Research On Mixed Capacity Analysis Of Automated-Human Driven Vehicles Based On Markov Chain

With the development of vehicle technology,there will be more and more autonomous vehicles on the street in the future.Some autonomous vehicles have begun to drive on the road.It is predicted that the market penetration rate of autonomous vehicles will continue to improve in the coming decades,which will have a huge impact on the existing road traffic.Therefore,it is necessary to study the mixed capacity of autonomous and human-driven vehicles.Aiming at the traffic capacity characteristics of autonomous and human-driven vehicles based on the headway capacity analysis formula,the traffic capacity models of single lane and two lanes in mixed traffic environment are established respectively.Firstly,the Markov chain model is added to the capacity formula,and a single-lane autonomous and human-driven mixed capacity model is established.The three factors affecting the mixed capacity,i.e.the headway,the penetration rate of the autonomous vehicles and the randomness of the arrangement distribution,are all taken into account in the model.Moreover,due to the difficulty in calculating the true value of mixed capacity,an estimate value is proposed to replace the true value,and the rationality of the mixed Markov chain capacity model and the estimated value is proved.In previous studies,it is often believed that with the increase of the penetration rate of autonomous vehicles,the traffic capacity will increase;under the penetration rate of autonomous vehicles,the tighter the arrangement of autonomous vehicles,the greater the traffic capacity.In order to verify these statements,the traffic capacity model is first analyzed mathematically.The results show that only when the headway values of several kinds of vehicles in mixed traffic satisfy certain numerical relationships can the capacity be satisfied,and the capacity will be increased with the increase of the proportion of automatic driving or the tighter the arrangement of automatic driving vehicles.The conclusions are validated by MATLAB,and the changing trend of single lane capacity with the proportion and arrangement of different automatic driving vehicles under various headway time-distance numerical relationships is obtained.Finally,the two-lane traffic capacity is analyzed.Because the two-lane traffic involves the lane management strategy,the optimal two-lane traffic management strategy is determined with the goal of maximizing the two-lane traffic capacity.The changing trend of the two-lane traffic capacity with the the penetration rate of autonomous vehicles,under different headway time-distance numerical relations and different vehicle arrangement is analyzed,and the optimal management strategy under various conditions is determined.