Cooperative vehicle positioning with multi-sensor data fusion and vehicular communications

Vehicular positioning with multi-sensor fusion has achieved promising results in recent years. Having potential benefit from the emerging vehicular communications based on IEEE 802.11p dedicated short-range communication (DSRC), cooperative positioning opens new opportunities to support several vehicular applications. In addition, radar based active safety functions and GPS are being integrated into modern vehicles. With the availability of information from multiple sources, exchange of sensor information and multi-sensor fusion can be applied to obtain the precise positioning of vehicle without substantial additional cost. However, the main challenge in data fusion is the inherent data association problem due to dissimilar measurement update rate of DSRC and automotive radar. To overcome these challenges, this paper proposes a robust positioning approach considering track-to-track matching and fusion of position information obtained from multiple on-board sources such as GPS receiver, Vehicle-to-vehicle communication and automotive radar. Realistic 3D road traffic and wave propagation model is developed using a ray-tracing tool and the effectiveness of the proposed concept was evaluated. The system concept is validated by conducting extensive simulation considering realistic car following model. Results show that the proposed cooperative positioning method exhibits significant improvement in terms of positioning accuracy.

[1]  T. Zwick,et al.  Millimeter-Wave Technology for Automotive Radar Sensors in the 77 GHz Frequency Band , 2012, IEEE Transactions on Microwave Theory and Techniques.

[2]  Yuming Ou,et al.  An Investigation of Positioning Accuracy Transmitted by Connected Heavy Vehicles Using DSRC , 2017 .

[3]  Dominique Gruyer,et al.  A New Decentralized Bayesian Approach for Cooperative Vehicle Localization Based on Fusion of GPS and VANET Based Inter-Vehicle Distance Measurement , 2015, IEEE Intelligent Transportation Systems Magazine.

[4]  B. Hofmann-Wellenhof,et al.  Global Positioning System , 1992 .

[5]  Alexiadis,et al.  The next generation simulation program , 2004 .

[6]  Fabian de Ponte Muller.  Survey on Ranging Sensors and Cooperative Techniques for Relative Positioning of Vehicles. , 2017 .

[7]  Yasmine A. Fahmy,et al.  High Accuracy GPS-Free Vehicle Localization Framework via an INS-Assisted Single RSU , 2015, Int. J. Distributed Sens. Networks.

[8]  X. Chen,et al.  A global optimization algorithm for trajectory data based car-following model calibration , 2016 .

[9]  Steven E. Shladover,et al.  Analysis of Vehicle Positioning Accuracy Requirements for Communication-Based Cooperative Collision Warning , 2006, J. Intell. Transp. Syst..

[10]  Tao Zhang,et al.  Vehicular Communications Using DSRC: Challenges, Enhancements, and Evolution , 2013, IEEE Journal on Selected Areas in Communications.

[11]  H. Rohling,et al.  Radar waveform for automotive radar systems and applications , 2008, 2008 IEEE Radar Conference.

[12]  Fabian de Ponte Müller,et al.  Cooperative positioning and radar sensor fusion for relative localization of vehicles , 2016, 2016 IEEE Intelligent Vehicles Symposium (IV).

[13]  Jing Li,et al.  GPS accuracy estimation using map matching techniques: Applied to vehicle positioning and odometer calibration , 2006, Comput. Environ. Urban Syst..

[14]  Véronique Berge-Cherfaoui,et al.  A track-to-track association method for automotive perception systems , 2012, 2012 IEEE Intelligent Vehicles Symposium.

[15]  John B. Kenney,et al.  Dedicated Short-Range Communications (DSRC) Standards in the United States , 2011, Proceedings of the IEEE.

[16]  Jian Wang,et al.  A Tightly-Coupled GPS/INS/UWB Cooperative Positioning Sensors System Supported by V2I Communication , 2016, Sensors.

[17]  Abdelmoumen Norrdine,et al.  An algebraic solution to the multilateration problem , 2012 .

[18]  Gilwon Seo,et al.  Demo: Implementation of IEEE 802.11p transceiver using USRP-RIO By LabVIEW Communications , 2015, 2015 IEEE Vehicular Networking Conference (VNC).

[19]  Charles Wang,et al.  Vehicle-to-Vehicle Real-Time Relative Positioning Using 5.9 GHz DSRC Media , 2013, 2013 IEEE 78th Vehicular Technology Conference (VTC Fall).

[20]  Mate Boban,et al.  Vehicular Communications: Survey and Challenges of Channel and Propagation Models , 2015, IEEE Vehicular Technology Magazine.

[21]  Ryan Close,et al.  Fusion of lidar and radar for detection of partially obscured objects , 2015, Defense + Security Symposium.

[22]  Lorenzo Rubio,et al.  Path Loss Characterization for Vehicular Communications at 700 MHz and 5.9 GHz Under LOS and NLOS Conditions , 2014, IEEE Antennas and Wireless Propagation Letters.

[23]  Hirozumi Yamaguchi,et al.  Cooperative Vehicle Positioning via V2V Communications and Onboard Sensors , 2011, 2011 IEEE Vehicular Technology Conference (VTC Fall).

[24]  Taimoor Abbas.  Measurement Based Channel Characterization and Modeling for Vehicle-to-Vehicle Communications , 2014 .

[25]  Ta-Sung Lee,et al.  Design of an FMCW radar baseband signal processing system for automotive application , 2016, SpringerPlus.