Empirical And Simulation Research On Urban Driving Restriction Policy

In the process of urbanization,urban residents are making more trips and relying more on motorized modes if there is no extra costs.Rapid motorization has lead to serious congestion problems.More and more cities began to rely on driving restrictions to alleviate traffic congestion.Due to the driving restriction policy,urban traffic system will be affected in both individual and aggregated level.At the micro-level,travelers will be influenced due to the restriction policy,and thus they will build different attitudes toward this policy and take the corresponding actions to cope with it.Traveler's micro behavior aggregated to form the macro states,and thus influence the traffic conditions.Travelers choose a travel mode based on the traffic conditions they perceived,and lead to a long-term impacts on macro transportation systems.Using empirical research and multi-agent modeling approach,and taking Tianjin as an example,this dissertation analyzed the short and long term effects of driving restriction policy at both micro and macro-level.The main contents of this dissertation are summarized as below:In terms of the macro-level short-term impacts of the urban traffic system,a linear regression method was used to analyze the traffic flow changes under different restriction schemes during certain hours on both working days and non-working days.Results demonstrate that the implement of driving restriction policy can reduce the traffic volume on working days,and the reduction extent is related to the restriction level.However,there is an increase in the traffic volume on non-working days with the implement of restriction policy.In terms of the micro-level short-term impacts of the urban traffic system,a questionnaire survey was conducted to capture the influence factors of the public's attitudes toward the trail number restriction policy and its subsequent influence on the coping actions.Results demonstrate that public's attitudes toward the restriction policy are affected by anticipated results,social status,responsibility attribution,problem sensing and fairness.There was an association between the acceptance degree of restriction policy and the coping behaviors.A low acceptance degree of the policy will lead to a series of problems.Some of the car owners who preferred to take public transit before the restriction policy switch to private automobiles.Moreover,the private car travelers are more likely to break the restriction rule.In terms of the micro-level long-term impacts of the urban traffic system,a logistic model was used to analyze the data obtained from the questionnaire survey.Results demonstrate that the driving restriction policy positively affect the travel mode usage tendency for both private automobiles and public transit.Among them,public transit usage tendency is influenced by the travel experience mostly;private car usage tendency remains unchanged after the implement of restriction policy.Moreover,the effect of the driving restriction policy will diminish gradually with the growing of the total amount of private cars.Based on the above observations,an multi-agent modeling method is adopted to simulate the traveler mode choice behavior under the driving restriction policy,and analyzed the macro-level long-term traffic conditions that are likely to appear.On this basic,we analyzed the effects of the driving restriction policy and different public transport improvement policies.Results demonstrate: under the driving restriction policy,among all the public transport improvement schemes,measures that aimed at improve the service quality(e.g.increase the departure frequency)would be more effective;whereas,reduce the price of public transport has little effect.Based on the macro and microscopic level studies of the driving restriction policy,we analyzed the efficiency of the policy and give the policy advices for urban transportation management.Finally,prospects for further studies are presented.