Research On Information Feedback Strategy Of Dual-channel System With Two-lane

With the increase of the number of cars,the traffic problem is becoming more and more prominent.How to make full use of existing traffic resources to improve road utilization through scientific management and control has become a key issue need to solve that affects people’s daily life and restricts economic development.In this context,the intelligent transportation system as a good medicine to solution the above problems,go into the people’s vision.As the core part of the intelligent transportation system,the traffic flow induction strategy based on information feedback has been paid more and more attention by the majority of scholars.In this paper,a two-channel network model with two lanes was established,and the influence of average speed feedback strategy,vehicle number feedback strategy,randomness feedback strategy,traffic flow feedback strategy and smooth flow index feedback strategy on the traffic flow was studied by numerical simulation.The main work of this paper was as follows:Firstly,an improved dual-channel road network model was established-a Dual-channel model with two lanes.The existing Dual-channel model was assumed that the width of the alternative path is the same,which neglected the situation that the alternative path was inconsistent,so there were some limitations.In this paper,taking into account the complexity of the actual road conditions,the Dual-channel model that a candidate path is the single lane,the other is two lanes was established.And the single-lane path used NS model,the two-lane path used the improved two-lane multi-value CA model.At the same time,the simulation results show that the traffic conditions of the road network were deteriorated and the road traffic capacity was urgent to be improved when the probability of entering the vehicle was large.In this paper,the randomness concept was introduced,and the random degree feedback strategy was compared with the average speed feedback strategy and vehicle feedback strategy.The simulation results show that under the random degree feedback strategy,the average speed of the two paths in the single exit road network model had good balance,the number of vehicles and the traffic flow have good stability.The distribution of the vehicles on the two paths in the double exit road network model was balanced,and the vehicles on the road run orderly.When the proportion of dynamic vehicles was large,regardless of which road network model,the average speed feedback strategy and the number of vehicles feedback strategy were invalid,and the random degree feedback strategy had obvious advantages.Then,the smoothing index feedback strategy that merges the average speed and the number of vehicles was established.The weight coefficient of the smoothing index feedback strategy was determined,that applied to the dual-channel model with two-lane,and the operation of traffic in the single exit road network model with different dynamic vehicle ratio was simulated.The simulation results show that when the proportion of dynamic vehicles was small,the average speed and the number of vehicles on the two paths had much different,and the vehicle drives slowly.When the proportion of dynamic vehicles was large,the running status of the two paths was unstable.While the dynamic car ratio of 0.6 or so,the smoothing index feedback strategy compared with the average speed feedback strategy,the number of vehicles feedback strategy,the random degree feedback strategy and the traffic flow feedback strategy was better.When the dynamic vehicle ratio is 0.4 to 0.7,the smoothing index feedback strategy was superior.Finally,this paper summarized the work and innovation of the whole paper,and prospected the future research direction.