Assessing overnight parking infrastructure policies for commercial vehicles in cities using agent-based simulation
Name
sustainability-12-02673-v2.pdf
Size
2.62 MB
Format
Adobe PDF
Checksum (MD5)
0875c46c77b42a480272335ec9478734
Author(s)
Gopalakrishnan, Raja
Alho, André Romano
Sakai, Takanori
Hara, Yusuke
Cheah, Lynette
Ben-Akiva, Moshe E.
Date Issued
March 28, 2020
Journal
Sustainability
Publisher
Multidisciplinary Digital Publishing Institute
Citation
Gopalakrishnan, Raja, et al., "Assessing overnight parking infrastructure policies for commercial vehicles in cities using agent-based simulation." Sustainability 12, 7 (Mar. 2020): no. 2673 doi 10.3390/su12072673 ©2020 Author(s)
Version
Final published version
Abstract
Urban freight transport is primarily fulfilled by commercial road vehicles. Within cities, overnight parking is a critical element influencing commercial vehicle operations, particularly for heavy vehicles with limited parking options. Providing adequate overnight parking spaces for commercial vehicles tends to be a challenge for urban planners. Inadequate parking supply can result in illegal parking and additional vehicle kilometers traveled, contributing to traffic congestion and air pollution. The lack of tools for evaluating the impacts of changing parking supply is an impediment in developing parking-related solutions that aim to minimize the negative externalities. In this study, we develop an overnight parking choice model for heavy commercial vehicles and integrate it with SimMobility, an agent-based urban simulation platform, demonstrating the potential of this tool for policy evaluation. Using simulations applied to a case study in Singapore, we compare two parking supply scenarios in terms of vehicle kilometers traveled due to changes in the first and last trips of vehicle tours, as well as resulting impacts in traffic flows. ©2020 Keywords: urban freight; freight parking; city logistics; parking choice; SimMobility
MIT Department
Singapore-MIT Alliance in Research and Technology (SMART)
Massachusetts Institute of Technology. Intelligent Transportation Systems Laboratory
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.3390/su12072673
