Effect of Bus Stop Walking Time on Elderly's Bus Choice

被引:0
作者
Liu J.-R. [1 ]
Hao X.-N. [1 ]
机构
[1] School of Civil Engineering and Transportation, South China University of Technology, Guangzhou
来源
Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology | 2020年 / 20卷 / 01期
基金
中国国家自然科学基金;
关键词
Demographic characteristics; Elderly; Psychological factor; Random parameters Logit model; Urban traffic; Walking time;
D O I
10.16097/j.cnki.1009-6744.2020.01.019
中图分类号
学科分类号
摘要
Public transportation is an important way for the elderly to travel, and walking time to the station is an important part of the quality of public transport services. Taking walking time from the origin to the bus station, and based on the stated preference data, this paper analyzed the impact of walking time on the elderly's bus choice behavior with the random parameters Logit model. Through analysis, it was found that the random parameters Logit model fitting the data much better than the multinomial Logit model. The parameter of in-vehicle time was non-random, while the parameter of walking time was random. Furthermore, the elderly's demographic characteristics including gender, age, motorcar ownership, education, monthly income (greater than 3 000 yuan or not), had a significant impact on the parameter of walking time. So did the latent psychological factors, such as psychological factors towards physical activity, perceived physical functioning. Copyright © 2020 by Science Press.
引用
收藏
页码:124 / 129
页数:5
相关论文
共 13 条
  • [1] Zhou P., Grady S.C., Chen G., How the built environment affects change in older people's physical activity: A mixed-methods approach using longitudinal health survey data in urban China, Social Science & Medicine, 192, pp. 74-84, (2017)
  • [2] Kim J., Lee B., More than travel time: New accessibility index capturing the connectivity of transit services, Journal of Transport Geography, 78, pp. 8-18, (2019)
  • [3] Zhang Z., Feng X.J., Guo Y.D., Research on the departure time choices of the elders' daily travels, Journal of Transportation Systems Engineering and Information Technology, 11, pp. 109-114, (2011)
  • [4] Barnett D.W., Barnett A., Nathan A., Et al., Built environmental correlates of older adults' total physical activity and walking: A systematic review and meta-analysis, International Journal of Behavioral Nutrition and Physical Activity, 14, 1, pp. 1-24, (2017)
  • [5] Wong R.C.P., Szeto W.Y., Yang L., Et al., Public transport policy measures for improving elderly mobility, Transport Policy, 63, pp. 73-79, (2018)
  • [6] Feng J.X., Yang Z.S., Factors influencing travel behavior of urban elderly people in Nanjing, Progress in Geography, 34, 12, pp. 1598-1608, (2015)
  • [7] Das S., Pandit D., Importance of user perception in evaluating level of service for bus transit for a developing country like India: A review, Transport Reviews, 33, 4, pp. 402-420, (2013)
  • [8] Bhat C.R., An endogenous segmentation mode choice model with an application to intercity travel, Transportation Science, 31, 1, pp. 34-48, (1997)
  • [9] Mcfadden D., Train K., Mixed MNL models for discrete response, Journal of Applied Econometrics, 15, 5, pp. 447-470, (2000)
  • [10] Mertens L., Van Dyck D., Deforche B., Et al., Individual, social, and physical environmental factors related to changes in walking and cycling for transport among older adults: A longitudinal study, Health Place, 55, pp. 120-127, (2019)