Space-Time Behavior Survey for Smart Travel Planning in Beijing, China

Space-Time Behavior Survey for Smart Travel Planning in Beijing, China

Yanwei Chai (Peking University, China), Zifeng Chen (Peking University, China), Yu Liu (Peking University, China), Tana (Peking University, China) and Xiujun Ma (Peking University, China)
DOI: 10.4018/978-1-4666-6170-7.ch005
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Abstract

In China, smart travel planning, trying to influence traveler behavior using information and communication technologies, has attracted growing interest from governments and scholars because of its potential to alleviate urban transportation problems. The implementation of smart travel planning should be based on in-depth investigations and analysis of activity-travel behavior; it is necessary to use space-time behavior data and studies in smart travel planning. This chapter argues the necessity of space-time behavior surveys for smart travel planning in China and discusses a recent example. The survey was carried out in the Shangdi-Qinghe area of Beijing and involved 709 residents recruited through a multi-stage cluster sampling procedure. GPS tracking technologies were integrated with Web-based activity-travel diaries to collect data of high spatial and temporal resolution. The data shows that, on average, respondents participated in 8.19 activities and 2.66 trips per person per day. Despite several defects, the data provides a good quantitative foundation for smart travel planning in the study area.
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Transportation Information Delivery

Transportation information services based on Websites or mobile phone apps are emerging in Chinese cities. These services provide real-time information about navigation, road traffic situations, operations status of public transport, traffic regulations, traffic emergency, etc. Currently, three types of transportation information services can be distinguished. The first type of service, in which neither the socio-demographics nor location data of travellers are used, only delivers information about traffic congestion, traffic regulations, and traffic incidents of the whole city or district. The second type of information service, in which the location data of travellers are used, delivers information about traffic congestion, traffic incidents, and bus stations close to certain road sections, based on the travellers’ current locations. Using data of the traveller’s speed and acceleration, the transportation mode can be identified automatically, and related transportation information can be selected and delivered. The third type of service, in which the socio-demographics of travellers are used, delivers different transportation information targeted at different population groups (e.g. women, elders, children, disabled, etc.).

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