AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
Home AIMS Energy Article
PDF (1.1 MB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Research Article | Open Access

TALe-Bus: An interactive dashboard for electric bus fleet electrification planning

Kareem Othman1,2( )Diego Da Silva1Amer Shalaby1Baher Abdulhai1
Department of Civil and Mineral Engineering, University of Toronto, Toronto, Ontario, Canada
Public Works Department, Faculty of Engineering, Cairo University, Giza, Egypt
Show Author Information

Abstract

This study presents the development of the Transit Analytics Lab Electric Bus (TALe-Bus) Dashboard, an integrated decision-support tool designed to support transit agencies in planning the transition from conventional diesel buses to battery-electric buses. The dashboard combines predictive modeling, data analytics, and interactive visualization to estimate electric bus energy consumption rates, fleet size requirements, replacement factors, and maximum operational range for the case of overnight depot charging. The dashboard was built based on real-world data collected from the operations of 60 battery-electric buses on 48 routes in Toronto. The modeling workflow includes data preprocessing, feature selection, and the development and comparison of multiple statistical and machine learning energy prediction models. Tree-based modeling techniques outperformed the other techniques, demonstrating strong capability in capturing the relationships between operational, environmental, vehicle, and route characteristics and the energy consumption rate, achieving a root mean square error (RMSE) of 0.13 kWh/km. These techniques were therefore adopted as the core predictive engine of the system. The fleet-sizing module integrates traditional transit planning formulations (for diesel fleets) with electric-bus energy and range constraints to estimate both electric and diesel fleet requirements and compute the replacement factor, a key indicator reflecting the relative fleet needs for electrification. The dashboard also estimates the maximum operational bus range based on the battery capacity and real-world operating conditions, supporting reliable service planning. The system is implemented as an interactive web-based platform that provides geospatial visualization of route electrification feasibility and a scenario-based interface for customized operational analysis. By translating complex predictive analytics into a practical planning tool, the TALe-Bus Dashboard supports informed, data-driven decision-making for fleet electrification and infrastructure planning.

References

【1】
【1】
 
 
AIMS Energy
Pages 732-759

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
Othman K, Da Silva D, Shalaby A, et al. TALe-Bus: An interactive dashboard for electric bus fleet electrification planning. AIMS Energy, 2026, 14(3): 732-759. https://doi.org/10.3934/energy.2026030

3

Views

0

Downloads

0

Crossref

0

Web of Science

0

Scopus

Received: 01 March 2026
Revised: 30 May 2026
Accepted: 15 June 2026
Published: 15 June 2026
©2026 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)