Measuring delivery route cost trade-offs between electric-assist cargo bicycles and delivery trucks in dense urban areas

INTRODUCTION: Completing urban freight deliveries is increasingly a challenge in congested urban areas, particularly when delivery trucks are required to meet time windows. Depending on the route characteristics, Electric Assist (EA) cargo bicycles may serve as an economically viable alternative to delivery trucks. The purpose of this paper is to compare the delivery route cost trade-offs between box delivery trucks and EA cargo bicycles that have the same route and delivery characteristics, and to explore the question, under what conditions do EA cargo bikes perform at a lower cost than typical delivery trucks? METHODS: The independent variables, constant variables, and assumptions used for the cost function comparison model were gathered through data collection and a literature review. A delivery route in Seattle was observed and used as the base case; the same route was then modelled using EA cargo bicycles. Four separate delivery scenarios were modeled to evaluate how the following independent route characteristics would impact delivery route cost - distance between a distribution center (DC) and a neighborhood, number of stops, distance between each stop, and number of parcels per stop. RESULTS: The analysis shows that three of the four modeled route characteristics affect the cost trade-offs between delivery trucks and EA cargo bikes. EA cargo bikes are more cost effective than delivery trucks for deliveries in close proximity to the DC (less than 2 miles for the observed delivery route with 50 parcels per stop and less than 6 miles for the hypothetical delivery route with 10 parcels per stop) and at which there is a high density of residential units and low delivery volumes per stop. CONCLUSION: Delivery trucks are more cost effective for greater distances from the DC and for large volume deliveries to one stop.

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  • English

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  • Accession Number: 01703061
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Feb 14 2019 3:07PM