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Title:

Measuring the Cost Trade-Offs Between Electric-Assist Cargo Bikes and Delivery Trucks in Dense Urban Areas

Accession Number:

01661444

Record Type:

Component

Abstract:

Urban freight deliveries are increasingly challenged in dense urban areas, particularly where delivery trucks are required to meet delivery time windows. Depending on the route characteristics, Electric Assist (EA) cargo bikes may serve as an economic and environmentally sustainable alternative to delivery trucks. In this paper, the cost trade-offs between a box delivery truck and an EA cargo bikes are compared. The independent and constant variables and assumptions used for a cost function comparison model are gathered through data collection, a literature review, and interviews. An observed route completed by a well-known courier company was used as a control and the same route was modeled with an EA cargo bike. It was found that a delivery truck was a more cost efficient vehicle type given the route and delivery characteristics present. Four separate delivery scenarios were modeled to explore how the distance between distribution center (DC) and neighborhood, a number of stops, distance between each stop, and a number of parcels per stop would impact the optimum vehicle type. The results from the models indicate that the route and delivery characteristics significantly influence whether a delivery truck or EA cargo bike is the best option.

Supplemental Notes:

This paper was sponsored by TRB committee AT025 Standing Committee on Urban Freight Transportation.

Report/Paper Numbers:

18-05401

Language:

English

Authors:

Butrina, Polina
Sheth, Manali
Goodchild, Anne
McCormack, Edward

Pagination:

5p

Publication Date:

2018

Conference:

Transportation Research Board 97th Annual Meeting

Location: Washington DC, United States
Date: 2018-1-7 to 2018-1-11
Sponsors: Transportation Research Board

Media Type:

Digital/other

Features:

Figures; References

Uncontrolled Terms:

Subject Areas:

Finance; Freight Transportation; Highways; Pedestrians and Bicyclists; Planning and Forecasting; Vehicles and Equipment

Source Data:

Transportation Research Board Annual Meeting 2018 Paper #18-05401

Files:

TRIS, TRB, ATRI

Created Date:

Jan 8 2018 11:22AM