Research on Vehicle Automatically Tracking Mechanism in VANET

The intelligent vehicle is a complex system equipped with advanced technologies such as the artificial intelligence, automatic control, and computer, communication. It is a combination of multiple academic subjects and the latest technologies representing the developing tendency of future automobile technology and attracts more and more attention. In this paper, we made some useful explorations in the fields of intelligent vehicle control technology and obstacle avoidance, and a deep research is carried out about the distance of vehicle, vehicle tracking, vehicle lane changing and intersections obstacle avoidance and communication protocols, and some innovative ideas are proposed during the research. By using VANET, some predictable status of tracing and tracking of intelligent vehicle technology was researched, and the communication protocols between two vehicles, the safe spacing algorithm, the method of computing the actual distance at corners and straights, and the trajectory of lane change were designed. In addition, a series of vehicle tracing and tracking technologies, such as without knowing the road conditions, homeostatic mechanism, keeping a safe spacing to the target vehicle, and adjusting its own speed to track the target vehicle smoothly to the destination by comparing the actual distance and safe spacing between vehicles, were discussed here.

[1]  Sonia Martinez,et al.  Deployment algorithms for a power‐constrained mobile sensor network , 2010 .

[2]  Paul J. M. Havinga,et al.  A virtual infrastructure based on honeycomb tessellation for data dissemination in multi-sink mobile wireless sensor networks , 2012, EURASIP J. Wirel. Commun. Netw..

[3]  Lu Zhao,et al.  An Adaptive Opportunistic Network Coding Mechanism in Wireless Multimedia Sensor Networks , 2012, Int. J. Distributed Sens. Networks.

[4]  Qiang Yang,et al.  Tracking Mobile Users in Wireless Networks via Semi-Supervised Colocalization , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Dipankar Raychaudhuri,et al.  Frontiers of Wireless and Mobile Communications , 2012, Proceedings of the IEEE.

[6]  Sonia Martínez,et al.  Coverage control for mobile sensing networks , 2002, IEEE Transactions on Robotics and Automation.

[7]  Jie Jia,et al.  Energy-Balanced Density Control to Avoid Energy Hole for Wireless Sensor Networks , 2012, Int. J. Distributed Sens. Networks.

[8]  Xiaohua Jia,et al.  Exploiting Data Fusion to Improve the Coverage of Wireless Sensor Networks , 2012, IEEE/ACM Transactions on Networking.

[9]  Minyi Guo,et al.  Adaptive Forwarding Delay Control for VANET Data Aggregation , 2012, IEEE Transactions on Parallel and Distributed Systems.

[10]  Sooksan Panichpapiboon,et al.  A Review of Information Dissemination Protocols for Vehicular Ad Hoc Networks , 2012, IEEE Communications Surveys & Tutorials.

[11]  Charalampos Konstantopoulos,et al.  A Rendezvous-Based Approach Enabling Energy-Efficient Sensory Data Collection with Mobile Sinks , 2012, IEEE Transactions on Parallel and Distributed Systems.

[12]  Donghyun Kim,et al.  Minimizing data collection latency in wireless sensor network with multiple mobile elements , 2012, 2012 Proceedings IEEE INFOCOM.