Intelligent Vehicular Warning System for VANET

Abstract:

The vehicular ad hoc network (VANET) has made significant progress in recent years, attracting a lot of interest from academia and the industry. VANET involves vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications based on a wireless network. V2I refers to the communication between vehicles and infrastructure of roadside unit (RSU), e.g., a base station and access point (AP) connected to the Internet. V2V refers to the direct or multi-hop communications among vehicles in VANET. V2V is efficient and cost effective owing to its short range bandwidth advantage and its ad hoc nature. V2V communications are enabling technologies that enhance the driver’s awareness of nearby vehicular traffic, leading to improved traffic safety and efficiency. The V2V mode provides a communications platform between road vehicles (cars, bikes, scooters, motorcycles, trucks, etc.) without requiring a central control unit. Safety-related V2V applications are enabled via an integrated early warning mechanism. To facilitate safe driving, we propose an Intelligent Vehicular Warning System (IVWS) that sends an immediate warning message in the event of an accident. According to V2V communications, the other cars or vehicles could have enough time to avoid the accident and make an appropriate decision such as slow down, stop, and detour after receiving the urgent warning messages. Furthermore, the local CMS (Changeable Message Sign) can show the accident information for neighbor vehicles when receiving the warning message. To achieve experimental architecture with our proposed IVWS, the robot vehicles have been designed to simulate vehicles on the road. Besides, vehicles also apply ZigBee wireless interface to communicate with each other. The experiment has shown that our proposed intelligent system can initially provide message display and safety driving for vehicles when traffic accident occurred.

• Periodical: Applied Mechanics and Materials (Volume 145)
• Pages: 164-168
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.145.164
• Online since: December 2011
• Authors: Yi Ting Mai, Jeng Yueng Chen, Yi Kuan Liu, Wen Yi Lee, Guan Ting Wu, Ming Yuan Li
• Keywords: Safety, Traffic Accident, VANET, Vehicular Warning System, ZigBee

References

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