Abstract
The population of Beijing has already come to its loading capacity. The China central government plans to build an ideal city named Xiong’an nearby Beijing. The city is expected to work as a carrying hub for noncapital functions of Beijing. The central government does not rush to build before a deliberated urban planning is accomplished. For sustainable development, a difficulty faced by urban planners is that the maximum number of people can be migrated from Beijing to Xiong’an with constraint on level of transport service. This paper developed a specialized bilevel programming model where the upper level is to ensure a predetermined transport service level regarding to population migration, while the lower level is feedback equilibrium between trip generation and traffic assignment. To be more specific, trip is generated by the gravity model, and traffic is assigned by the user equilibrium model. It is well known that the bilevel programming problem is tough and challenging. A try-and-error algorithm is designed for the upper-level model, and a method of successive average (MSA) is developed for the lower-level model. The effectiveness of the model and algorithm is validated by an experimental study using the current transport network between Beijing and Xiong’an. It shows that the methods can be very useful to identify the maximum population migration subject to level of transport service.
Highlights
Beijing is a well-known metropolitan city that is suffering from high housing price, traffic congestion, urban sprawl, air pollution, and water resource shortage
Travel time and traffic flows are determined endogenously in the lower level model. e travel demand is generated based on the initial travel time and assigned to the transport network by user equilibrium. en, the new travel time is produced by the shortest path algorithm, i.e., Dijkstra’s algorithm. e method of successive average
More and more people live in the metropolitan area, which causes a lot of problems including traffic congestion and air pollution, as well as social problems
Summary
Beijing is a well-known metropolitan city that is suffering from high housing price, traffic congestion, urban sprawl, air pollution, and water resource shortage. Yim et al [5] formulated a bilevel model where the upper level minimizes the probability of overloading links regarding land use developments and transport network enhancement, while the lower level is a combined trip distribution and traffic assignment model. Levi et al [11] formulated a multiobjective bilevel programming model for urban planning where the upper level is monetary cost minimization and travel time minimization with regard to land use layout, while the lower level is a combined trip distribution, mode split, and traffic assignment problem. A specialized bilevel model is developed where the upper level is to ensure the level of transport service is not worse than a predetermined one with constraints on population migration, while the lower level model is a feedback procedure between trip generation and traffic assignment.
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