Study On Departure Time Choice Behavior In Commuting With Stochastic Bottleneck Capacity

The imbalance and instability of traffic supply and demand are the causes of traffic congestion.It is difficult to solve the problem by simply replenishing the supply,and it will even stimulate more travel demand.On the other hand,the supply side is easy to be affected by the external environment,and the demand side has strong time characteristics,so it is almost impossible for both sides to maintain a stable state for a long time.In this case,it is necessary to adopt the method of dredging to relieve congestion.To fully understand the behavior characteristics of travelers' travel choices in the face of uncertain environment is the premise of effective counseling policies.Firstly,based on the framework of Vickrey's bottleneck model,this paper designed and carried out departure time choice experiment for different parameter settings and scenarios with stochastic capacity as the experimental core.By setting up two kinds of information feedback modes,the influence of feedback personal information and general information on traveler's choice behavior was tested.It is found that there is an obvious linear relationship between the mean cost and the standard deviation of the cost at departure times,and the fitting slope is positive.This indicates that travelers tend to minimize the travel cost budget when choosing the departure time in the face of uncertain capacity,and the group behaves risk preferring.In terms of individual behavior,it is found that factors such as historical capacity and historical arrival time will cause the change of individual strategy.Secondly,based on the behavior characteristics obtained from experiments,this paper proposes a learning model by applying the theory of reinforcement learning.In the simulation process of this model,the agent's propensity for each departure time is determined by the travel cost budget,while for the departure time that has never been selected,the propensity is calculated by linear interpolation.The simulation results show that the model can describe the selection process of commuters in an uncertain environment and reproduce the main experimental findings well.Finally,this paper centers on the single evening rush hour,and divides into five possible travel patterns under the user equilibrium state based on travel cost budget.The departure rate,critical departure time and boundary conditions of each pattern are deduced theoretically,and the analytical expressions are given.Furthermore,the rationality of these patterns in practice is discussed in the paper.On the basis of theoretical research,numerical examples are used to intuitively demonstrate the influence of risk preference coefficient,ratio of degraded capacity and capacity reduction probability on the change of travel mode,the duration of peek hour,travel cost budget,mean cost and standard deviation of the cost.