Eco-driving at signalized intersections using V2I communication

Rakha, Hesham A.; Kamalanathsharma, Raj Kishore

doi:10.1109/itsc.2011.6083084

Cited by 229 publications

(147 citation statements)

References 12 publications

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“…Kamal used the model predictive control for improve vehicle's ecology in varying traffic environment [27]. Rakha designed an eco-driving framework that has detailed microscope fuel consumption and emission model in the objective function [28]. Mensing utilized the dynamic programming approach to optimize the speed trajectories of vehicles [29].…”

Section: Introductionmentioning

confidence: 99%

Eco-Approach and Departure System for Left-Turn Vehicles at a Fixed-Time Signalized Intersection

Jiang¹,

An²,

Jian³

et al. 2018

Sustainability

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Abstract:This research proposed an eco-approach and departure system for left-turn vehicles at a fixed-time signalized intersection. This system gives higher priority to enhancing traffic safety than improving mobility and fuel efficiency, and optimizes the entire traffic consisted of connected and automated vehicles (CAVs) and conventional human-driven vehicles by providing ecological speed trajectories for left-turn CAVs. All the ecological speed trajectories are offline optimized before the implementation of system. The speed trajectory optimization is constructed in Pontryagin's Minimum Principle structure. The before and after evaluation of the proposed system shows the percentage of vehicles that drive pass the intersection at safe speed increases by 2.14% to 45.65%, fuel consumption benefits range 0.53% to 18.44%, emission benefits range from 0.57% to 15.69%, no significant throughput benefits is observed. The proposed system significantly enhances the traffic safety and improves the fuel efficiency and emission reduction of left-turn vehicles with no adverse effect on mobility, and has a good robustness against the randomness of traffic. The investigation also indicates that the computation time of proposed system is greatly reduced compared to previous eco-driving system with online speed optimization. The computation time is up to 0.01 s. The proposed system is ready for real-time application.

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Section: Introductionmentioning

confidence: 99%

Eco-Approach and Departure System for Left-Turn Vehicles at a Fixed-Time Signalized Intersection

Jiang¹,

An²,

Jian³

et al. 2018

Sustainability

View full text Add to dashboard Cite

show abstract

“…The original optimization problem (13) will be now divided into sub-problems for the simplification of constraints (14) and the formulation of a convex optimization problem.…”

Section: Optimization Algorithmmentioning

confidence: 99%

“…Predictive cruise control (PCC) in traffic networks with signalized intersections was extensively treated in [11], where a preliminary logic computes the constant velocity to be tracked by the driver to pass through the as high number of intersections as possible, while penalizing the brakes action to indirectly reduce energy consumption and trip time. In [14] only one traffic light is considered and accelerations upstream and downstream of the intersection are varied to find sub-optimal values for the fuel consumption minimization problem. In [15] Dynamic Programming is used to find the minimum energy solution, for a trip with up to two traffic lights and investigating different timings of the green signal.…”

mentioning

confidence: 99%

Eco-driving in urban traffic networks using traffic signal information

Nunzio

Wit

Moulin

et al. 2013

52nd IEEE Conference on Decision and Control

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“…Barth et al [22] developed a dynamic eco-driving velocity planning algorithm to minimize acceleration/deceleration rates, the total tractive power demand, and the idling time for probe vehicles, so that fuel consumption and emissions can be reduced. Rakha and Kamalanathsharma [23] presented seven examples with different speeds and throttles through a sample scenario with a single signalized intersection. After assuming or calculating the other parameters, they determined which case had the most fuel-optimal speed profile.…”

Section: Introductionmentioning

confidence: 99%

“…In the aforementioned studies, the goal of reducing fuel consumption was usually transformed into simple functions of acceleration/deceleration rates [20,22] or the time of arrival at the intersection [10,21,23] (Sun and Henry, 2015; Wu et al, 2015a, 2015b). None of these models used an explicit objective function to minimize the total fuel consumption.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Eco-Driving Speed Guidance at Signalized Intersections: Multivehicle Driving Simulator Based Experimental Study

Chen

Yan

Sun

et al. 2018

Journal of Advanced Transportation

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Variations in vehicle fuel consumption and gas emissions are usually associated with changes in cruise speed and the aggressiveness of drivers' acceleration/deceleration, especially at traffic signals. In an attempt to enhance vehicle fuel efficiency on arterials, this study developed a dynamic eco-driving speed guidance strategy (DESGS) using real-time signal timing and vehicle positioning information in a connected vehicle (CV) environment. DESGS mainly aims to optimize the fuel/emission speed profiles for vehicles approaching signalized intersections. An optimization-based rolling horizon and a dynamic programming approach were proposed to track the optimal guided velocity for individual vehicles along the travel segment. In addition, a vehicle specific power (VSP) based approach was integrated into DESGS to estimate the fuel consumption and CO 2 emissions. To evaluate the effectiveness of the overall strategy, 15 experienced drivers were recruited to participate in interactive speed guidance experiments using multivehicle driving simulators. It was found that compared to vehicles without speed guidance, those with DESGS had a significantly reduced number of stops and approximately 25% less fuel consumption and CO 2 emissions.

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Eco-driving at signalized intersections using V2I communication

Cited by 229 publications

References 12 publications

Eco-Approach and Departure System for Left-Turn Vehicles at a Fixed-Time Signalized Intersection

Eco-Approach and Departure System for Left-Turn Vehicles at a Fixed-Time Signalized Intersection

Eco-driving in urban traffic networks using traffic signal information

Dynamic Eco-Driving Speed Guidance at Signalized Intersections: Multivehicle Driving Simulator Based Experimental Study

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