Benefit

Implementation of a connected eco-driving traffic signal system can lead to fuel savings of up to nine percent for heavy-duty diesel trucks.

The study, performed in Carson, California, equipped a connected truck with an eco-driving signal that used SPaT information to recommend more efficient acceleration profiles.


07/31/2019
Carson; California; United States


Summary Information

The development of Connected and Automated Vehicles (CAVs) has inspired applications designed to improve existing transportation systems. Connected eco-driving, where drivers are guided to approach and depart from signalized intersections in a way that minimizes unnecessary emissions, takes advantage of Signal Phase and Timing (SPaT) information from traffic signals to communicate with CAVs. Simulation models show emissions reductions of between 10 and 15 percent. However, implementations involving real vehicles are not very common.

Field trials were conducted in the city of Carson, California along two corridors with six connected, signalized intersections, using a connected eco-driving system that was implemented on a heavy-duty diesel truck. The tests were performed in a real traffic environment, though the results were analyzed from a set of four trials where there was no downstream traffic. The four trials were split into "acceleration" scenarios, where the eco-driving system led to the driver predicting a signal change and accelerating to pass through the intersection before the phase turned red, and "deceleration" scenarios, where the eco-driving system led to the driver decelerating in anticipation of a signal change and braking more smoothly.

FINDINGS
Using the US EPA's MOVES model, the researchers concluded that the connected eco-driving system provided nine percent fuel savings in the acceleration scenario and four percent fuel savings in the deceleration scenario.

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Source

Early Findings from Field Trials of Heavy-Duty Truck Connected Eco-Driving System

Author: Wang, Ziran et.al.

Published By: University of California- College of Engineering - Center for Environmental Research and Technology

Source Date: 07/31/2019

URL: https://arxiv.org/pdf/1908.00541.pdf

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Benefit ID: 2019-01391