A System for Traffic Violation Detection

This paper describes the framework and components of an experimental platform for an advanced driver assistance system (ADAS) aimed at providing drivers with a feedback about traffic violations they have committed during their driving. The system is able to detect some specific traffic violations, record data associated to these faults in a local data-base, and also allow visualization of the spatial and temporal information of these traffic violations in a geographical map using the standard Google Earth tool. The test-bed is mainly composed of two parts: a computer vision subsystem for traffic sign detection and recognition which operates during both day and nighttime, and an event data recorder (EDR) for recording data related to some specific traffic violations. The paper covers firstly the description of the hardware architecture and then presents the policies used for handling traffic violations.

[1]  Tarak Gandhi,et al.  Looking-In and Looking-Out of a Vehicle: Computer-Vision-Based Enhanced Vehicle Safety , 2007, IEEE Transactions on Intelligent Transportation Systems.

[2]  Alastair R. Allen,et al.  Using self-organising maps in the detection and recognition of road signs , 2009, Image Vis. Comput..

[3]  Nikolaos Papanikolopoulos,et al.  Driver fatigue: a vision-based approach to automatic diagnosis , 2001 .

[4]  Hiroaki Ishikawa,et al.  Improving driving behavior by allowing drivers to browse their own recorded driving data , 2011, 2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC).

[5]  José Eugenio Naranjo,et al.  Autonomous Manoeuvring Systems for Collision Avoidance on Single Carriageway Roads , 2012, Sensors.

[6]  William J Horrey,et al.  Assessing the awareness of performance decrements in distracted drivers. , 2008, Accident; analysis and prevention.

[7]  Keiichi Uchimura,et al.  Driver Inattention Monitoring System for Intelligent Vehicles: A Review , 2009, IEEE Transactions on Intelligent Transportation Systems.

[8]  Michael Isard,et al.  Active Contours: The Application of Techniques from Graphics, Vision, Control Theory and Statistics to Visual Tracking of Shapes in Motion , 2000 .

[9]  A. Ardeshir Goshtasby.  On edge focusing , 1994, Image Vis. Comput..

[10]  Dariu M. Gavrila,et al.  Steering and evasion assist , 2012 .

[11]  Pradeep Mitra Ecspe,et al.  REPORT NO , 2001 .

[12]  José Manuel Pastor,et al.  Visual sign information extraction and identification by deformable models for intelligent vehicles , 2004, IEEE Transactions on Intelligent Transportation Systems.

[13]  Miguel Ángel Sotelo,et al.  Real-time system for monitoring driver vigilance , 2004, Proceedings of the IEEE International Symposium on Industrial Electronics, 2005. ISIE 2005..

[14]  William J. Horrey,et al.  Driver-initiated distractions: examining strategic adaptation for in-vehicle task initiation. , 2009, Accident; analysis and prevention.

[15]  Preeti R. Bajaj,et al.  Centroid Based Detection Algorithm for Hybrid Traffic Sign Recognition System , 2010, 2010 3rd International Conference on Emerging Trends in Engineering and Technology.

[16]  Xiaoliang Ma,et al.  Behavior Measurement, Analysis, and Regime Classification in Car Following , 2007, IEEE Transactions on Intelligent Transportation Systems.

[17]  Mohan M. Trivedi,et al.  Video-based lane estimation and tracking for driver assistance: survey, system, and evaluation , 2006, IEEE Transactions on Intelligent Transportation Systems.

[18]  Samuel Adu Sarkodie.  Road Safety Research , 2005 .

[19]  S Rajalin,et al.  The connection between risky driving and involvement in fatal accidents. , 1994, Accident; analysis and prevention.

[20]  Thomas Kalinke,et al.  An image processing system for driver assistance , 2000, Image Vis. Comput..

[21]  Nourdine Aliane,et al.  Driver behavior monitoring system based on traffic violation , 2012, 2012 IEEE Intelligent Vehicles Symposium.

[22]  Saturnino Maldonado-Bascón,et al.  Goal Evaluation of Segmentation Algorithms for Traffic Sign Recognition , 2010, IEEE Transactions on Intelligent Transportation Systems.

[23]  H. Fleyeh,et al.  Color detection and segmentation for road and traffic signs , 2004, IEEE Conference on Cybernetics and Intelligent Systems, 2004..

[24]  Azriel Rosenfeld,et al.  Computer Vision , 1988, Adv. Comput..

[25]  Visvanathan Ramesh,et al.  A system for traffic sign detection, tracking, and recognition using color, shape, and motion information , 2005, IEEE Proceedings. Intelligent Vehicles Symposium, 2005..

[26]  Arturo de la Escalera,et al.  Traffic sign recognition and analysis for intelligent vehicles , 2003, Image Vis. Comput..

[27]  Dariu Gavrila,et al.  Active Pedestrian Safety by Automatic Braking and Evasive Steering , 2011, IEEE Transactions on Intelligent Transportation Systems.

[28]  Jordi Vitrià,et al.  Traffic-Sign Recognition Systems , 2011, Springer Briefs in Computer Science.

[29]  Juan Zamorano,et al.  Argos: An Advanced In-Vehicle Data Recorder on a Massively Sensorized Vehicle for Car Driver Behavior Experimentation , 2010, IEEE Transactions on Intelligent Transportation Systems.

[30]  Tomer Toledo,et al.  In-vehicle data recorders for monitoring and feedback on drivers' behavior , 2008 .

[31]  Ho Gi Jung,et al.  A New Approach to Urban Pedestrian Detection for Automatic Braking , 2009, IEEE Transactions on Intelligent Transportation Systems.

[32]  Nourdine Aliane,et al.  Traffic violation alert and management , 2011, 2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC).