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Open AccessJournal ArticleDOI

Traffic Signal Control with Connected Vehicles

TLDR
A decentralized, fully adaptive traffic control algorithm, the predictive microscopic simulation algorithm, which uses a rolling-horizon strategy in which the phasing is chosen to optimize an objective function over a 15-s period in the future is developed.
Abstract
The operation of traffic signals is currently limited by the data available from traditional point sensors. Point detectors can provide only limited vehicle information at a fixed location. The most advanced adaptive control strategies are often not implemented in the field because of their operational complexity and high-resolution detection requirements. However, a new initiative known as connected vehicles allows the wireless transmission of the positions, headings, and speeds of vehicles for use by the traffic controller. A new traffic control algorithm, the predictive microscopic simulation algorithm, which uses these new, more robust data, was developed. The decentralized, fully adaptive traffic control algorithm uses a rolling-horizon strategy in which the phasing is chosen to optimize an objective function over a 15-s period in the future. The objective function uses either delay only or a combination of delay, stops, and decelerations. To measure the objective function, the algorithm uses a micro...

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Citations
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Journal ArticleDOI

A real-time adaptive signal control in a connected vehicle environment

TL;DR: In this paper, a real-time adaptive signal phase allocation algorithm using connected vehicle data is proposed to optimize the phase sequence and duration by solving a two-level optimization problem, which minimizes the total vehicle delay and minimizes queue length.
Journal ArticleDOI

Using connected vehicle technology to improve the efficiency of intersections

TL;DR: Overall, it is observed that connected vehicle technology could significantly improve the operation of traffic at signalized intersections, at least under the proposed algorithm.
Journal ArticleDOI

Energy saving potentials of connected and automated vehicles

TL;DR: This paper is an attempt to highlight the energy saving potential of connected and automated vehicles based on first principles of motion, optimal control theory, and a review of the vast but scattered eco-driving literature.
Journal ArticleDOI

Urban traffic signal control with connected and automated vehicles: A survey

TL;DR: Six types of CAV-based traffic control methods are summarized and a conceptual mathematical framework is proposed that can be specified to each of six three types of methods by selecting different state variables, control inputs, and environment inputs is proposed.
Journal ArticleDOI

50th Anniversary Invited Article—Autonomous Vehicles and Connected Vehicle Systems: Flow and Operations Considerations

TL;DR: This work explains using elementary traffic science concepts how autonomous vehicles and connected vehicles are expected to increase the throughput of highway facilities, as well as improve the stability of the traffic stream, through a microsimulation framework featuring varying behavioral mechanisms for the three classes of vehicles.
References
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Book

Simulation Modeling and Analysis

TL;DR: The text is designed for a one-term or two-quarter course in simulation offered in departments of industrial engineering, business, computer science and operations research.

Traffic signal settings

F V Webster
TL;DR: In this article, the authors present an approach to evaluate the number of delays at a signal-to-interception intersection and propose a formulae to calculate the average delay per vehicle.

The 100-Car Naturalistic Driving Study Phase II – Results of the 100-Car Field Experiment

TL;DR: The 100-Car Naturalistic Driving Study (100-CARS) as discussed by the authors is a three-phase effort designed to accomplish three objectives: Phase I, conduct test planning activities; Phase II, conduct a field test; and Phase III, prepare for large-scale field data collection effort.
Journal ArticleDOI

A real-time traffic signal control system: architecture, algorithms, and analysis

TL;DR: Real-time traffic-adaptive signal control system referred to as RHODES takes as input detector data for real-time measurement of traffic flow, and “optimally” controls the flow through the network.
Journal Article

Opac: a demand-responsive strategy for traffic signal control

TL;DR: Optimization Policies for Adaptive Control is a computational strategy for real-time demand-responsive traffic signal control that requires on-line data that can be readily obtained from upstream link detectors and is suitable for implementation on existing microprocessors.
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