Urban Freight and Heavy Vehicle Study

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 .

Project Title: 

Urban Freight and Heavy Vehicle Study (Award No. L2NICTDF1-2016-1)

Project Manager(s): 

Moshe E. Ben-Akiva, André Romano Alho, Lynette Cheah (SUTD)

Sponsor: 

Singapore’s Ministry of National Development (MND) and the National Research Foundation (Singapore)

Team: 

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)

Start Date: 

May 2016

Scheduled End Date: 

November 2019

Research Highlights: 

● 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.

References: 

● Lu, F., F. Zhao, L. Cheah, 2018. Dimensionality Reduction to Reveal Urban Truck Driver Activity Patterns. Transportation Research Record. Manuscript accepted (presented at Transportation Research Board 97th Annual Meeting, 2018).
● Sakai, T., B. B. Kuzhiyamkunnath, A. Alho, T. Hyodo, M. Ben-Akiva, 2018. Urban Freight Distribution considering Logistics Chain Structure: Selection of Supplier with Distribution Channel, TRB 97th Annual Meeting, Jan 7-11, 2018, Washington, D.C.
● Sakai, T., B. B. Kuzhiyamkunnath, A. Alho, T. Hyodo, M. Ben-Akiva. 2018. Commodity flow estimation for a metropolitan scale freight modeling system: supplier selection considering distribution channel using an error component logit mixture model. Transportation.
● Alho, A., et al, 2017. A multi-scale agent-based modelling framework for urban freight distribution, Transportation Research Procedia, 20th EURO Working Group on Transportation Meeting, EWGT 2017, 4-6 September 2017, Budapest, Hungary.
● Dalla Chiara, G., L. Cheah, 2017. Data stories from loading bays. European Transport Research Review (2017) 9:50. doi:10.1007/s12544-017-0267-3 (presented at VREF Conference on Urban Freight 2016).
● Sun, X., et al, 2017. A Generic Framework for Monitoring Local Freight Traffic Movements Using Computer Vision-based Techniques, 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, June 26-28, 2017, Naples, Italy.
● Cheah, L., et al, 2017. Next-Generation Commodity Flow Survey: A Pilot in Singapore. 10th International Conference on City Logistics, Jun 14-16, 2017, Phuket, Thailand.
● Lu, F. et al, 2017. Applying gamification to freight surveys: understanding Singapore truck drivers’ preferences, 10th International Conference on City Logistics, 14-16 June 2017, Phuket, Thailand.
● Dalla Chiara, G. et al, 2017. Evaluating the Impact of Centralized Goods Receiving Stations at Urban Retail Malls. TRB 96th Annual Meeting, Jan 8-12, 2017, Washington, D.C.
● Alho, A. R., Linlin, Y., Lu, F., Cheah, L., Zhao, F., and M. Ben-Akiva (2018) Next-generation freight vehicle surveys by supplementing truck GPS tracking with a driver activity survey: account and insights. The 21st IEEE International Conference on Intelligent Transportation Systems, November 4-7, 2018, Maui, Hawaii, USA.
● You, L., Zhao, F., Cheah, L., Jeong, K., Zegras, C. and M. Ben-Akiva (2018) Future Mobility Sensing: An Intelligent Mobility Data Collection and Visualization Platform. The 21st IEEE International Conference on Intelligent Transportation Systems, November 4-7, 2018, Maui, Hawaii, USA.
● Jing, P., Zhang, Y., Jeong, K., Alho, A. R. and M. Ben-Akiva. 2019. MODELING DAILY TOUR-CHAINING PATTERN CHOICE OF URBAN HEAVY COMMERCIAL VEHICLES. Presented at the Transportation Research Board 2019 Annual Meeting
● Sakai, T., B. B. Kuzhiyamkunnath, A. Alho, T. Hyodo, M. Ben-Akiva. 2019. Modeling Freight Generation, Commodity Contracts, and Shipments for SimMobility Freight – A Disaggregate Agent-Based Urban Freight Simulator. Presented at the Transportation Research Board 2019 Annual Meeting