A Class of Efficient Algorithms for the Bi-Level Demand Adjustment Problems in Congested Traffic Networks
This paper studies a class of gradient-descent heuristic algorithms for the bi-level demand adjustment problem (DAP), which seeks to adjust origin-destination (OD) matrices based on observed link flows in congested transportation networks. We first present a general gradient-descent solution framewo...
Saved in:
Main Authors: | Lan Cheng, Jun Xie, Jun Huang, Liyang Feng, Qianni Wang, Hongtai Yang |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2023-01-01
|
Series: | Journal of Advanced Transportation |
Online Access: | http://dx.doi.org/10.1155/2023/8862759 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Evaluation of Shared Space to Reduce Traffic Congestion
by: Colin Frosch, et al.
Published: (2019-01-01) -
Dynamic Congested Traffic States of Density Difference Lattice Hydrodynamic Model with On-Ramp
by: Jun-fang Tian, et al.
Published: (2013-01-01) -
How Well Does the Traffic System Protect Transit from Congestion? Measuring Route-Level Costs That Congestion Imposes on Transit Operators and Users
by: Peter G. Furth, et al.
Published: (2018-01-01) -
Dynamic Traffic Congestion Simulation and Dissipation Control Based on Traffic Flow Theory Model and Neural Network Data Calibration Algorithm
by: Li Wang, et al.
Published: (2017-01-01) -
Congestion Control for Mixed-Mode Traffic with Emission Cost
by: Ya Li, et al.
Published: (2020-01-01)