Simulating and analyzing the effect on travel behavior of residential relocation and corresponding traffic demand management strategies

Triggered by rapid urban expansion and fast population growth, a progressive residential relocation has occurred in most cities and its impacts on travel behavior have been confirmed in many studies. However, none has evaluated the effects of travel management strategies that relieves the side effects caused by this relocation. To this end, a multi-agent-based simulation model is proposed to assess the impacts of residential relocation on travel behavior and urban transportation in China. Based on the data in Tongling, China, the simulation on six scenarios is conducted to test how the residents in the urban center and suburbs are affected by different strategies, such as increased land diversity in suburbs, lowered growth in private car ownership and improved public transit accessibility. The results indicate that more daily trips would be lengthened and tend to be motorized by this residential relocation. The scenario test shows that compared to other strategies, policies that aims to reduce travel demand and trip distances after residential relocation have a better performance in traffic improvement.