An online target tracking protocol for vehicular Ad Hoc networks

Target tracking in vehicular ad hoc networks (VANETs) contributes to the design of many types of applications, namely: traffic management, security, car recovery and apprehension of an illegal runaway target. Inter-vehicular communication allows vehicles to participate and collaborate in the tracking process. For such applications, a large volume of data can be required to be transferred between the participating vehicles and a control center, which can easily congest the wireless network in a VANET and decrease the tracking efficiency if not managed properly. Therefore, one important challenge in this context is optimizing bandwidth usage to avoid collisions, delays and accelerate the overall tracking process. Thus, we propose a collaborative tracking protocol for VANETs based on a new strategy that we named virtual RSUs, which aims essentially to ensure the network communication coverage during the tracking process on the one hand, and on the other hand, to optimize bandwidth usage during the overall tracking process. In addition, in order to deal with uncertainties and enhance the tracking precision and further decrease the network load, we propose a theoretical pertinence level assignment strategy based on the Transferable Belief Model (TBM), that takes the target detection notifications as inputs. We believe this protocol holds potentials to serve as a basic algorithm to implement vehicle tracking applications for VANETs. Simulative study demonstrates clearly that the proposed protocol provides better performance in terms of network load for target tracking in a VANET as compared to a previous approach.

[1]  Brad Karp,et al.  GPSR: greedy perimeter stateless routing for wireless networks , 2000, MobiCom '00.

[2]  György Pongor,et al.  OMNeT: Objective Modular Network Testbed , 1993, MASCOTS.

[3]  Yi-Bing Lin,et al.  Location Tracking for WAVE Unicast Service , 2010, 2010 IEEE 71st Vehicular Technology Conference.

[4]  Abdelhamid Mellouk,et al.  An Evidence-Based Sensor Coverage Model , 2012, IEEE Communications Letters.

[5]  Atanu Mondal,et al.  Identification, authentication and tracking algorithm for vehicles using VIN in distributed VANET , 2012, ICACCI '12.

[6]  D. E. Manolakis,et al.  Efficient solution and performance analysis of 3-D position estimation by trilateration , 1996 .

[7]  Michel Barbeau,et al.  Non-cooperating vehicle tracking in VANETs using the conditional logit model , 2013, 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013).

[8]  Moussaoui Samira,et al.  Target Tracking in VANETs Using V2I and V2V Communication , 2014, 2014 International Conference on Advanced Networking Distributed Systems and Applications.

[9]  Mircea Popa,et al.  A solution for tracking a fleet of vehicles , 2011, 2011 19thTelecommunications Forum (TELFOR) Proceedings of Papers.

[10]  Yu-Chee Tseng,et al.  A vehicular surveillance and sensing system for car security and tracking applications , 2010, IPSN '10.

[11]  Azzedine Boukerche,et al.  The Trap Coverage Area Protocol for Scalable Vehicular Target Tracking , 2017, IEEE Access.

[12]  Daniel Krajzewicz,et al.  SUMO (Simulation of Urban MObility) - an open-source traffic simulation , 2002 .

[13]  Azzedine Boukerche,et al.  Cooperative target tracking in vehicular sensor networks , 2012, IEEE Wireless Communications.

[14]  Richard Werner Nelem Pazzi,et al.  Using clustering for target tracking in vehicular ad hoc networks , 2017, Veh. Commun..

[15]  Khalil El-Khatib,et al.  A distributed clustering algorithm for target tracking in vehicular ad-hoc networks , 2013, DIVANet '13.

[16]  Stephen D. Wolthusen,et al.  Algorithmic approach for clandestine localisation and tracking in short-range environments , 2012, Int. J. Commun. Networks Distributed Syst..

[17]  Azzedine Boukerche,et al.  Vehicular Ad Hoc Networks: A New Challenge for Localization-Based Systems , 2008, Comput. Commun..

[18]  Michel Barbeau,et al.  Tracking an on the run vehicle in a metropolitan VANET , 2013, 2013 IEEE Intelligent Vehicles Symposium (IV).

[19]  Sencun Zhu,et al.  SVATS: A Sensor-Network-Based Vehicle Anti-Theft System , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[20]  Philippe Smets,et al.  The Transferable Belief Model , 1994, Artif. Intell..

[21]  Stephen D. Wolthusen,et al.  Probabilistic Vehicular Trace Reconstruction Based on RF-Visual Data Fusion , 2010, Communications and Multimedia Security.

[22]  T. Denœux Conjunctive and disjunctive combination of belief functions induced by nondistinct bodies of evidence , 2008 .

[23]  Aravind Kota Gopalakrishna,et al.  On the architecture of vehicle tracking system using wireless sensor devices , 2009, 2009 International Conference on Ultra Modern Telecommunications & Workshops.

[24]  Luca Delgrossi,et al.  IEEE 802.11p: Towards an International Standard for Wireless Access in Vehicular Environments , 2008, VTC Spring 2008 - IEEE Vehicular Technology Conference.