Self-organizing traffic signals using secondary extension and dynamic coordination

Cesme, Burak; Furth, Peter G.

doi:10.1016/j.trc.2014.08.006

Cited by 61 publications

(35 citation statements)

References 15 publications

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“…The simulation traffic network consists of 15 intersections and 76 links constructed in Vissim. The network includes 16 ingress links and 16 exit links, as shown in Figure 8 During the simulation, the green light time of each light phase is assumed to be 21s, which is the pedestrian clearance time (the road width is about 21m, and the pedestrians speed is about 1m/s) [4]. The yellow light time is assumed to be 3s.…”

Section: Simulation and Discussionmentioning

confidence: 99%

“…Next, an actuated traffic control method was proposed to extend the light phase duration according to the detected traffic flow data in real time, using detectors installed at upstream segments. However, the detection of sparse traffic has a considerable influence on delay time [3] and it was applied mainly at isolated intersections [4]. Adaptive traffic control methods (SCOOT [5] and SCATS [6]) were proposed to adjust signal timing plans based on online traffic information for responding to real-time traffic demand.…”

Section: Introductionmentioning

confidence: 99%

“…Although adaptive traffic control systems have been implied in real urban traffic networks, the cooperation of multiple intersections requires a control center, which has obstructed further development. In addition, the centralized signal timing scheme is always calculated according to the current traffic conditions, but is implied in the next cycle when the traffic situation may have already changed [4].…”

Section: Introductionmentioning

confidence: 99%

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Distributed Cooperative Backpressure-Based Traffic Light Control Method

Hao

Yang

Ding

et al. 2019

Journal of Advanced Transportation

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On the foundation of the original backpressure-based traffic light control algorithm, a distributed cooperative backpressure-based traffic light control method is proposed in this paper. The urban traffic network is modeled as a smart agent-controlled queuing network, in which the intersection agents exchange the queue length information and the selected activating light phase information of neighboring intersections through communications and determine the activating light phase at each time slot according to local traffic information. The improved phase pressure computation method considers the phase state of downstream intersections instead of only the queue length of the local intersections. Light phase switching coordination among adjacent intersections is achieved using the consensus-based bundle algorithm, in which the cooperative light phase switching problem is viewed as a task assignment issue among adjacent intersections. Simulation results illustrated that the proposed cooperative backpressurebased traffic light control method obtained better performance than the original backpressure-based and fixed-time traffic control methods.

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Section: Simulation and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Distributed Cooperative Backpressure-Based Traffic Light Control Method

Hao

Yang

Ding

et al. 2019

Journal of Advanced Transportation

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“…The research by Cesme and Furth [25] explores a paradigm "self-organizing signals" for traffic signal control based on local rules that create coordination mechanisms. Simulation tests in VISSIM performed on arterial corridors in Massachusetts and Arizona show overall delay reductions.…”

Section: Related Workmentioning

confidence: 99%

Deliberative Self-Organizing Traffic Lights with Elementary Cellular Automata

2017

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Self-organizing traffic lights have shown considerable improvements compared to traditional methods in computer simulations. Self-organizing methods, however, use sophisticated sensors, increasing their cost and limiting their deployment. We propose a novel approach using simple sensors to achieve self-organizing traffic light coordination. The proposed approach involves placing a computer and a presence sensor at the beginning of each block; each such sensor detects a single vehicle. Each computer builds a virtual environment simulating vehicle movement to predict arrivals and departures at the downstream intersection. At each intersection, a computer receives information across a data network from the computers of the neighboring blocks and runs a self-organizing method to control traffic lights. Our simulations showed a superior performance for our approach compared with a traditional method (a green wave) and a similar performance (close to optimal) compared with a self-organizing method using sophisticated sensors but at a lower cost. Moreover, the developed sensing approach exhibited greater robustness against sensor failures.

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“…The main advantage of actuated control over fixed time control is natural recovery from oversaturation and priority interruptions. When leading to and recovering from temporal oversaturation, actuated control makes full use of capacity, ending the green on stages whose queues has dissipated and switching to stages, which still have a queue (Cesme, Furth 2014). Actuated control has compensation mechanisms making it amenable to aggressive public transport priority.…”

Section: Introductionmentioning

confidence: 99%

Estimating the Effects of Public Transport Priority Measures At Signal Controlled Intersections

Dumbliauskas

Vitkienė

2017

The Baltic Journal of Road and Bridge Engineering

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Most of the Lithuanian cities try to achieve public transport priority by the provision of special dedicated public transport lanes. However, the possible priority measures at signalised intersections receive less attention. This paper explains common signal control strategies applied at isolated intersections in the cities around the world and estimated their effects on the travel times of both, public transport and general traffic. The analysis employs well recognised PTV VISSIM simulation environment and VisVAP graphical programming interface to implement and test priority measures under question. The results indicate that priority actions significantly reduce public transport delays up to 60%, without high adverse impact on general traffic delays.

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Self-organizing traffic signals using secondary extension and dynamic coordination

Cited by 61 publications

References 15 publications

Distributed Cooperative Backpressure-Based Traffic Light Control Method

Distributed Cooperative Backpressure-Based Traffic Light Control Method

Deliberative Self-Organizing Traffic Lights with Elementary Cellular Automata

Estimating the Effects of Public Transport Priority Measures At Signal Controlled Intersections

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