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Title:

Modeling and Simulation of the Heterogeneous Non-motor Traffic Flow on Physically Separated Bicycle Roadways in China

Accession Number:

01660510

Record Type:

Component

Abstract:

The heterogeneous non-motor traffic flow (including traditional bike and electric bike) is common in China. Existing models fail to reproduce the dynamic and complex interactive behaviors among different non-motorized vehicles under diverse traffic situations, due to the lack of reflecting motivation and decision-making of riders. This paper proposes an integrated “motivation-decision-operation” (MDO) model to settle down the issue. The motivation module based on Comfort-Zone theory divides the Comfort zone of bicycles into five spaces: unaffected space, comfort space, discomfort space, danger space, and yield space. The respectively generated motivations then guide the decision-making process and the operation of behaviors. The model is verified by the travel speed distribution, interspace distribution, features of trajectories and overtaking behaviors, compared with a typical social force model and empirical data. The results show the MDO model is more consistent with the field data than the social force model. Finally, a sensitivity analysis of traffic volume and e-bikes percentage using MDO model is proposed.

Supplemental Notes:

This paper was sponsored by TRB committee ANF20 Standing Committee on Bicycle Transportation.

Report/Paper Numbers:

18-03750

Language:

English

Authors:

Ni, Ying
Li, Xuhong
Sun, Jian
Li, Tienan

Pagination:

8p

Publication Date:

2018

Conference:

Transportation Research Board 97th Annual Meeting

Location: Washington DC, United States
Date: 2018-1-7 to 2018-1-11
Sponsors: Transportation Research Board

Media Type:

Digital/other

Features:

Figures; References; Tables

Geographic Terms:

Subject Areas:

Pedestrians and Bicyclists; Planning and Forecasting; Vehicles and Equipment

Source Data:

Transportation Research Board Annual Meeting 2018 Paper #18-03750

Files:

TRIS, TRB, ATRI

Created Date:

Jan 8 2018 10:56AM