The aim of this research project is to develop an integrated framework for data collection, modelling, simulation and decision-making to facilitate the design and evaluation of policies related to urban freight and logistics, as well as the planning and provision of Heavy Vehicle Parks (HVP). This project applies next-generation sensing and surveying capabilities using the Future Mobility Sensing behavioral laboratory. Moreover, it extends and enhances innovative freight behavioural models in the SimMobility simulation laboratory .
Urban Freight and Heavy Vehicle Study (Award No. L2NICTDF1-2016-1)
Moshe E. Ben-Akiva, André Romano Alho, Lynette Cheah (SUTD)
Singapore’s Ministry of National Development (MND) and the National Research Foundation (Singapore)
Moshe Ben-Akiva, Chris Zegras, André Romano Alho, Zhao Fang, Tomer Shaby, Takanori Sakai, Yusuke Hara, Rayden Chua, Zhiyuan Chua, Chu Yaw Tai, Kakali Basak, Wen Han Chong, Raja Gopalakrishnan, Giacomo Dalla Chiara, Rakhi Manohar, Peiyu Jing, Linlin You, Thanh Le Tan, Andrew Tong, Rebecca Lau, Lynette Cheah (STUD), Costas Courcoubetis (SUTD), Ngai-Man Cheung (SUTD), Lee Ven Hoo (URA)
Scheduled End Date:
● Data Collection: The project will collect data on (i) freight and goods (e.g. production/consumption flows, logistics and transportation arrangements, etc.) and (ii) heavy vehicles (e.g. routes, parking locations, usage patterns of heavy vehicle parking places, truck driver preferences, etc.). Data collection methods include GPS tracking of selected freight vehicles and shipments, and surveys on truck drivers and relevant establishments and agents. The research team will leverage on state-of-the-art sensing technologies and approaches to obtain urban freight and HV data (e.g. automated identification of vehicle types, instead of manual counts).
● Modelling and Analysis: Models of freight behaviours will be integrated with the SimMobility agent-based model of passenger and freight transportation, intended for urban freight transportation analysis and design/evaluation of innovative and sustainable solutions.
● Decision and Policy-Making: To ensure applicability in real-world settings, we will demonstrate through pilot trials and case studies how technology-enabled urban freight and logistics innovations, and data-driven freight and HVP planning can impact land use and transportation system.