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.

scholarly journals Traffic Light Optimization using OpenCV

2020 ◽  
Vol 6 (12) ◽  
pp. 171-175
Author(s):  
Aditya Lahoty
Keyword(s):  
Real Time ◽  
Waiting Time ◽  
Traffic Congestion ◽  
Computer Software ◽  
Green Light ◽  
Traffic Signals ◽  
Signalized Intersections ◽  
Traffic Signal ◽  
Traffic Light ◽  
Real Time Traffic

Traffic Light Optimization aims to find the solution for an increased amount of unnecessary waiting time on traffic signals. Traffic Signal Optimization is the process of changing the timing parameters relative to the length of the green light for each traffic movement and the timed relationship between signalized intersections using a computer software program. Our project aims to set the timer of green light based on real-time traffic congestion i.e. number of vehicles in a particular direction of the traffic light. To work in this project, we are using the OpenCV method to detect vehicles and then perform our calculation in the algorithm to predict the time for the green light to be in an active state.

scholarly journals The role of optimization to control traffic signals setting on capacity and flow at peak hours at intersections

2015 ◽  
Vol 4 (3) ◽  
pp. 432
Author(s):  
Pegah Jafari Haghighatpour ◽  
Ali Mansourkhaki ◽  
Gholamreza Mehdizadeh ◽  
Mahmouddreza Keymanesh
Keyword(s):  
Traffic Congestion ◽  
Traffic Signals ◽  
Traffic Signal ◽  
Control Measures ◽  
Modular System ◽  
Signal Timing ◽  
Peak Time ◽  
Central System ◽  
Traffic Signal Timing ◽  
Freeway Networks

Control the pre timing of traffic signals has many advantages because of its responsiveness to traffic demands, short cycles, and effective use of capacity leading to and recovering from oversaturation and amenability to aggressive transit priority. Traffic congestion in urban road and freeway networks leads to a strong degradation of the network infrastructure and accordingly reduced throughput, which can be countered via suitable control measures and strategies. Coordination between intersections in a central system increases capacity, appropriate traffic flow and reduce total delays of vehicles. Scats system has been installed in many world intersections, and many researchers have done about the advantages of it to decrease delays and travel times at intersection. SCATS is a modular system and development of this is possible. Now in Tehran's this system is used and traffic conditions matches on it. Traffic signal timing schedule gives in this system as default and although this system is capable of adapting to the moment traffic but in terms of super saturation and during peak hours due to the lack of optimization, default program around intersection has caused widespread congestion at intersection. In this paper, two intersections of East and West of Tehran have been selected, and in two different situations, the flow to capacity ratio of traffic signal timing has been investigated before and after optimization. Simulation by AIMSUN and optimization by SYNCHRO software is done. After optimization can be observed that if before the pre-defined schedule for SCATS, this plan for each intersection of the volume of traffic at peak hours has been optimized, a great reduction in delay and increase in capacity can be observed at intersections. For example, delay time reduction has been occurred about 14.77 in AM peak time and 12.65 in PM peak time at GOLBARG-DARDASHT intersection.

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 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 An Intelligent Fuzzy Logic Based Traffic Controller

2020 ◽  
Keyword(s):  
Fuzzy Logic ◽  
Cycle Time ◽  
Traffic Congestion ◽  
Carbon Dioxide Emissions ◽  
Road Traffic ◽  
Green Light ◽  
Traffic Lights ◽  
Road Congestion ◽  
Light Duration ◽  
Matlab Programming

Increasing road congestion, travel time, number of accidents, carbon dioxide emissions, and fuel consumption are some of the consequences of growth in the vehicle population. Therefore, intelligent traffic controllers are required to solve road traffic congestion problems. The results of prevalent methods, including preset cycle time controller and vehicle-actuated controller, indicated that they do not effectively perform at traffic peak moments. Therefore, due to the deficiency of common methods, fuzzy logic based traffic signal controllers have attracted a lot of attention among researchers. In this article, a fuzzy logic based algorithm for 4-way intersections is proposed and it consists of two main stages for sorting the phase and determining the green light duration. The proposed system is simulated in the MATLAB programming environment and the performance of the designed controller and a conventional controller is compared for some of the presumed conditions. The results of applying the proposed system indicate that this algorithm has a better performance in different traffic conditions in contrast to a preset cycle time controller and it can reduce the number of vehicles behind traffic lights at intersections and the waiting time of passengers.

scholarly journals Traffic signal coordination control along oversaturated two-way arterials

2020 ◽  
Vol 6 ◽  
pp. e319
Author(s):  
Haitao Xu ◽  
Zuozhang Zhuo ◽  
Jing Chen ◽  
Xujian Fang
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Control Method ◽  
Traffic Signal ◽  
Coordination Control ◽  
Minimization Method ◽  
Traffic Condition ◽  
Traffic Demand ◽  
Signal Coordination ◽  
Arterial Coordination

As an effective method to alleviate traffic congestion, traffic signal coordination control has been applied in many cities to manage queues and to regulate traffic flow under oversaturated traffic condition. However, the previous methods are usually based on two hypotheses. One is that traffic demand is constant. The other assumes that the velocity of vehicle is immutable when entering the downstream section. In the paper, we develop a novel traffic coordination control method to control the traffic flow along oversaturated two-way arterials without both these hypotheses. The method includes two modules: intersection coordination control and arterial coordination control. The green time plan for all intersections can be obtained by the module of intersection coordination control. The module of arterial coordination control can optimize offset plan for all intersections along oversaturated two-way arterials. The experiment results verify that the proposed method can effectively control the queue length under the oversaturated traffic state. In addition, the delay in this method can be decreased by 5.4% compared with the existing delay minimization method and 13.6% compared with the traffic coordination control method without offset optimization. Finally, the proposed method can balance the delay level of different links along oversaturated arterial, which can directly reflect the efficiency of the proposed method on the traffic coordination control under oversaturated traffic condition.

scholarly journals Integrating Data Mining and Microsimulation Modelling to Reduce Traffic Congestion: A Case Study of Signalized Intersections in Dhaka, Bangladesh

Urban Science ◽  
2019 ◽  
Vol 3 (2) ◽  
pp. 41 ◽  
Author(s):  
S.M. Labib ◽  
Hossain Mohiuddin ◽  
Irfan Mohammad Al Hasib ◽  
Shariful Hasnine Sabuj ◽  
Shrabanti Hira
Keyword(s):  
Data Mining ◽  
Traffic Congestion ◽  
Traffic Signals ◽  
Fixed Time ◽  
Travel Speed ◽  
Signalized Intersections ◽  
Signal Timing ◽  
Data Set ◽  
Video Footage ◽  
Transportation Technologies

A growing body of research has applied intelligent transportation technologies to reduce traffic congestion at signalized intersections. However, most of these studies have not considered the systematic integration of traffic data collection methods when simulating optimum signal timing. The present study developed a three-part system to create optimized variable signal timing profiles for a congested intersection in Dhaka, regulated by fixed-time traffic signals. Video footage of traffic from the studied intersection was analyzed using a computer vision tool that extracted traffic flow data. The data underwent a further data-mining process, resulting in greater than 90% data accuracy. The final data set was then analyzed by a local traffic expert. Two hybrid scenarios based on the data and the expert’s input were created and simulated at the micro level. The resultant, custom, variable timing profiles for the traffic signals yielded a 40% reduction in vehicle queue length, increases in average travel speed, and a significant overall reduction in traffic congestion.

Sign in / Sign up

Export Citation Format

Share Document