Adaptive Quasi-Dynamic Traffic Light Control

Fleck, Julia L.; Cassandras, Christos G.; Geng, Yanfeng

doi:10.1109/tcst.2015.2468181

Cited by 41 publications

(36 citation statements)

References 31 publications

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“…An analytical solution of problem (14) may be obtained through a Hamiltonian analysis. The presence of constraints (2) and (13) complicates this analysis. Assuming that all constraints are satisfied upon entering the CZ and that they remain inactive throughout [t 0 i , t m i ], a complete solution was derived in [16] and [17] for highway on-ramps, and in [14] for two adjacent intersections.…”

Section: B Analytical Solution Of the Decentralized Optimal Control mentioning

confidence: 99%

Optimal control of Connected Automated Vehicles at urban traffic intersections: A feasibility enforcement analysis

Zhang

Cassandras

Malikopoulos

2017

2017 American Control Conference (ACC)

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Earlier work has established a decentralized optimal control framework for coordinating on line a continuous flow of Connected Automated Vehicles (CAVs) entering a "control zone" and crossing two adjacent intersections in an urban area. A solution, when it exists, allows the vehicles to minimize their fuel consumption while crossing the intersections without the use of traffic lights, without creating congestion, and under the hard safety constraint of collision avoidance. We establish the conditions under which such solutions exist and show that they can be enforced through an appropriately designed "feasibility enforcement zone" that precedes the control zone. The proposed solution and overall control architecture are illustrated through simulation.

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Section: B Analytical Solution Of the Decentralized Optimal Control mentioning

confidence: 99%

Optimal control of Connected Automated Vehicles at urban traffic intersections: A feasibility enforcement analysis

Zhang

Cassandras

Malikopoulos

2017

2017 American Control Conference (ACC)

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“…It is estimated that in 2017, traffic congestion costs U.S. more than $300 billion and drivers in big cities spent more than 100 hours in congestion [1]. To alleviate traffic congestion, various traffic control technologies have been proposed, including variable speed limits [4], [5], dynamic traffic light control [6], [7], and ramp metering [8], [9]. It is worth noting that these technologies all require accurate realtime traffic estimation and prediction.…”

Section: Introductionmentioning

confidence: 99%

A New Microscopic Traffic Model Using a Spring-Mass-Damper-Clutch System

Khasawneh

Yin

et al. 2020

IEEE Trans. Intell. Transport. Syst.

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Microscopic traffic models describe how cars interact with their neighbors in an uninterrupted traffic flow and are frequently used for reference in advanced vehicle control design. In this paper, we propose a novel mechanical system inspired microscopic traffic model using a mass-spring-damper-clutch system. This model naturally captures the ego vehicle's resistance to large relative speed and deviation from a (driver and speed dependent) desired relative distance when following the lead vehicle. Comparing to existing car following (CF) models, this model offers physically interpretable insights on the underlying CF dynamics, and is able to characterize the impact of the ego vehicle on the lead vehicle, which is neglected in existing CF models. Thanks to the nonlinear wave propagation analysis techniques for mechanical systems, the proposed model therefore has great scalability so that multiple mass-spring-damper-clutch system can be chained to study the macroscopic traffic flow. We investigate the stability of the proposed model on the system parameters and the time delay using spectral element method. We also develop a parallel recursive least square with inverse QR decomposition (PRLS-IQR) algorithm to identify the model parameters online. These real-time estimated parameters can be used to predict the driving trajectory that can be incorporated in advanced vehicle longitudinal control systems for improved safety and fuel efficiency. The PRLS-IQR is computationally efficient and numerically stable so it is suitable for online implementation. The traffic model and the parameter identification algorithm are validated on both simulations and naturalistic driving data from multiple drivers. Promising performance is demonstrated.

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“…To date, traffic light control is the prevailing method for coordinating conflicting traffic flows and ensure road safety in urban areas. Recent technological developments include designing adaptive traffic light control systems that can dynamically adjust the signal timing to various context, e.g., [7] and references therein. However, in addition to the obvious infrastructure cost of traffic lights, the efficiency and safety offered by such signaling methods is limited, thus motivating research efforts to explore new approaches capable of enabling smoother traffic flow while ensuring safety.…”

Section: Introductionmentioning

confidence: 99%

Decentralized optimal control of Connected Automated Vehicles at signal-free intersections including comfort-constrained turns and safety guarantees

Yue

Cassandras

2019

Automatica

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We extend earlier work for optimally controlling Connected Automated Vehicles (CAVs) crossing a signal-free intersection by including all possible turns taken so as to optimize a passenger comfort metric along with energy and travel time minimization. We show that it is possible to achieve this goal in a decentralized manner with each CAV solving an optimal control problem, and derive explicit solutions that guarantee collision avoidance and safe distance constraints within a control zone. We investigate the associated tradeoffs between minimizing energy and vehicle travel time, as well as the passenger comfort metric and include extensive simulations to illustrate this framework.

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Adaptive Quasi-Dynamic Traffic Light Control

Cited by 41 publications

References 31 publications

Optimal control of Connected Automated Vehicles at urban traffic intersections: A feasibility enforcement analysis

Optimal control of Connected Automated Vehicles at urban traffic intersections: A feasibility enforcement analysis

A New Microscopic Traffic Model Using a Spring-Mass-Damper-Clutch System

Decentralized optimal control of Connected Automated Vehicles at signal-free intersections including comfort-constrained turns and safety guarantees

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