Research Of Armed Vehicle Patrols Route Planning Techniques Based On VANET

Patrol is one of the most important daily duty of Chinese Armed Police Force(CAPF).It is critical to the security and stability of country and society,and is also the basic guarantee of successful completion of various tasks.For now,there are still some defects on most previous researches with respect to patrol.They are concentrated on:(1)Under the urban armed patrols scenario,patrol schemes and the realistic tasks are difficult to match.Patrol routers are always unplanned and crude.(2)The level of informatization construction in military vehicle equipment is low;the primary method of communications among the patrol vehicles is through vehicular radio.It's difficult to master the situation around the vehicle,and means of handling the sudden affairs is still lacking.(3)It rarely takes into account the traffic congestion when deciding the vehicle routing.To solve these problems above,a novel real-time monitoring traffic congestion information sharing scheme for VANET communication is proposed.We have studied on the key technologies of route planning and the shortest path problem,and give an improvement algorithm.Then we design a real-time armed vehicle patrol planning system,which is based on VANET.The specific research works are as follow.1.For collecting and broadcasting the traffic jam information,an efficient and real-time network information sharing scheme is proposed,which is based on VENET communication.First of all,each vehicle gathers real-time information(speed,location,traveling direction,etc)of its surrounding vehicles,and generates traffic evaluation report.Second,a location-based cluster mechanism is applied to divide the area of interest into a set of adjacent,non-overlapping and manageable clusters.At last,in each cluster,one transmit vehicle is chosen to send its own cluster's traffic evaluation report to its neighbor clusters.These reports are sent from one cluster to the other cluster until they reach the both ends' Road Side Units(RSUs).Then RSUs can use these reports to evaluate the whole segment's traffic condition.The simulation results show that competing with traditional algorithm our approach has several advantages such as real-time capability,lower bandwidth consumption and high information accuracy.2.For optimization of CAPF patrol schemes,our research is divided into two parts: initial configuration and dynamic Planning of patrol.In the aspect of initial configuration,we propose an advanced Genetic Algorithm(GA),which utilizes elite-reservation mechanism to optimize initial configuration.This method can effectively reduce the number of iterations.In the aspect of dynamic Planning of patrol configuration,after taking dynamic patrol route and hiding into account,we propose a path roulette algorithm based on traffic congestion and priorities of path probability model.This method would do well on arrival rate,coverage and hiding.3.For disposal situation issue during the armed patrol,we propose a variable-weight network quickly path generating algorithm based on routing mechanism after fully considering the traffic jam case.This scheme can quickly calculate the shortest path even if traffic jam happens.Compared traditional method with simulation method,our scheme can quickly adjust the route base on the actual situation.This algorithm has a lower computational cost;it's very useful for the future real-world experience.4.Based on VANET,a real-time armed vehicle patrol planning system is proposed.This system is made up of traffic detection module and patrol planning module.The main function of traffic detection module is to collect and calculate located region's traffic jam information by the same region's moving vehicles;the main function of patrol planning module is to afford assistant decision for patrol vehicle's conventional patrol scheme and emergency disposal scheme,which is primarily utilizing the traffic jam information from the traffic detection module.At last,the proposed scheme is verified by simulation experiments.