摘要
随着出行需求和机动车保有量的迅猛增加,城市道路不堪重负,不仅交通拥堵严重,同时大量的尾气排放更造成了严重的空气环境污染问题.本文在传统的道路收费研究中明确加入排放约束或目标,建立了一系列带均衡约束的数学规划双层决策模型,探讨多模式混合交通网络下如何通过经济手段诱导人们选择更环保的出行模式和更合理的出行路径,以同时达到缓解交通拥堵和降低尾气排放的目的.模型下层考虑多模式之间的相互影响,运用变分不等式描述个体出行者的模式路径选择;上层根据不同的管理目标构建数学规划模型.采用遗传模拟退火算法对数值算例进行求解,结果显示了道路收费对系统各种指标的影响和改善.
The rapid growth of travel demand and the overuse of private cars give rise to not only the severe traffic jam in the urban area, but also the adverse air pollution due to lots of vehicles＇ emissions. This paper re-explores the traditional road pricing problem by involving the emission constraints or targets. The primary objective of this study is to investigate the impact of road pricing schemes on the route and mode choices of travelers for a multi-modal transportation network so as to achieve the congestion alleviation and emissions reduction simultaneously. The concerned problem is formulated into a mathe- matical programming with equilibrium constraints （MPEC）, which is a bi-level model. In the lower level, a variational inequality model is constructed to model the combined mode-split and traffic-assignment problem considering the asymmetric interactions among travel modes. The upper level is a mathematical programming with various management objectives and constraints. The governor in the upper level would make the decisions on road tolls based on the responses from the lower road users. The genetic simulated annealing algorithm （GSAA） is proposed to solve the bi-level model. The effectiveness of the algorithm and the effect of road tolls on the system performance are illustrated in the numerical example.
出处
《系统工程理论与实践》
EI
CSSCI
CSCD
北大核心
2016年第9期2345-2354,共10页
Systems Engineering-Theory & Practice
基金
国家自然科学基金面上项目(71271112)~~
关键词
道路收费
尾气排放
模式选择
均衡约束数学规划
遗传模拟退火算法
road pricing
emissions
mode choice
mathematical programming with equilibrium constraints
genetic simulated annealing algorithm
