Travel Demand Estimation in a Multi-subnet Urban Road Network

被引：0

作者：

Krylatov, Alexander ^{[1
,2
]}

Raevskaya, Anastasiya ^{[1
]}

机构：

[1] St Petersburg State Univ, St Petersburg, Russia

[2] RAS, Inst Transport Problems, St Petersburg, Russia

来源：

LEARNING AND INTELLIGENT OPTIMIZATION, LION 15 | 2021年 / 12931卷

基金：

俄罗斯科学基金会;

关键词：

Bi-level optimization; Travel demand estimation; Multi-subnet urban road network; COMPOSITED COMPLEX NETWORK; MATRIX ESTIMATION; DESIGN; OPTIMIZATION; ASSIGNMENT; SCALE;

D O I：

10.1007/978-3-030-92121-7_16

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Today urban road network of a modern city can include several subnets. Indeed, bus lanes form a transit subnet available only for public vehicles. Toll roads form a subnet, available only for drivers who ready to pay fees for passage. The common aim of developing such subnets is to provide better urban travel conditions for public vehicles and toll-paying drivers. The present paper is devoted to the travel demand estimation problem in a multi-subnet urban road network. We formulate this problem as a bi-level optimization program and prove that it has a unique solution under quite a natural assumption. Moreover, for the simple case of a road network topology with disjoint routes, we obtain important analytical results that allow us to analyze different scenarios appearing within the travel demand estimation process in a multi-subnet urban road network. The findings of the paper contribute to the traffic theory and give fresh managerial insights for traffic engineers.

引用

页码：183 / 197

页数：15

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