Designing area pricing schemes to minimize travel disutility and exposure to pollutants. (November 2019)

• Record Type: Journal Article
• Authors: Rodriguez-Roman, Daniel; Allahviranloo, Mahdieh
• Is Part Of: Transportation research. Volume 76(2019)
• Page Start: 236
• Page End: 254
• Publication Date: 2019-11
• Subjects: Surrogate-based optimization -- Area pricing problems -- Activity-based models -- Pollutant exposure; Transportation -- Research -- Periodicals; Transportation -- Environmental aspects -- Periodicals; 354.76
• DOI: 10.1016/j.trd.2019.10.001
• Languages: English
• ISSNs: 1361-9209

Abstract

Highlights: A bi-objective model for the design of area pricing schemes is presented. The model accounts for environmental inequality and pollutant concentration limits. The model also considers the exposure of individuals to vehicle emissions. The agent-based Household Activity Pattern Problem is extended. Surrogate-based optimization approach proposed to solve multi-objective problems. Abstract: The introduction of area-based pricing schemes is often motivated by both urban congestion and pollution concerns. Existing discrete network optimization models for the design of area pricing schemes focus primarily on travel-related objectives, such as maximizing social welfare measures based on travel costs. In this paper, an area pricing problem is proposed that explicitly accounts for both travel- and environmentally-oriented objectives to optimally define charging boundaries and tolling levels. The environmental objective is formulated from an equity perspective. Specifically, it is assumed that regional planners are interested in minimizing inequality in the levels of pollutant encountered by individuals as they perform their daily activities. Here, pollutant exposure is specified in terms of agent-level intake of pollutants. In addition, it is assumed that pricing schemes must reduce pollutant concentrations in the region below an established threshold. A network-based activity model is presented as an approach for modeling the changes in travelers' mobility behavior and activity patterns in response to pricing schemes. A surrogate-based optimization approach is proposed to solve the area pricing problem, as it is likely that, in practice, this design problem would be computationally costly. The proposed algorithm uses a geometric representation of the charging boundary. New procedures for generating candidate boundary locations are presented, which include the use of surrogate-based methods to screen for feasible, non-dominated solutions prior to their evaluation via the computationally expensive models. The proposed model and solution heuristic are tested using the Chicago Sketch Network and a smaller test network.