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TANG Li, ZHOU Hou-qing, ZHANG Xue-jun. Ordered choice model of travel information demand based on scale choice set[J]. Journal of Traffic and Transportation Engineering, 2019, 19(4): 151-160. doi: 10.19818/j.cnki.1671-1637.2019.04.014
Citation: TANG Li, ZHOU Hou-qing, ZHANG Xue-jun. Ordered choice model of travel information demand based on scale choice set[J]. Journal of Traffic and Transportation Engineering, 2019, 19(4): 151-160. doi: 10.19818/j.cnki.1671-1637.2019.04.014
shu

Ordered choice model of travel information demand based on scale choice set

doi: 10.19818/j.cnki.1671-1637.2019.04.014
  • 1.

    School of Automobile and Transportation, Xihua University, Chengdu 610039, Sichuan, China

  • 2.

    School of Electronic and Information Engineering, Beihang University, Beijing 100083, China

More Information
  • Author Bio:

    TANG Li(1988-), female, lecturer, PhD, tangli@mail.xhu.edu.cn

  • Received Date: 2019-03-06
  • Publish Date: 2019-08-25
    Abstract
  • The key information needed for urban travelers' daily activity and travel was studied, and a quantitative analysis method focusing on scale data was proposed. Setting traveler's information demand as the study subject, a survey based on Likert 5 scale questionnaire was designed. The rankings of travel individual's demand degrees for various types of travel information were summarized, and the ordered choice models for driving route, destination location and real-time traffic information demand were built and calibrated separately. The ordered choice model was compared with the multinomial Logit model in terms of parameter significance, Akaike information criterion and log likelihood function value so as to verify its effectiveness, and the partial effect analysis on key variables affecting the information demand was carried out. Research result shows that the bus operation change information is mostly required before the travelers' commuting trips, and the real-time traffic information is mostly required during commuting. Non-commuting travelers care destination location information most, and the demand probabilities for destination location information before departure and en-route are 31.08% and 29.25% higher than that before commuting, respectively. In general, workers have higher information demand degree than that of students and freelancers, indicating that people with high value of time are more expected to properly arrange their trips by comprehensive and timely information acquisition. Demand probability of real-time traffic information for female is 10.23% higher than that for male, indicating that females have stronger cognition in avoiding delay risks. The 20 s to 40 s have the strongest travel information needs that gradually decline with age increasing. All age groups show a higher demand for real-time traffic information, indicating that people are more sensitive to information with potential negative impact. Therefore, the scale choice set can be analyzed by using the ordered choice model.

     

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