01627972

Component

https://doi.org/10.3141/2645-07

This research developed an ecodriving support platform based on Internet+ technology and aimed at real-time dynamic collection and feedback optimization of driving behavior. The system served government and enterprises in monitoring and managing drivers’ driving behaviors and provides practical ecodriving feedback information on improvement in individual drivers’ driving behavior through a smartphone app. The vehicle operation data were collected by onboard diagnostics and GPS devices mounted on vehicles, and then these basic data were transmitted to the cloud platform for storage through a 3G network. The user information about ecodriving behaviors was created and stored in a local server. Nine driving events related to ecodriving and an ecodriving score could be detected and estimated. The validation test of 50 taxicab drivers’ fuel consumption of 1 month before and after receiving ecodriving feedback through the smartphone app showed that the effectiveness of the ecodriving app on reducing fuel consumption was statistically significant, with an average reduction of 4.5% and the highest of 13.0%. Furthermore, both the adaptive process at the beginning of and a long-term effect after a period of time were maintained for ecodriving training through the smartphone app. In addition, the relationship between vehicle fuel consumption and app usage frequency was found to be highly linear: fuel consumption decreased as app usage increased. The study results demonstrated a real-time dynamic and practical approach for the ecodriving app and further provided a research platform for monitoring and management of driving behavior in the big data era.

01628860

17-05681

English

pp 57–66

2017

Transportation Research Record: Journal of the Transportation Research Board

9780309460408

Digital/other

Figures (10) ; References (20)

Automatic data collection systems; Driver performance; Ecodriving; Fuel consumption; Mobile applications; Smartphones; Taxicab drivers

Beijing (China)

Data and Information Technology; Operations and Traffic Management; Public Transportation; Safety and Human Factors

TRIS, TRB, ATRI

Dec 8 2016 12:16PM

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