Research On Dynamic Traffic Organization Model For Special Events

During special events there are increased traffic demand and traffic flow around the stadium road network in a short period, resulting in traffic congestion and parking shortage. The temporary traffic problem can't be solved by constructing roads and parking facilities. It is effective to develop reasonable traffic organization and management plan to relieve the traffic supply and demand conflict by using other roads and parking resources. How to develop reasonable and efficient traffic organization and management plan according to demand and supply is worth studying. In this dissertation, interaction between traffic planners and participators is considered when we develop traffic organization and management optimization model for special events. An optimization approach based on bi-level programming system was proposed. It was applied in parking fare optimization problem, parking guidance information optimization problem and evacuation network one-way optimization problems for special events. The main study works in this dissertation are as following:(1) Bi-level programming model system framework as well as its solving algorithm are researched in special events traffic organization and management. To avoid Braess strange phenomenon in traffic network organization and management process, the bi-level programming of traffic network design optimization problem is used for traffic organization and management optimization. In the model, traffic planners and travelers of optimization problems are considered as the upper model and the lower model decision-makers separately. The game process of planners and travelers is described by bi-level programming model. Quasi-dynamic traffic assignment model and quasi-dynamic stochastic user equilibrium model are used respectively to describe traveler's route choice behavior for different optimization problems under dynamic demand circumstance. Because of Non-linear and solving difficulty characteristics of bi-level programming, advanced Particle Swarm Optimization (PSO) and Quantum Evolutionary Algorithm (QEA) are applied for upper level problem solving to get a better solution. The research has been supported by the National Basic Research Program of China (No. 2006CB705505) and National Basic Research Program of China (No.2005CB724205) (2) Special Events parking fare optimization model is established and parking demand for different parking lots is control by parking fare. Based on special events Parking-Ride/Walk multi-trip characteristics analysis, traffic network conversion is implemented. The after-parking links are converted to attractiveness of parking lot, because the travel prices of these links are relatively stable. In this way, the original parking choice problem can be described by trip distribution/traffic assignment model. Based on network conversion, Logit-based effectiveness model is applied to describe the behavior of travel and parking choice. The effectiveness model takes into account driving time, parking fees, bus fees, walk costs and other factors. This model is the lower level model of bi-level programming model. By Analysis of special events total travel time object, parking fares and parking capacity constraints, the upper level model is established. The proposed parking fare optimization model is solved by Discrete Particle Swarm Optimization (DPSO) and lower level assignment model is solved by Convex Combination Method (CCM).(3) Special events Parking Guidance Information (PGI) optimization model is established. Based on the the parking fare plan research, we studied the incomplemention guidance information optimization method, which aims to make system travel-time minimum. By considering parking lots as dummy links, the original traffic network with parking lots can be converted into a new expanded common network. In this way, the shortest path algorithm and traffic assignment can implement effectively in the network. The reaction rate of guidance information is used to describe traveler's response of information, which is the basis of parking time prediction. The stochastic user equilibrium model is used to describe the route choice behavior and as the lower level. Bi-level programming-based PGI optimization model was proposed and the upper level is resolved by QEA.(4) Special events temporary one-way optimization model is developed. Based on the asymmetric traffic demand characteristics of special events evacuation, the traffic network temporary one-way is configured by optimization model. The route choice behavior under dynamic demand circumstance is described using Quasi-Dynamic User Optimal traffic assignment model, which is also the lower model of bi-level programming model. Based on the object and constraints of background traffic and evacuation traffic, the network one-way Mathematic Programming is established, which is also the upper level model of the bi-level programming model. An algorithm based on DPSO and Frank-Wolf (FW) is designed to solve the proposed model.(5) The special events traffic organization and management Decision Support System is developed. Based on system needs analysis and module division, the database as well as data table needed for the system are designed. Special events traffic Organization and Management Decision Support System by Visual C#. NET and ArcGIS Engine. The parking fare optimization model, PGI optimization model and network one-way optimization model are implemented in corresponding module.