Intelligent Control to Reduce Vehicle Energy Consumption and Greenhouse Gas Emissions

Chen, Bin

doi:10.1007/978-3-030-91546-9_14

Cited by 2 publications

(1 citation statement)

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“…A two-level hierarchal cooperative control technique that fixed phase duration traffic signal and HEV energy management was used to reduce energy consumption [6]. An overview of various intelligent controls of vehicles to achieve energy savings is shared in [7]. Data about road conditions, overall vehicular traffic, inter-vehicle positioning, or crowding can be fused for considering long-term plans.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

Real-Time Suitable Predictive Control Using SPaT Information from Automated Traffic Lights

Bhat

Chen

2023

Future Transportation

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Traffic intersections throughout the United States combine fixed, semi-actuated, and fully actuated intersections. In the case of the semi-actuated and actuated intersections, uncertainties are considered in phase duration. These uncertainties are due to car waiting queues and pedestrian crossing. Intelligent transportation systems deployed in traffic infrastructure can communicate Signal and Phase Timing messages (SPaT) to vehicles approaching intersections. In the connected and automated vehicle ecosystem, the fuel savings potential has been explored. Prior studies have predominantly focused on fixed time control for the driver. However, in the case of actuated signals, there is a different and significant challenge due to the randomness caused by uncertainties. We have developed a predictive control using the SPaT information communicated from the actuated traffic intersections. The developed MPC-based algorithm was validated using model-based design platforms such as AMBER®, Autonomie®, MATLAB®, and SIMULINK®. It was observed that the proposed algorithm can save energy in a single phase, in multiple phase scenarios, and in compelled stopping at stop signs when employed considering communications.

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Section: Introduction and Literature Reviewmentioning

confidence: 99%