A Study Of Vehicle Multi-Warning Control System Based On AHP-Gray Fuzzy

Vehicular Ad Hoc Networks (VANETs) is a emerging mobile network, which is applied in communications between vehicles. Supporting dynamic, random, multi-hop topology, it has broad application prospects on security warning, assistance driving, vehicle coordination, and multimedia resource sharing, etc. On the one hand, a vehicle is a node and information exchange uses radio communication between vehicles in VANWTs. As path loss, distance effect, and Doppler effect in radio communication, there are inaccurate interactive information of nodes between the vehicle, even causing data forwarding failure. Therefore, vehicles can not get relevant traffic information. In the vehicle-intensive scenes, since the channel of communication between the vehicles used is not authorized by the channel 5.8Hz, increasing of information transfer rate, and limited channel bandwidth, congestion may occurs. On the other hand, with the acceleration of China’s highway construction, significantly increased traffic on the highway, so traffic accidents increase rapidly. Most highway accident due to rear-end collision. Thus, to ensure the validity and accuracy of information exchange between vehicles in the vehicle-intensive scenes, to further study safe distance in highway traffic and influent factors under the circumstance of smooth flow of information exchange between vehicles, to help the driver control speed according to security alert is significantly important to prevent rear-end traffic.In this paper, we propose a network-based vehicle congestion multi-level warning control system on the basis of the characteristics of vehicular ad-hoc network and wireless communication. The whole system consists two parts. The first part is vehicle network data distribution based on congestion game theory. The main idea of the theory is to apply it to vehicle network data distribution in order to get the best data distribution slot allocation matrix and ensuring each vehicle can get maximum effectiveness. Taking into account the different service requirement of different vehicles, the safely and quality (QoS) is introduced into utility function. The congestion game algorithm in this paper can effectively reduce network congestion. And it can be used for congestion control both in the vehicle-intensive scenes and safety-related data distribution. The second part is vehicle active safety warning and control system based on AHP-gray fuzzy control, based on the first part. To obtain velocity, acceleration, and position information of own and surrounding vehicle by vehicle to vehicle communication and by communication to infrastructure. Such as to obtain weather, traffic and pedestrian information by GPS, GIS, etc. Combining method of AHP and gray blur after receiving the information, next to calculate the vehicle absolutely safe distance and relatively safe distance. Then, to judge the state of the vehicle safety and warning according to this two safe distance. Finally, depending on the state of the vehicle to help the driver control the vehicle in order to ensure traffic safety.