Simulation Model And Assessment Method Of Congestion Pricing Effects On Urban Traffic

With a rapid increase of urban motorization level,traffic congestion has become one of the most common traffic issues and many traffic demand management measures have been applied in practice to relieve urban traffic congestion.Congestion pricing is a measure of traffic demand management based on economic regulation,it has already been applied in many foreign cities and has gained a good effect.However,this measure has not officially been applied in China.On the one hand,the implementation conditions of congestion pricing are not yet mature,on the other hand,there lacks an effective method to assess the effects of the measure.In this paper,a multi-agent simulation model based on activity-travel is established to reflect the spatial and temporal distribution characteristics of residents after analyzing the impact of congestion pricing on traffic activities.The effects of congestion pricing are then simulated and assessed using this model.Since the multi-agent simulation model can reflect the individuals' activity-travel behavior which is exactly the impacts of congestion pricing,this model can better reflect the effect of congestion pricing policy.In order to manifest the policy in the multi-agent model,some parameters need to be calibrated in the model.After analyzing the impact of congestion pricing on traffic activities,travel mode choice is selected to be the key research object.The utility function is first selected from the actual survey data and then a MNL model is established to analysis the preference of car or transit travel choice under the influence of congestion pricing policy which provides a theoretical basis for the calibration of congestion pricing in the following model.While establishing the multi-agent model,activity-travel survey data of Jiangning district of Nanjing city is used.Typical individual activity travel patterns are extracted through summarizing activity travel time and location information.Different agents are then established according to activity travel patterns and a simulation model of travel time and space distribution is subsequently constructed based on multi-agent.Finally,based on the impacts of congestion pricing on travel mode travel,parameters are calibrated in the multi-agent model.By comparing with the change of residents' activity before and after the congestion pricing implementation,the evaluation of the implementation of congestion pricing policy is realized.The provided multi-agent based simulation model can effectively evaluate the impacts of congestion pricing and other TDM measures on urban macroscopic traffic activities.This model also provides a quantitative analysis tool for formulating urban transportation policy and will help to further promote research results in practice.