Abstract
Real-time transit information (RTI) service can provide travellers with information on public transport and guide them to arrange departure time and travel mode accordingly. This paper aims to analyse travellers’ choices under RTI by exploring the relationship between the related variables of RTI and passengers’ travel choice. Based on the stated preference (SP) survey data, the ordinal logistic regression model is established to analyse the changing probability of passengers’ travel behaviour under RTI. The model calculation results show that travellers getting off work are more likely to change their travel choice under RTI. When data from the control and experimental groups are compared, the differences in route selection are significant. Specifically, passengers with RTI have a more complex route selection than those without, including their changes of travel mode, departure time, vehicles, and stop choices. The research findings can provide insights into the optimisation of intelligent transit information systems and the strategy of RTI. Also, the analysis of passengers’ travel choice under RTI in the transit network can help to improve network planning.
Highlights
Improving the efficiency of public transportation and user satisfaction has been widely studied for a long time [1]
The results show that the score difference is not significant for the weekly bus travel mode selection (t=0.54, p=0.631), and there is no significant change for the weekly departure time choices (t=0.46, p=0.593)
Based on the data analysis, we designed a statistical experiment that integrated the survey data to facilitate the review of decision-making changes before and after the use of real-time transit information (RTI)
Summary
Improving the efficiency of public transportation and user satisfaction has been widely studied for a long time [1]. Among them, providing passengers with effective real-time transit information (RTI) has been a very popular practice in recent years [2,3,4]. In order to assess the impacts of RTI that are obtained from electronic devices such as mobile phones, several stated preference (SP) surveys, and revelled preference (RP) surveys have been conducted [9]. These impacts are mostly related to passenger perception of time [10], passenger anxiety [11, 12], and their level of ride satisfaction
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