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Mathematical Problems in Engineering
Volume 2013 (2013), Article ID 620973, 9 pages
Research Article

Analysis on Residents’ Travel Activity Pattern in Historic Urban Areas: A Case Study of Historic Urban Area of Yangzhou, China

1Department of Transportation Engineering, Nanjing University of Science and Technology, 200 Xiaolingwei, Nanjing 210094, China
2School of Transportation, Southeast University, 2 Sipailou, Nanjing 210096, China

Received 12 September 2013; Revised 4 November 2013; Accepted 21 November 2013

Academic Editor: Wuhong Wang

Copyright © 2013 Mao Ye et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Travel behaviors and activity patterns in the historic urban area of a city are expected to be different from the overall situations in the city area. The primary objective of this study is to analyze the residents’ travel activity patterns in historic urban area. Based on survey data conducted in the historic urban area of Yangzhou, the travel activities of local residents in a whole day were classified into five types of patterns. The multinomial logit (MNL) model was developed to evaluate the impacts of explanatory variables on the choices of activity patterns. The results showed that the choice of activity pattern was significantly impacted by five contributing factors including the gender, age, occupation, car ownership, and number of electric bikes in household. The other variables, which were the family population, preschoolers, number of conventional bikes in household, motorcycle ownership, and income, were found to be not significantly related to the choice of activities. The results of this study from historic urban area were compared to findings of previous studies from overall urban area. The comparison showed that the impacts of factors on activity pattern in the historic urban area were different from those in the overall area. Findings of this study provide important suggestions for the policy makings to improve the traffic situations in historic urban areas of cities.