Excavation of Attractive Areas for Car-Share Travel and Prediction of Car-Share Usage Beijing Jiaotong University, China

Format:

Book

Conference/Event

Author/Creator:

Wu, Zhen, author.

Contributor:

Bi, Jun

Sai, Qiuyue

Conference Name:

3rd International Forum on Connected Automated Vehicle Highway System through the China Highway & Transportation Society (2020-10-29 : Jinan, China)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2020

Summary:

Car-share trajectory is the big data of time and space that contains the travel behavior of residents. It is of great significance for station planning to dig out residents' travel hotspots from the Car-share track data. This paper uses a clustering algorithm based on grid density. The algorithm first divides the trajectory space into grid cells and sets the density threshold of the grid cells; then maps the trajectory points to the grid cells and extracts hot grid cells based on the density threshold; By merging reachable hotspot grid units, hotspot areas of cities are discovered. This paper analyzes the demand for residents' travel in the hotspot area, and uses the random forest model to predict the demand, which can make a reference for the car-share company to launch cars and provide convenience for users to travel

Notes:

Vendor supplied data

Publisher Number:

2020-01-5176

Access Restriction:

Restricted for use by site license