Assessing Overnight Parking Infrastructure Policies for Commercial Vehicles in Cities Using Agent-Based Simulation

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.

Exploring Algorithms for Revealing Freight Vehicle Tours, Tour-Types, and Tour-Chain-Types from GPS Vehicle Traces and Stop Activity Data

“…• Base-driven algorithm: A return to the identified base marks the end of a tour. This algorithm is most aligned with prior research applications such as You and Ritchie (2018) and Gopalakrishnan et al (2019). • Purpose-driven algorithm: A pickup stop that follows a delivery marks the start of a new tour.…”

“…Well-structured and informationrich records of truck tours have the potential to enhance the replication of freight vehicle tour-chains in a simulation environment for policy analysis. The definition of methods for identifying tours directly contributes to tour-chain modelling (Jing et al 2019), tour-based simulation case studies , Gopalakrishnan et al 2019, and the identification of commodity flows and load factors (Alho et al 2018).…”

Challenges and Threats Faced in 2020 by International Logistics Companies Operating on the Polish Market

“…After the quantitative analysis, it was considered worthwhile to investigate the content of the identified items. The articles published this year can basically be divided into two thematic areas: challenges in urban logistics [10][11][12] and intermodal transport issues or industry perspectives on selected issues, e.g., India [13], the Silk Road [14], or challenges in the context of emerging economies [15]. The issue of risk related to supply chains is discussed in the publication focused on identification and proposal of a set of seven risk factors that drive the risks associated with the Belt and Road initiative.…”

A Simulation-Based Evaluation of a Cargo-Hitching Service for E-Commerce Using Mobility-on-Demand Vehicles

“…The long-term model captures land use and economic activity as they are related to a set of longer-term decisions (residential choice, workplace choice), which are more stable in time [28,29]. Households and individuals are considered as well as businesses (i.e., commodity flows [30]), including the overnight parking choices of freight vehicles [31].…”