Research On Urban VANET Routing Method Based On Geographic Location Information

VANET(Vehicular Ad Hoc Network)is a new technology of intelligent transportation system in smart city.In VANET,the main nodes are vehicles running on the road,and the nodes communicate wirelessly through the vehicle wireless communication equipment which can realize the transmission of various traffic assistance and safety warning information.As the key technology of network layer,routing decision has an important impact on the performance of VANET network communication.With the improvement of vehicle positioning service accuracy,the routing method based on geographic location information can route according to the real-time updated vehicle location information,which has gradually become the mainstream research direction of VANET routing method.Owing to the typical GPSR(Greedy Perimeter Stateless)routing method based on geographical location information,this paper proposes LQ-GPSR based on link quality optimization and PSO-GPSR routing method based on particle swarm optimization.In the greedy forwarding stage of LQ-GPSR,the reliable communication range is defined according to the distance factor,and the link quality evaluation standard and neighbor node density are introduced.Finally,the link quality and neighbor node density are combined to calculate the metric of candidate nodes in the reliable communication range,and the node with the highest metric in the candidate nodes is selected for forwarding.At the same time,in the peripheral forwarding stage,the forwarding angle between the candidate node and the destination node,the link quality and the neighbor node density are taken into account,and the global weight formula is designed to select the node with the highest weight to transmit the next hop.With the purpose of tackling the difficulty of routing performance instability attributed by the instantaneous dynamic topology of the VANET,PSO-GPSR uses particle swarm optimization algorithm to replace greedy forwarding,and selects the node with the best comprehensive performance as the next hop forwarding node through particle swarm iteration.Through simulation and comparison experiments,it is concluded that LQ-GPSR reduces the path redundancy while ensuring the stability of the communication link by selecting candidate nodes with better link quality and high neighbor node density,and improves the routing delivery rate and reduces the routing delay.PSO-GPSR uses particle swarm optimization algorithm to help select the optimal relay forwarding node,which can adapt to the dynamic topology,select the optimal relay node with integrated routing performance in the network at the forwarding time,and improve the stability of routing performance.