Study On Emergency Dispatching Of Rail Transit Abnormal Feeder Bus Based On Cumulative Prospect Theory

Rail transit system is considered as an important means to promote economic development,optimize urban spatial layout,change travel mode and improve travel quality due to its advantages in speed,traffic volume,safety and stability.It has gradually become the main travel mode.While bearing the huge passenger flow,rail transit is prone to train delay and service interruption due to equipment failure,malicious damage,bad weather,disaster and other disturbances.These lead to panic,congestion and detention of passengers,as well as losses and negative effects.According to the requirements of transportation capacity resource allocation under abnormal conditions and combined with the characteristics of abnormal scenes,to make rational use of flexible road traffic for emergency response is the key to maintaining the normal operation of the network.Therefore,it is urgent and necessary to deeply study the abnormal characteristics and potential risks of rail transit,scientifically describe the travel behavior of abnormal passengers,reasonably describe the travel time of passengers under abnormal conditions,and establish a feeder bus dispatching model to ensure the normal operation of the network and improve the network security and emergency response ability.Through literature review,data analysis,questionnaire survey,model construction and other technical means,the feeder bus scheduling model considering abnormal classification and passenger travel behavior is established in this paper.In order to provide theoretical support for abnormal multi-mode collaborative optimal scheduling of rail transit.There are three core aspects: rail transit abnormal risk classification and decision support,abnormal passenger travel behavior model and feeder bus scheduling model in this paper.1.After analyzing the abnormal interference,classification and impact of existing rail transit,the abnormal events that their consequences is less than the existing regulations are classified as the basic condition for studying the optimization of feeder bus dispatching.With the help of historical data,the characteristics of various abnormal states are analyzed,and their distribution law and influence intensity can be obtained.There are ten parameters such as affected passenger flow,interruption duration and number of affected trains.The cluster analysis and Bayesian network are used for risk classification and decision support by the ten indexes.The emergency connection strategy is formulated accordingly to provide the basis for emergency response conditions.2.Considering the incomplete rationality of passengers,cumulative prospect theory is proposed to describe the travel behavior under abnormal state.There are four indicators,time,cost,comfort and convenience to comprehensively quantify the cumulative prospect of combined travel mode under abnormal conditions and calculate the division rate.The questionnaire survey is designed to describe passenger travel behavior under abnormal conditions.The reference point and weight vector is calibrated in the model.Poisson distribution is used to reasonably describe the dependence of reference point.Although the calculated value of the model is small for the mode with fixed loss and high uncertainty,it can fit the division rate of emergency bus well and provide a basis for reasonably calculating the emergency connection demand.3.Combined with the results of abnormal risk classification and the travel behavior under the abnormal states,a feeder bus dispatching model is proposed for single line and multi-line abnormal scenarios to generate an emergency response scheme.By introducing station stop,cross station,direct,section and comprehensive operation modes,a nonlinear programming model is established.The stop scheme,number of vehicles and departure interval are taken as decision variables and the minimum total travel time of passengers is taken as the goal.The vehicle resources,connection demand,connection time,full load rate and physical constraints are consider as multiple constraints.The discrete particle swarm optimization algorithm is established to solve the model.Through the case study,the feasibility of the feeder bus scheduling model considering the abnormal classification and passenger travel behavior is verified.