  Nidhi Kalra,et al.  Driving to Safety , 2016 .

[27]  Fawzi Nashashibi,et al.  Intersection safety using lidar and stereo vision sensors , 2011, 2011 IEEE Intelligent Vehicles Symposium (IV).

[28]  Thomas Helmer,et al.  Development of a Methodology for the Evaluation of Active Safety using the Example of Preventive Pedestrian Protection , 2014 .

[29]  別所 誠人,et al.  Tire pressure monitoring system and pressure monitoring unit , 2009 .

[30]  Åse Svensson,et al.  A method for analysing the traffic process in a safety perspective , 1998 .

[31]  C. Hydén THE DEVELOPMENT OF A METHOD FOR TRAFFIC SAFETY EVALUATION: THE SWEDISH TRAFFIC CONFLICTS TECHNIQUE , 1987 .

[32]  Stijn Daniels,et al.  In search of the severity dimension of traffic events: Extended Delta-V as a traffic conflict indicator. , 2017, Accident; analysis and prevention.

[33]  Hampton C. Gabler,et al.  Safety Benefits of Forward Collision Warning, Brake Assist, and Autonomous Braking Systems in Rear-End Collisions , 2012, IEEE Transactions on Intelligent Transportation Systems.

[34]  Hermann Winner,et al.  Absicherung automatischen Fahrens, Vortrag 6. Tagung Fahrerassistenz , 2013 .

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

[36]  Felix Fahrenkrog,et al.  A Comprehensive Evaluation Approach for Highly Automated Driving , 2017 .

[37]  P. Rousseeuw Silhouettes: a graphical aid to the interpretation and validation of cluster analysis , 1987 .

[38]  Tim De Ceunynck,et al.  Defining and applying surrogate safety measures and behavioural indicators through site-based observations , 2017 .