Modeling Impact of Sensor Placement for Vision-Based Traffic Monitoring

A generic sensor placement model for vision-based traffic monitoring is the focus of this study. A significant problem with such sensors is the difficulty in detection because of the occlusion between vehicles. Thus, the efficiency of traffic monitoring can be directly affected by sensor placement. To simulate various traffic flows, models are developed for various aspects of moving traffic. Such models include Gaussian mixture distributions for vehicle dimensions and the distribution for gap length between vehicles. These models are used to predict the vehicle detection error in a traffic flow as perceived from various sensor locations when vehicle headlight detection methods are used. Validation of the model has shown that accuracy is consistent with performance from a vehicle detection framework with approximately 3% variance on average.

[1]  Kaan Ozbay,et al.  A Clustering Based Methodology for Determining the Optimal Roadway Configuration of Detectors for Travel Time Estimation , 2007, 2007 IEEE Intelligent Vehicles Symposium.

[2]  Jianhua Xu,et al.  Robust placement of sensors in dynamic water distribution systems , 2010, Eur. J. Oper. Res..

[3]  K. Ozbay,et al.  A Clustering Based Methodology for Determining the Optimal Roadway Configuration of Detectors for Travel Time Estimation , 2006, 2006 IEEE Intelligent Transportation Systems Conference.

[4]  Kostia Robert.  Night-Time Traffic Surveillance: A Robust Framework for Multi-vehicle Detection, Classification and Tracking , 2009, 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance.

[5]  Tim Tau Hsieh.  Using sensor networks for highway and traffic applications , 2004, IEEE Potentials.

[6]  Thia Kirubarajan,et al.  Hierarchical markov decision processes based distributed data fusion and collaborative sensor management for multitarget multisensor tracking applications , 2007, 2007 IEEE International Conference on Systems, Man and Cybernetics.

[7]  Galen H. Sasaki,et al.  Wireless sensor placement for reliable and efficient data collection , 2003, 36th Annual Hawaii International Conference on System Sciences, 2003. Proceedings of the.

[8]  S. Sitharama Iyengar,et al.  Sensor placement for grid coverage under imprecise detections , 2002, Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997).

[9]  Andreas Krause,et al.  Simultaneous placement and scheduling of sensors , 2009, 2009 International Conference on Information Processing in Sensor Networks.

[10]  Weimin Huang,et al.  Effect of Sensor Spacing on Performance Measure Calculations , 2006 .

[11]  Yang Wang,et al.  Vehicle occlusion model for traffic monitoring , 2010, IWCTS '10.

[12]  C. Guestrin,et al.  Distributed localization of networked cameras , 2006, 2006 5th International Conference on Information Processing in Sensor Networks.

[13]  Alexandre M. Bayen,et al.  A Framework for Analyzing the Sensitivity of Traffic Data Quality to Sensor Location and Spacing , 2008 .

[14]  Yang Wang,et al.  On the performance of adaptive traffic signal control , 2009, IWCTS '09.

[15]  Thomas F. La Porta,et al.  Movement-assisted sensor deployment , 2004, IEEE INFOCOM 2004.