Research On Key Technologies Of DASS Service Generation Based On Dynamic QoS And Demand Drive In IOV

With the continuous increase of car ownership in China,the limited road resources and the continuous growth of vehicles constitute an irreconcilable contradiction.It has led to a series of problems such as frequent traffic accidents and increased traffic congestion.In this context,the Driving Active Service System(DASS)emerged as the times require.DASS provides real-time,active and efficient services for vehicle driving in the Internet of Vehicles(IV)environment by collecting vehicle driving information and effectively automatic perception and identification of driving services through information fusion.Based on the existing DASS,the paper relies on China Postdoctoral Science Fund: Vehicle Active Service Mechanism Analysis and System Modeling for Vehicle Network(Project No.2016M600375),analyzes the shortcomings of existing systems in service selection and service composition,and proposes dynamics based on dynamics.Quality of Service(QoS)and subjective and objective empowerment evaluation methods for driving active service selection and service demand-driven service composition framework.It solves the problem that the volatility of QoS parameter values and the irrational allocation of QoS parameters are not considered in the DASS service selection,and the dynamic change of the service requirements is difficult to grasp in the service composition.The paper mainly completed the following four parts of research work:(1)Systematic analysis the research and development status of vehicle networking technology,service selection and combination technology and DASS.The basic principles of DASS,service classification and related technologies are elaborated,and the feasibility of DASS is analyzed from the perspective of technology development and application promotion.(2)Aiming at the unreasonable QoS fluctuation and QoS parameter weight distribution in DASS dynamic traffic network environment,a DASS selection method based on dynamic QoS and subjective and objective weighted evaluation method is proposed.By establishing the DASS-QoS interval model to represent the QoS dynamics,the QoS objective weights and the subjective preferences of the driving users are used to obtain the QoS parameter comprehensive weights.Finally,the two are combined with the guidance service selection.Taking the transportation vehicle dispatching service as an example to verify the above service selection method,the results show that the service selected by this method reduces the total scheduled transportation time by 35.73% and the total cost by 25.01%.(3)In view of the difficulty in grasping the dynamic changes of service demand in the DASS service portfolio,a service composition framework and algorithm based on service demand are designed.Through the real-time perception of changes in the service environment and service requirements,the DASS service is automatically combined for users to use.At the same time,the driving user demand perception algorithm and the driving service matching algorithm are established,and the flow of the DASS service combination is described.The above service combination method is verified by taking the tractor and trailer matching service in the hanging transportation as an example.The results show that the service combined with this method can improve the comprehensive service quality by 32% and 30% before and after the service demand changes.(4)Based on PreScan-Matlab/Simulink and Logitech G29,the semi-physical driver-in-the-loop DASS simulation verification platform,taking real-time dynamic path planning as an example,the key technologies of DASS service generation based on dynamic QoS and demand-driven are comprehensively tested and verified.The simulation results show that the path planning service generated by this method can save 9% of the travel time on average,and can save up to 15% of the travel time.