Excavation of Attractive Areas for Car-Share Travel and Prediction of Car-Share Usage

2020-01-5176

12/30/2020

Features
Event
3rd International Forum on Connected Automated Vehicle Highway System through the China Highway & Transportation Society
Authors Abstract
Content
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.
Meta TagsDetails
DOI
https://doi.org/10.4271/2020-01-5176
Pages
5
Citation
Wu, Z., Bi, J., and Sai, Q., "Excavation of Attractive Areas for Car-Share Travel and Prediction of Car-Share Usage," SAE Technical Paper 2020-01-5176, 2020, https://doi.org/10.4271/2020-01-5176.
Additional Details
Publisher
Published
Dec 30, 2020
Product Code
2020-01-5176
Content Type
Technical Paper
Language
English