Lessons and Challenges from Crowd-Sourced Data in Rural Michigan to Assess EV Suitability based on Analyzing Personal Driving University of Michigan-Ann Arbor

Format:

Book

Conference/Event

Author/Creator:

Manoj, Ashwin, author.

Contributor:

Faraj, Aḥmad ʻUmar

Stefanopoulou, Anna

Tomkins, Sabina

Vaishnav, Parth

Yin, Sally

Conference Name:

WCX SAE World Congress Experience (2025-04-08 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2025

Summary:

AbstractReal-world driving data is an invaluable asset for several types of transportation research, including emissions estimation, vehicle control development, and public infrastructure planning. Traditional methods of real-world driving data collection use expensive GPS-based data logging equipment which provide advanced capabilities but may increase complexity, cost, and setup time. This paper focuses on using the Google Maps application available for smartphones due to the potential to scale-up real-world driving data logging. Samples of the potential data processing and information that can be gathered by such a logging methodology is presented. Specifically, two months of Google Maps driving data logged by a rural Michigan resident on their smartphone may provide insights on their driving range, duration, and geographic area of coverage (AOC) to guide them on future vehicle purchase decisions. Aggregating such statistics from crowd-sourcing real-world driving data via Google Maps may also inform us of general characteristics in rural driving, along with placing public chargers, particularly in under-studied geographic regions like rural Michigan

Notes:

Vendor supplied data

Publisher Number:

2025-01-8525

Access Restriction:

Restricted for use by site license