Research On Cooperative Neighboring Vehicle Positioning And Vehicle Platooning Based On Vehicular Networks

The rapid development of the automobile industry has brought great convenience to people's travel,but also brought a series of problems such as congestion,frequent traffic accidents,exhaust emissions and energy consumption.In order to cope with serious traffic problems,autonomous driving and Internet of vehicle(IoV)technologies have become research hotspots.Autonomous driving technology relies on the perception of the surrounding traffic environment(positioning of neighboring vehicles,etc.)to control the vehicle itself.IoV technology enables vehicles to communication with vehicles,pedestrians and roadside units,providing auxiliary information for vehicle driving and intelligent traffic management.Based on autonomous driving technology,platooning technology reduces wind resistance,energy consumption and emissions by maintaining a small and stable distance between vehicles,while ensuring vehicle safety.This thesis studies on neighboring vehicle positioning and platooning technology based on IoV,to improve the positioning accuracy of neighboring vehicles,and the stability and safety of vehicle platoons.Firstly,we study the cooperative neighboring vehicle positioning method based on particle filtering and vehicle-to-vehicle(V2V)communication.Specifically,the measuring vehicle can use sensors to measure the driving status of neighboring vehicles,and use wireless communication to receive the self-status sampling information sent by neighboring vehicles.Considering that the status sampling time between vehicles is asynchronous,we formulate the neighboring vehicle positioning problem to a multi-sensor asynchronous data fusion problem.We design an asynchronous data fusion method based on particle filtering,which can filter and fuse asynchronous neighboring vehicles' position measurement in real time,and improve the positioning accuracy of neighboring vehicles.We use SUMO and NS-3 to simulate the vehicle trajectory and communication,respectively,and conduct some experiments to verify the effectiveness of our proposed cooperative neighboring vehicle positioning method.Secondly,we study the joint system design of vehicle platoon communication and control.Considering the objectives of platoon control,we design a two-stage platoon communication scheme,in which the platoon leader's information dissemination is separated from following vehicles.We use relays to forward the platoon leader's information to extend its communication range,and propose a relay selection algorithm.On the other hand,we design an adaptive distributed model predictive control(DMPC)mechanism for platoon vehicles,which can automatically adjust their control parameters based on the platoon communication results.We also add the safe distance restriction in the control mechanism and propose platoon control schemes when a vehicle is in abnormal states,to further improve the platoon safety.Finally,we study the control and management problems of multiple platoons in a dedicated autonomous driving lane.Based on the research with single lane and single platoon,we propose the control mechanism of multiple platoons,which is actually the control mechanism of the platoon leader.Considering the scenarios where vehicles join/leave a platoon,we design communication and control coordination schemes of multiple platoons and vehicles,and devise corresponding flowcharts.The simulation results illustrate the effectiveness of our proposed multiple platoon control and management scheme.