Accounting for population exposure to vehicle-generated pollutants and environmental equity in the toll design problem

The emissions generated by motor vehicles remain a major source of air pollutants that affect public health and contribute to anthropogenic climate change. These negative externalities can be reduced, in part, with the implementation of environmentally oriented road pricing schemes, which can be des...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:International journal of sustainable transportation Ročník 11; číslo 6; s. 406 - 421
Hlavní autori: Rodriguez Roman, Daniel, Ritchie, Stephen G.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Taylor & Francis 03.07.2017
Predmet:
Algorithms
Bilevel optimization
Design analysis
environmental equity
Exposure
Mathematical analysis
Mathematical models
network design problems
Pollutants
pollution exposure
road pricing
surrogate-based solution algorithm
toll design problem
Toll roads
Traffic models
ISSN:1556-8318, 1556-8334
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:The emissions generated by motor vehicles remain a major source of air pollutants that affect public health and contribute to anthropogenic climate change. These negative externalities can be reduced, in part, with the implementation of environmentally oriented road pricing schemes, which can be designed using optimization-based approaches. In this paper, a toll design problem is proposed for determining toll locations and levels that minimize the expected human exposure to air pollutants and the related environmental inequalities, subject to constraints on pollutant concentration levels and implementation costs. The practical use of the proposed problem is hindered in most real-world applications by the computational costs associated with the evaluation of candidate solutions, as is common for network design problems. Furthermore, the problem cannot be expressed analytically given the multiple types of models (e.g., traffic assignment, emissions, air dispersion models) that would be required to evaluate a single design alternative. For these reasons, a derivative-free surrogate-based solution algorithm is proposed for mixed integer problems like the ones considered here. Numerical examples are used to illustrate possible applications of the proposed model and to test the performance of the surrogate-based algorithm. Relative to a joint simulated annealing-genetic algorithm heuristic and a genetic algorithm-based approach, the proposed algorithm found better solutions in fewer function evaluations.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1556-8318
1556-8334
DOI:10.1080/15568318.2016.1266423