Y3R3- Integrate Autonomous Delivery Vehicle into Sustainable Urban Logistics Planning and Optimization: Economic and Environmental Evaluation

The ongoing urbanization presents a challenge both to enterprises who want to adapt to the change and deliver goods more efficiently, also the policymakers who can positively impact urban logistics in terms of trade-off decisions on economic and environmental impact. As sustainable urban distribution system becomes one of the most recent trends, hubs are augmented with smaller logistic centers in the city. In urban logistics system, autonomous delivery vehicles (ADV) as a new element of ground-based delivery services are a more practical solution in cities. The study team discusses the potential ADV combined with delivery van regarding the urban sustainable freight delivery network. A multi-modal and multi-objective optimization model is proposed to simultaneously minimize the aggregate operating cost and reduce carbon dioxide emission. Also, delivery hubs from alternative hubs are chosen for ADV positioning. An improved Non-dominated Sorting Genetic Algorithm was used to solve the problem. The study team applies it to a case study comparing the Economic and Environmental performance in both unimodal delivery method and combined delivery using Van-Autonomous delivery vehicle (V-ADV). Finally, sensitivity analysis is used to assess the robustness of the results of the model in the presence of uncertainty. This research provides decision support to government authorities, logistics service providers, and other relevant decision makers. Motivated both by the adaption of new delivering technologies (ADV) in practical transportation industry and the theoretical gap existing in the present literature, a network planning problem for the cooperated van and ADV is studied. The primary objective of this study is to develop an urban logistics optimization model in terms of minimizing the logistics operating cost and carbon emission using V-ADV from the point of authorities. Simultaneously, the best locations from a set of existing stations are selected for ADV positioning and optimal flow assignment.

Language

• English

Project

• Status: Active
• Funding: $95,733
• Contract Numbers:

  69A3551747120

• Sponsor Organizations:

  United States Department of Transportation - FHWA - LTAP

  1200 New Jersey Avenue, SE
  Washington, DC    20590

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  Freight Mobility Research Institute

  Florida Atlantic University
  Boca Raton, FL  United States  33431
• Project Managers:

  Stearns, Amy

• Performing Organizations:

  Florida Atlantic University, Boca Raton

  Boca Raton, FL  United States  33431
• Principal Investigators:

  Kaisar, Evangelos

  Liu, Dan

• Start Date: 20190212
• Expected Completion Date: 20190322
• Actual Completion Date: 20210727
• USDOT Program: Advanced Research

Subject/Index Terms

• TRT Terms: Autonomous vehicles; Delivery vehicles; Economic factors; Logistics; Operating costs; Optimization; Sustainable transportation; Urban areas
• Subject Areas: Administration and Management; Economics; Environment; Freight Transportation; Highways; Planning and Forecasting; Vehicles and Equipment;

Filing Info

• Accession Number: 01777979
• Record Type: Research project
• Source Agency: Freight Mobility Research Institute
• Contract Numbers: 69A3551747120
• Files: UTC, RIP
• Created Date: Jul 27 2021 5:29PM