Open AccessInfluencing factor analysis of car-sharing demand based on point of interest data
Author(s) -
Huimin Dong,
XiaoBao Yang,
Wencheng Wang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1972/1/012074
Subject(s) - beijing , negative binomial distribution , car sharing , transport engineering , computer science , traffic congestion , point (geometry) , car ownership , sharing economy , order (exchange) , public transport , business , engineering , china , geography , mathematics , statistics , geometry , archaeology , finance , world wide web , poisson distribution
The rise of car-sharing can make full use of road space resources, alleviate traffic congestion and reduce traffic energy consumption. However, due to the failure to accurately predict the demand distribution of car-sharing, there are a lot of empty driving phenomena in vehicle scheduling, which leads to the economic losses of car-sharing operators. Existing studies show that the point of interest has a significant impact on urban residents’ travel, but few of them study the quantitative relationship between interest points and shared car orders. Based on this, using the order data of car-sharing in Beijing, this paper establishes a negative binomial model of travel demand and density of different kind of points of interest, and analyzes their relationship. The analysis found that users tend to use car-sharing to go to leisure places. In areas where public transportation is underdeveloped, people will use car-sharing more. The methodology of this paper can provide a theoretical basis for sharing automobile enterprises to develop new operation areas and select reasonable car sharing stations.