李晓伟 Likes:

Journal:

Computational Intelligence and Neuroscience

Key Words:

ELECTRIC BIKE USERS; HIGH-SPEED RAIL; PREDICTION MODEL; IMPACTS

Abstract:

To explore the influence of weather conditions on the choice of the intercity travel mode of travelers, four modes of traveler transportation were studied in Xi'an, China, in March 2019: airplane, high-speed rail, conventional train, and express bus. The individual characteristics of travelers and intercity travel activity data were obtained, and they were matched with the weather characteristics at the departure time of the travelers. The Bayesian multinomial logit regression was employed to explore the relationship between the travel mode choice and weather characteristics. The results showed that temperature, relative humidity, rainfall, wind, air quality index, and visibility had significant effects on the travel mode selection of travelers, and the addition of these variables could improve the model’s predictive performance. The research results can provide a scientific decision basis for traveler flow transfer and the prediction of traffic modes choice due to the effects of climate change.

Co-author:

马强强,王文博,王宝杰

First Author:

李晓伟

Translation or Not:

no

Date of Publication:

2021-01-01

Included Journals:

EI