Papers by Keyword: Travel Demand

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Authors: En Jian Yao, Qi Rong Yang, Yong Sheng Zhang, Hong Na Dai
Abstract: High speed train (HST) has received plenty of attention due to the characteristics of safety, quickness, convenience and better service in China over recent years. With consideration of rapid development of HST and intense competition between HST and other transport modes, it is essential to estimate the travel demand for HST. In this research, a disaggregate logit model is applied to estimate the travel demand for high-speed train based on stated preference data. Considering the independence of irrelevant alternatives attribute, a nested structure is chosen to these alternatives. Besides, both the service attributes of transport mode and passengers' attributes are taken into account when establishes model. The results obtained confirm that HST occupies a significant position in modes conpetition and have an important impact on air in middle and long distance market.
Authors: Ning Ma, Li Na Xu, Fei Fei Xie, Xue Mei Li
Abstract: In the background of the development of global low-carbon economy, to blossom the low-carbon transport is necessary for every country. Railway is recognized as a green transport with low-power consumption, less pollution, which is one of the most important infrastructures developed actively around the world. With the approaching era of high-speed railway, railway passenger demand has been paid much more attention. As passengers with different trip purposes are influenced by different factors when choosing means of transport, this paper will classify passengers by trip purposes and find the main influential factors according to different types of passengers with the aid of rough set. Then put forward initiatives aimed at improving passenger satisfaction, and enhance the positive attitude of passengers towards rail transportation.
Authors: Jun Chen, Xiao Hua Li, Lan Ma
Abstract: Traditional transit travel information is acquired by Trip Sample Survey which has some disadvantages including high cost and short data lifecycle. This paper researched transit travel demand analysis method using Advanced Public Transportation Systems (APTS) data. The study collected APTS data of Nanning City in China and established APTS multi-source data analysis platform applying data warehouse technology. Based on key problems research, the paper presented the analysis procedure and content. Then, this study proposed the core algorithms of the method which are determinations of boarding bus stops, alighting bus stops and transfer bus stops of smart card passengers. Finally, these algorithms programs are experimented using large scale practical APTS data. The results show that this analysis method is low cost, operability and high accuracy.
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