Enabling Decision-Making in Battery Electric Bus Deployment through Interactive Visualization

Xiaoyue Cathy Liu, University of Utah



Encouraged by the advancement of battery technology, the transition from diesel or compressed natural gas to fully zero-emission bus fleets has been the trend in the United States. Policymakers and transit agencies have set up goals to accelerate such transition, yet various challenges that are, by nature, institutional, technological and/or financial still present themselves. For example, in terms of institutional challenges, cities without a proper fleet management framework will have a hard time transiting directly to battery electric buses (BEBs). Also, BEBs will require a significantly larger upfront financial investment which could hinder the chance of deploying BEBs. From the technological perspective, successfully deploying BEBs requires a combined knowledge of transportation system, energy/power system, optimization, and risk assessment. 

To address the aforementioned challenges, we designed a bi-objective optimization framework that takes cost and environmental equity into consideration. The flexible framework can also be applied to optimize any transit-related objectives.  Built upon this framework, we develop a prototype of a visualization tool, referred to as the BEBExplorer. Users are able to test, visualize, and explore deployment scenarios given all combinations of constraints on budget, bus schedule, bus routing, locations of charging stations, etc. To ensure the transferability of the pipeline of products, a guidebook detailing the step-by-step implementation, from data compilation to model running to results interpretation to visualization platform set-up, is developed in this Translate Research to Practice project, so that other agencies could replicate easily with their own customized data.

Project Details

Project Type:
Technology Transfer
Project Status:
End Date:
November 30,2022
UTC Grant Cycle:
NITC 16 Translate Research to Practice
UTC Funding: