scholarly journals Remarks on Traffic Signal Coordination

10.29007/flbm ◽  
2019 ◽  
Author(s):  
Peter Wagner ◽  
Robert Alms ◽  
Jakob Erdmann ◽  
Yun-Pang Flötteröd
Keyword(s):  
Transport System ◽  
Traffic Signals ◽  
Transportation Systems ◽  
Traffic Signal ◽  
Signal Set ◽  
Signal Coordination ◽  
Set Up ◽  
Good Organization

The co-ordination between traffic signals is assumed to be important for the good organization of a transport system. By using an artificial approach to create and analyze a multitude of transportation systems, a few different simple traffic signals programs has been put to the test and compared to each other. The result is that a well co-ordinated system can be outperformed by a non-coordinated signal set-up, where all signals controlers run in (single intersection) actuated mode. Clearly, these results are preliminary and require more investigation.

scholarly journals Multi-Agent Reinforcement Learning for Optimizing Traffic Signal Timing

2021 ◽  
Author(s):  
Areej Salaymeh ◽  
Loren Schwiebert ◽  
Stephen Remias
Keyword(s):  
Reinforcement Learning ◽  
Traffic Signals ◽  
Transportation Systems ◽  
Traffic Signal ◽  
Urban Traffic ◽  
Signal Timing ◽  
Model Free ◽  
Proposed Model ◽  
Multi Agent ◽  
Traffic Signal Timing

Designing efficient transportation systems is crucial to save time and money for drivers and for the economy as whole. One of the most important components of traffic systems are traffic signals. Currently, most traffic signal systems are configured using fixed timing plans, which are based on limited vehicle count data. Past research has introduced and designed intelligent traffic signals; however, machine learning and deep learning have only recently been used in systems that aim to optimize the timing of traffic signals in order to reduce travel time. A very promising field in Artificial Intelligence is Reinforcement Learning. Reinforcement learning (RL) is a data driven method that has shown promising results in optimizing traffic signal timing plans to reduce traffic congestion. However, model-based and centralized methods are impractical here due to the high dimensional state-action space in complex urban traffic network. In this paper, a model-free approach is used to optimize signal timing for complicated multiple four-phase signalized intersections. We propose a multi-agent deep reinforcement learning framework that aims to optimize traffic flow using data within traffic signal intersections and data coming from other intersections in a Multi-Agent Environment in what is called Multi-Agent Reinforcement Learning (MARL). The proposed model consists of state-of-art techniques such as Double Deep Q-Network and Hindsight Experience Replay (HER). This research uses HER to allow our framework to quickly learn on sparse reward settings. We tested and evaluated our proposed model via a Simulation of Urban MObility simulation (SUMO). Our results show that the proposed method is effective in reducing congestion in both peak and off-peak times.

scholarly journals Traffic signal coordination for Wellington Street West, Toronto, Ontario

2021 ◽  
Author(s):  
Sharareh Shadbakhsh
Keyword(s):  
Traffic Congestion ◽  
Road Traffic ◽  
Green Light ◽  
Traffic Signals ◽  
Traffic Signal ◽  
Continuous Series ◽  
Signal Timing ◽  
Signal Coordination ◽  
Road Users ◽  
Levels Of Service

The increasing volume of traffic in cities has a significant effect on road traffic congestion and the travel time it takes for road users to reach their destinations. Coordinating traffic signals, which is a system of light that cascade in sequence where a platoon of vehicles can travel through a continuous series of green light without stopping, can improve the driver's experience significantly. This report covers the development of a coordinated traffic signal system along Wellington Street West from Church Street to Blue Jays Way Street as part of a City of Toronto signal coordination project. The objective of this study is to improve coordination through modification of signal timing plans while maintaining reasonably minimal impacts to the side street levels of service and delays. The overall goal is to reduced travel times, delays, number of stops and fuel consumption, resulting in public benefit.

scholarly journals Traffic signal coordination for Wellington Street West, Toronto, Ontario

2021 ◽  
Author(s):  
Sharareh Shadbakhsh
Keyword(s):  
Traffic Congestion ◽  
Road Traffic ◽  
Green Light ◽  
Traffic Signals ◽  
Traffic Signal ◽  
Continuous Series ◽  
Signal Timing ◽  
Signal Coordination ◽  
Road Users ◽  
Levels Of Service

The increasing volume of traffic in cities has a significant effect on road traffic congestion and the travel time it takes for road users to reach their destinations. Coordinating traffic signals, which is a system of light that cascade in sequence where a platoon of vehicles can travel through a continuous series of green light without stopping, can improve the driver's experience significantly. This report covers the development of a coordinated traffic signal system along Wellington Street West from Church Street to Blue Jays Way Street as part of a City of Toronto signal coordination project. The objective of this study is to improve coordination through modification of signal timing plans while maintaining reasonably minimal impacts to the side street levels of service and delays. The overall goal is to reduced travel times, delays, number of stops and fuel consumption, resulting in public benefit.

Coordinating Traffic Signals for Bicycle Progression

2000 ◽  
Vol 1705 (1) ◽  
pp. 85-92 ◽  
Author(s):  
Dean B. Taylor ◽  
Hani S. Mahmassani
Keyword(s):  
Design Problem ◽  
Traffic Signals ◽  
Traffic Signal ◽  
Mixed Traffic ◽  
Conceptual Foundation ◽  
Signal Coordination

Traffic signal coordination that provides either ( a) progression for bicycles or ( b) simultaneous progression for bicycles and automobiles traveling on the same facility is analyzed. A conceptual foundation, consisting of three primary contributions, is developed for analyzing bicycleautomobile mixed-traffic progression along signalized streets. First, the principal considerations for bicycle progression are articulated. Second, several concepts and techniques that provide improved (or alternative) multiobjective solutions are presented and analyzed. Third, a multiobjective formulation framework for solving the mixed-traffic design problem is proposed. This framework formally incorporates the elements that were introduced as part of the first two contributions and provides a method to handle the inherent competing objectives of the situation. Additionally, important practical aspects of designing and implementing bicycle progression systems, such as handling bicycle speed variability and selecting appropriate facilities for initial (or test) projects, are identified and discussed.

scholarly journals Traffic Signal Coordination for Tramlines with Passive Priority Strategy

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Yun Bai ◽  
Jiajie Li ◽  
Tang Li ◽  
Lingling Yang ◽  
Chenxi Lyu
Keyword(s):  
Dwell Time ◽  
Coordinated Control ◽  
Traffic Signals ◽  
Travel Speed ◽  
Simulation Software ◽  
Traffic Signal ◽  
Model Case ◽  
Signal Coordination ◽  
Proposed Model ◽  
Traffic Volumes

Prioritizing traffic signals for trams crossing intersections without stops can increase the service punctuality and travel speed of trams, but it may also increase the delays of other vehicles at intersections. This paper presents a model on coordinated control of traffic signals among successive intersections along the tramline, taking into account driving characteristics of trams and vehicles. The objective is maximizing the valid bandwidth of vehicle green wave to reduce vehicle delays, while the trams cross intersections without stops. Linear Interactive and General Optimizer (LINGO) is applied to solve the proposed model and VISSIM simulation software is adopted to assess the solutions attained by the proposed model and the previous TRAMBAND model. Case studies show that the solutions given by the proposed model facilitate trams to go through all intersections along the tramline without stops. In comparison with the TRAMBAND model, the proposed model reduces tram delay by 13.14 s/pcu and increases the throughput of vehicles at intersections by 4.45% and reduces vehicle delays by 2.22%. Extensive simulations have verified that the performance of the proposed model is stable under different tram headways, dwell time, and traffic volumes. It is also found that the tram headway must be multiple of traffic signal cycle time to completely realize green wave control of all trams at all intersections along the tramline.

Recent Advances in Reinforcement Learning for Traffic Signal Control

2021 ◽  
Vol 22 (2) ◽  
pp. 12-18 ◽  
Author(s):  
Hua Wei ◽  
Guanjie Zheng ◽  
Vikash Gayah ◽  
Zhenhui Li
Keyword(s):  
Reinforcement Learning ◽  
Real World ◽  
Intelligent Transportation Systems ◽  
Transportation Systems ◽  
Traffic Signal ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Control Methods ◽  
Advantages And Disadvantages ◽  
Recent Advances

Traffic signal control is an important and challenging real-world problem that has recently received a large amount of interest from both transportation and computer science communities. In this survey, we focus on investigating the recent advances in using reinforcement learning (RL) techniques to solve the traffic signal control problem. We classify the known approaches based on the RL techniques they use and provide a review of existing models with analysis on their advantages and disadvantages. Moreover, we give an overview of the simulation environments and experimental settings that have been developed to evaluate the traffic signal control methods. Finally, we explore future directions in the area of RLbased traffic signal control methods. We hope this survey could provide insights to researchers dealing with real-world applications in intelligent transportation systems

Smart Traffic Light System

2021 ◽  
Vol 9 (9) ◽  
pp. 679-686
Author(s):  
Rashi Maheshwari
Keyword(s):  
Traffic Congestion ◽  
Traffic Signals ◽  
Traffic Monitoring ◽  
Traffic Signal ◽  
Traffic Signal Control ◽  
Traffic Light ◽  
Mathematical Functions ◽  
Light System ◽  
Smart Traffic ◽  
And Control

Abstract: Traffic signal control frameworks are generally used to monitor and control the progression of cars through the intersection of roads. Moreover, a portable controller device is designed to solve the issue of emergency vehicles stuck in overcrowded roads. The main objective of this paper is to design and implement a suitable algorithm and its simulation for an intelligent traffic signal simulator. The framework created can detect the presence or nonappearance of vehicles within a specific reach by setting appropriate duration for traffic signals to react accordingly. By employing mathematical functions and algorithms to ascertain the suitable timing for the green signal to illuminate, the framework can assist with tackling the issue of traffic congestion. The explanation relies on recent fixed programming time. Keywords: Smart Traffic Light System, Smart City, Traffic Monitoring.

scholarly journals Integrated Passenger Transport System in Rural Areas – A Literature Review

2020 ◽  
Vol 32 (6) ◽  
pp. 863-873
Author(s):  
Branimir Maretić ◽  
Borna Abramović
Keyword(s):  
Literature Review ◽  
Transport System ◽  
Rural Areas ◽  
Urban Areas ◽  
Planning System ◽  
Passenger Transport ◽  
Public Transport System ◽  
Urban And Rural Areas ◽  
Set Up ◽  
The Impact

The planning and organisation of public passenger transport in rural areas is a complex process. The transport demand in rural areas is often low, which makes it hard to establish and run a financially sustainable public transport system. A solution is integrated passenger transport that eliminates deficiencies and provides benefits for all participants in the public passenger transport process. This paper describes the impact of integrated passenger transport on mobility in rural areas and critically evaluates different literature sources. Integration of passenger transport in urban areas has been described in the context of rural areas, and the challenges of integration of public passenger transport specific to rural areas have been analysed. Through the application in urban and rural areas, the planning of integrated and non-integrated passenger transport has been functionally analysed. The analysis found an increase in the degree of mobility in the areas that use integrated passenger transport compared to the non-integrated one. This research of the literature review has identified the rural areas of mobility as under-researched. The mobility research can set up a more efficient passenger transport planning system in rural areas.

Numerical Analysis of Tunnel Support System at Pune Metro

2021 ◽  
Vol 9 (VII) ◽  
pp. 3681-3687
Author(s):  
Saurabh B. Yele
Keyword(s):  
Transport System ◽  
Support System ◽  
Public Transport ◽  
Transportation Systems ◽  
Vital Role ◽  
Industrial Growth ◽  
Rapid Urbanization ◽  
Tunnel Support ◽  
Underground Tunnel ◽  
Public Transport System

Pune has witnessed enormous industrial growth, rapid urbanization in the recent past and has put the city's travel infrastructure to stress. Being a densely populated area, Pune's traffic needs cannot be met by road-based transportation systems and additional flyovers. Considering this, the Pune Metro project a strong public transport system partly elevated, and partly underground Line 1 and the completely elevated Line 2 has been discussed and undertaken by Maha Metro Rail Corporation. With the rise in demand, the responsibility for a safe and efficient public transport system also increases hence proper planning, designing, and execution play a vital role. The underground tunnel stretch of the Pune Metro Line 1 project is carried out by TBM and by segmental lining as a support system. By geotechnical parameters and FEM, RS2 software author analyses the ground behaviour and support system and conveys a basic understanding of ground behaviour and results in guidelines for designing the underground tunnel.

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