Exploiting Wireless Communication in Vehicle Density Estimation

Vehicle density is one of the main metrics used for assessing road traffic condition. High vehicle density indicates that traffic is congested. Currently, most vehicle density estimation approaches are designed for infrastructure-based traffic information systems. These approaches require detection devices such as inductive loop detectors or traffic surveillance cameras to be installed at various locations. Consequently, they are not appropriate for an emerging self-organizing vehicular traffic information system, where vehicles have to collect and process traffic information without relying on any fixed infrastructure. In this paper, we consider a few methods for estimating vehicle density based on the number of vehicles in the vicinity of the probe vehicle and the number of vehicles in a communication cluster.

[1]  O. A. Nielsen,et al.  Estimation of speed-flow and flow-density relations on the motorway network in the greater Copenhagen region , 2008 .

[2]  Bart De Moor,et al.  Cellular automata models of road traffic , 2005, physics/0509082.

[3]  M. Tekalp,et al.  Automatic Vehicle Counting from Video for Traffic Flow Analysis , 2007, 2007 IEEE Intelligent Vehicles Symposium.

[4]  Danijela Cabric,et al.  Characterization of Distance Error with Received Signal Strength Ranging , 2010, 2010 IEEE Wireless Communication and Networking Conference.

[5]  R. L. Anderson Electromagnetic loop vehicle detectors , 1970 .

[6]  Aarnout Brombacher,et al.  Probability... , 2009, Qual. Reliab. Eng. Int..

[7]  Maen Artimy,et al.  Local Density Estimation and Dynamic Transmission-Range Assignment in Vehicular Ad Hoc Networks , 2007, IEEE Transactions on Intelligent Transportation Systems.

[8]  S. Panichpapiboon,et al.  Evaluation of a neighbor-based vehicle density estimation scheme , 2008, 2008 8th International Conference on ITS Telecommunications.

[9]  Benjamin Coifman,et al.  Estimating density and lane inflow on a freeway segment , 2003 .

[10]  P. G. Michalopoulos,et al.  Vehicle detection video through image processing: the Autoscope system , 1991 .

[11]  Bruno O. Shubert,et al.  Random variables and stochastic processes , 1979 .

[12]  Mate Boban,et al.  Impact of Vehicles as Obstacles in Vehicular Ad Hoc Networks , 2011, IEEE Journal on Selected Areas in Communications.

[13]  Michael W. Szeto,et al.  DESIGN OF DENSITY-MEASURING SYSTEMS FOR ROADWAYS , 1974 .

[14]  Ozan K. Tonguz,et al.  Routing in Sparse Vehicular Ad Hoc Wireless Networks , 2007, IEEE Journal on Selected Areas in Communications.

[15]  Stephen G. Ritchie,et al.  Individual Vehicle Speed Estimation Using Single Loop Inductive Waveforms , 1999 .

[16]  N. H. C. Yung,et al.  A Method for Vehicle Count in the Presence of Multiple-Vehicle Occlusions in Traffic Images , 2007, IEEE Transactions on Intelligent Transportation Systems.

[17]  R. L. Lawrence,et al.  The statistical properties of freeway traffic , 1977 .

[18]  John G. Proakis,et al.  Probability, random variables and stochastic processes , 1985, IEEE Trans. Acoust. Speech Signal Process..

[19]  Richard Cowan,et al.  Useful headway models , 1975 .

[20]  Sooksan Panichpapiboon,et al.  Connectivity Requirements for Self-Organizing Traffic Information Systems , 2008, IEEE Transactions on Vehicular Technology.

[21]  Mike McDonald,et al.  Car-following: a historical review , 1999 .

[22]  Joy Dahlgren,et al.  An enhancement to speed estimation using single loop detectors , 2003, Proceedings of the 2003 IEEE International Conference on Intelligent Transportation Systems.

[23]  Elizabeth M. Belding-Royer,et al.  A review of current routing protocols for ad hoc mobile wireless networks , 1999, IEEE Wirel. Commun..

[24]  Denos C. Gazis,et al.  On-Line Estimation of Traffic Densities from Time-Series of Flow and Speed Data , 1971 .

[25]  L. Alvarez-Icaza,et al.  Adaptive observer for traffic density estimation , 2004, Proceedings of the 2004 American Control Conference.

[26]  Tinku Mohamed Rasheed,et al.  An Infrastructure-Free Traffic Information System for Vehicular Networks , 2007, 2007 IEEE 66th Vehicular Technology Conference.

[27]  K. Harada,et al.  An automatic system for counting and capturing the pictures of moving vehicles in real-time , 2003, IEEE IV2003 Intelligent Vehicles Symposium. Proceedings (Cat. No.03TH8683).