Characteristics of Relative Spatiotemporal Efficiency of Urban Public Transit Based on Real-Time Road Conditions

Abstract

The travel efficiency of public transportation is a key indicator for judging whether the quality of public transportation has developed compared with other modes of transportation, especially private vehicles. The quality of public transportation is also an important reference factor for residents' choices. With the rapid urban expansion and improvement in motorized travel levels, reducing the time difference between private vehicles and public transportation is the key to improving the attractiveness of public transportation. The relative spatiotemporal efficiency is based on the time difference between private vehicles and public transportation, considering the number of passengers. Recently, scholars have shown great interest in relative travel efficiency. However, relevant studies have shown poor real-time performance because of the unavailability of large datasets, which cannot dynamically reflect the characteristics of relative travel efficiency. The spread of big data and internet maps enables us to perform systematic efficiency evaluations. The internet map incorporates various travel-related information such as travel route, time, and cost under different travel modes based on real-time road conditions and provides access to the extracted embedded travel information. This study proposes a framework for evaluating the spatiotemporal efficiency of different travel modes based on real-time road conditions in Shenzhen. First, travel time data were obtained using an internet map during the morning, afternoon, and evening rush hours. The passenger flow volume was computed using smart card data. We then constructed an evaluation index model of spatiotemporal efficiency based on the relative time efficiency and weighted passenger flow volume. Finally, the results highlighted the following: 1) the relative time efficiency of public transportation was higher during the evening rush hours than in the morning. The main reason was the increase in private vehicle travel time during the evening rush hours, reflecting the complexity of urban road conditions during the evening; 2) the spatiotemporal efficiency index of central public transport stations fluctuated greatly during the three periods, which was closely related to the dynamics of traffic volume caused by the high concentration of workplaces; 3) the spatiotemporal efficiency index of public transportation stations exhibited spatial aggregation characteristics in the three periods, highlighting the different clustering characteristics in the central and outer areas; 4) the spatiotemporal efficiency index of subway stations was generally higher than that of bus stations, reflecting the importance of subway systems in urban transportation networks. Evaluating the relative travel efficiency of urban public transport contributes to analyzing the development status of public transportation, supporting decisions to achieve high-quality development of public transport, and providing travel information for the government and residents.

Keywords

• public transportation
• real-time road conditions
• relative spatiotemporal efficiency
• spatiotemporal big data
• shenzhen city