Research On Allowable Traffic Capacity Of Road Sections Considering Braking Response Time

The transportation industry in China is booming,and traditional transportation methods are gradually shifting towards intelligent transportation.Connected vehicles and autonomous vehicles have emerged,providing new research directions for solving traffic problems.However,traffic accidents and congestion have not yet been effectively resolved.This thesis analyzes the shortcomings of traditional capacity calculation formulas,considers the impact of operators,vehicle performance,and connectivity,considers the contradiction between safety and smoothness,and proposes the concept of allowable capacity.The aim is to explain the uncertainty of capacity and the risk of road resource allocation through risk degree.Firstly,this thesis analyzes the shortcomings of traditional capacity expression,considers the impact of autonomous driving operators(vehicle terminals)and vehicle braking performance(hydraulic and pneumatic braking)on capacity,and takes into account the bias of capacity values.The concept of allowable capacity is introduced to characterize the error between estimated capacity and overall parameters based on risk.Analyze the influencing factors of traffic capacity from four aspects: operators,vehicles,roads,and technological level,preliminarily identify their influencing factors,and screen the influencing factors through the DEMATEL-ISM method to determine the set of influencing factors for road section traffic capacity.Secondly,convert the set of factors that affect the traffic capacity of the selected road section into a parameter set,and calibrate its parameters to determine their value range.By using the AHP method to assign weights to feature parameters that affect drivers,the range of driver response time parameters is obtained.By referring to a large number of literature,national industry standards,and consulting relevant experts,the response time parameters of the vehicle terminal were obtained,and vehicle and road related parameters were also calibrated.Next,a traffic flow average braking response time model is constructed based on the characteristics of the Internet of Vehicles.Applicable scenarios for determining the average braking response time of traffic flow by analyzing the composition of traffic flow: non vehicular connected traffic flow,vehicular connected traffic flow,and partial vehicular connected traffic flow;Establish an average braking response time model for non vehicular connected traffic flow,an average braking response time model for vehicular connected traffic flow,and an average braking response time model for some vehicular connected traffic flow based on the vehicle information interaction mode and traffic flow information interaction mode,and conduct parameter sensitivity analysis on them.Finally,by analyzing the relationship between the average braking response time and allowable risk of traffic flow through identifiable workshop time intervals and vehicle arrival patterns,the threshold range of the average braking response time of traffic flow under different allowable risks is obtained for three traffic flow states: free flow,interference flow,and tracking flow;Considering the absence of rear end collisions,a permissible capacity model based on the average braking response time of traffic flow is constructed,and the impact range of capacity parameters on it is analyzed and compared with standard capacity.