Eco approaching at an isolated signalized intersection under partially connected and automated vehicles environment

Jiang, Huifu; Hu, Jia; An, Shi; Wang, Meng; Park, Byungkyu Brian

doi:10.1016/j.trc.2017.04.001

Cited by 262 publications

(141 citation statements)

References 23 publications

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“…The main idea is to iteratively find state x forward in time and then co-state λ backward in time. Interested readers could refer to these papers [9,18,35] for the detailed algorithm.…”

Section: Conditions and Constraintsmentioning

confidence: 99%

“…As described before, the eco-approach control system proposed by Jiang and Hu could control the straight-going traffic under partially connected and automated vehicles environmental, and can generate optimal speed trajectories within a relative short computation time [35]. This system is more feasible for implementation in the near future and has potential to be improved to control the turning vehicles in real time.…”

Section: Introductionmentioning

confidence: 98%

“…Based on this idea, Jiang designed a similar system that is able to function under partially connected and automated vehicles environment by utilizing the impacts of connected and automated vehicles on conventional human-driven vehicles. This system shows a good performance under low market penetration of connected and automated vehicles and good robustness for traffic randomness, and is feasible for implementation in the near future [35].…”

Section: Introductionmentioning

confidence: 99%

“…To obtain the optimal speed trajectories with less computation time so as to minimize the fuel consumption, Wang, Hu and Jiang constructed the optimization problem in Pontryagin's Minimum Principle structure and use a bi-directional iteration approach to accelerate the solving stage. The computation time in these studies was reduced to 10 −1~1 0 1 s, which means these methods can potentially be used in real-time control on connected and automated vehicles with low control frequency (≤10 Hz) [8,12,13,35].…”

Section: Introductionmentioning

confidence: 99%

“…This module is activated when there is a conventional vehicle detected by the loop detector. Similar to module 2, this module also collect signal timing, conventional vehicle's current position and speed, preceding vehicle's speed and spatial-temporal trajectories as inputs, and then make a prediction of the conventional future speed and spatial-temporal trajectories by utilizing an improved Intelligent Driver Model (IDM) for signalized intersection proposed in previous study [35]. The predicted results are all stored in vehicle information for future use.…”

mentioning

confidence: 99%

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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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“…The main idea is to iteratively find state x forward in time and then co-state λ backward in time. Interested readers could refer to these papers [9,18,35] for the detailed algorithm.…”

Section: Conditions and Constraintsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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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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Real‐time control of connected vehicles in signalized corridors using pseudospectral convex optimization

Shi

Wang

LaClair

et al. 2023

Optim Control Appl Methods

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Recent advances in Connected and Automated Vehicle (CAV) technologies have opened up new opportunities to enable safe, efficient, and sustainable transportation systems. However, developing reliable and rapid speed control algorithms in highly dynamic environments with complex inter‐vehicle interactions and nonlinear vehicle dynamics is still a daunting task. In this paper, we develop a novel speed control method for CAVs to produce optimal speed profiles that minimize the fuel consumption and avoid idling at signalized intersections. To this end, an optimal control problem is formulated using the information of the upcoming traffic signal to adapt vehicles' speeds to avoid frequent stop‐and‐go driving patterns. By applying the pseudospectral discretization method and the sequential convex programming method, the computational efficiency is greatly improved, enabling potential real‐time on‐vehicle applications. In addition, the algorithm is implemented under a model predictive control framework to ensure online control with instant response for collision avoidance and robust vehicle coordination. The proposed algorithm is verified through numerical simulations of three different traffic scenarios. The convergence and accuracy of the proposed approach are demonstrated by comparing with a popular nonlinear solver. Furthermore, the benefit of the proposed method in both traffic mobility and fuel efficiency is validated using the speed profile determined from a traffic following model in a simulation software as the baseline.

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Combating Road Traffic Congestion with Big Data: A Bibliometric Review and Analysis of Scientific Research

Dogo

Makaba

Afolabi

et al. 2021

Towards Connected and Autonomous Vehicle Highways

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Eco approaching at an isolated signalized intersection under partially connected and automated vehicles environment

Cited by 262 publications

References 23 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

Real‐time control of connected vehicles in signalized corridors using pseudospectral convex optimization

Combating Road Traffic Congestion with Big Data: A Bibliometric Review and Analysis of Scientific Research

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