Real-time Traffic Information Acquisition And Traffic Road Network Load Balance Based On Vehicular Ad Hod Networks

With the rapid increasing of privacy vehicles' volume,the burden of traffic load in the road network becomes a rigorous challenge.Intelligent Transportation System(ITS)is an important technology to realize the real-time transportation management,which uses vehicles,traffic lights,road-side unit,and traffic management server to achieve information communication,and traffic control in complex traffic road network.However,how to realize the real-time traffic information acquisition,how to predict the traffic condition,and balance the traffic load based on real-time traffic information are still main challenges in this field.The dissertation does the research on the communication performance,the traffic condition prediction,the dynamic path planning and the traffic load balance,which involve the theories of wireless communication technology in Vanets,back-pressure,real-time path planning,and interior point method.The goal of the dissertaton is discussing the optimal balance dispatching policy in the dynamic vehicular motion of the ITS and proposes the reasonable and efficient traffic balance optimal algorithm on the view of global road network.The main contributions of the dissertation are as follows:(1)Firstly,the dissertation studies the data delivery delay of V2 V communication in VANETs.Cosidering nodes' topology in vehicular dynamic motion and the signal operation of traffic lights at road segments,the dissertation proposes a V2 V communication data delivery mechanism based on bi-directional roadways at road intersections.The mechanism selects the best position of relay node,which is based on the different cases of signal operations at road intersection.The mechanism outputs the optimal routing results to decrease the data delivery delay.The dissertation analyses the V2 V communication data delivery delay in both theory and evaluation,and our proposed mechanism outperforms to other traditional data delivery mechanisms in data delivery delay.(2)Considering the vehicular density's influence on V2 R communication performance,and the problem of redundancy and effectiveness on R2 R communication,the dissertation presents a novel V2 R communication mechanism which considers the density of communication node and converge area of RSUs,as well as a real-time RSU information sharing mechanism to improve the effectiveness of real-time information.The proposed V2 R communication data delivery mechanism can guarantee the efficiency of data delivery in different communication node density,and the real-time R2 R information sharing mechanism reduces the information redundancy among RSUs.We discuss the topic in both theory and evaluation.(3)Regarding the traffic flow prediction problem,the dissertation analyzes the inherent property of traffic flow and detect the singularities by using the Wavelet Transform.The next singularity of observation that is predicted via pattern matching provides the basis of dynamic unequal division of time slots.And then the dissertation gives a traffic flow prediction method based on the Vasicek model.The theory and evaluation results can both prove that the proposed dynamic traffic flow prediction algorithm can realize a trade-off between prediction accuracy and computing cost.(4)Regading the individual vehicle's dynamic path planning problem,the dissertation proposes a real-time travel time estimation model to improve the accuracy,which considers the traffic density,traffic lights' signal and road intersections.Then the dissertation uses the real-time travel time estimation as the metric to decide the optimal dynamic path planning results during dynamic time slots.Moreover,the dissertation proposes the optimal dispatch policy for the backlogged vehicles to the downstream road segments,which depends on the back-pressure theory and drift-plus-penalty model.The real-time path planning algorithm(RPP)is used for outputting the optimal number of dispatched vehicles.Based on the discussion on both theory and evaluation,the proposed RPP algorithm can reduce the individual vehicle's traveling time to destination efficiently and can realize the rapid response to the potential traffic congestion on the downstream road segments.(5)In order to solve the traffic congestion caused by traffic load imbalance,the dissertation proposes a traffic load balance optimization model for the global road network depending on vehicles' travelling time and the drivers' altruism selection for the path.The dynamic interior point method(DIPM)is used for calculating the optimal results,which is the optimal number of vehicles for each road segment in different time slots.Both theory and evaluation prove that our proposed algorithm can be convergent to the optimal results within finite iterations.The algorithm reduces the individual vehicle's travel time,which realizes the traffic load balance in global road network.Finally,we conclude our research on the information acquisition problem and the traffic road network load balance problem in VANETs.Some of the disadvantages of current research is analysed and some improvements of problems in this field which needs further research is discussed briefly.