TRB Pubsindex
Text Size:

Title:

Subnetwork Origin-Destination Matrix Estimation under Traffic Demand Constraints

Accession Number:

01629488

Record Type:

Component

Abstract:

This paper proposes a subnetwork origin-destination (OD) matrix estimation model under traffic demand constraints (SME-DC) that explicitly considers both internal-external subnetwork connection and OD demand consistency between the subnetwork and full network. This new model uses maximum entropy of OD demands as the objective function, and uses total traffic generations (attractions) along with some fixed OD demands for each subnetwork OD node as the constraints. The total traffic generations and attractions along with the fixed OD demands for subnetwork OD nodes are obtained through OD nodes transformation and subnetwork topology analysis. For solving the proposed model, a convex combination method is used to convert nonlinear SME-DC to classical linear transportation problem, and tabular method is used to solve the transportation problem. The Sioux Falls network and Kunshan network are provided to illustrate the essential ideas of the proposed model and the applicability of the proposed solution algorithm.

Supplemental Notes:

This paper was sponsored by TRB committee ADB30 Standing Committee on Transportation Network Modeling.

Monograph Accession #:

01618707

Report/Paper Numbers:

17-02862

Language:

English

Corporate Authors:

Transportation Research Board

500 Fifth Street, NW
Washington, DC 20001 United States

Authors:

Sun, Chao
Cheng, Lin
Ma, Jie
Zhu, Senlai
Chu, Zhaoming

Pagination:

15p

Publication Date:

2017

Conference:

Transportation Research Board 96th Annual Meeting

Location: Washington DC, United States
Date: 2017-1-8 to 2017-1-12
Sponsors: Transportation Research Board

Media Type:

Digital/other

Features:

Figures; References; Tables

Subject Areas:

Highways; Planning and Forecasting

Source Data:

Transportation Research Board Annual Meeting 2017 Paper #17-02862

Files:

TRIS, TRB, ATRI

Created Date:

Dec 8 2016 11:04AM