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 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 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 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.

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.

Evaluating the Operational Efficiency of Two Versions of Super Diverging Diamond Interchange Design: A Case Study in Denver, Colorado

2021 ◽  
pp. 036119812110372
Author(s):  
Muhammad Tahmidul Haq ◽  
Amirarsalan Mehrara Molan ◽  
Khaled Ksaibati
Keyword(s):  
Research Effort ◽  
Traffic Signals ◽  
Operational Efficiency ◽  
Traffic Demand ◽  
Operational Analysis ◽  
Signal Coordination ◽  
Traffic Volumes ◽  
Microsimulation Models ◽  
Better Than

This paper aims to advance the current research on the new super diverging diamond interchange (super DDI) design by evaluating the operational efficiency using real-world locations. As part of a comprehensive research effort on improving the performance of failing service interchanges in the mountain-plains region, the study identified three interchanges (Interstate 225 and Mississippi Avenue, Interstate 25 and 120th Avenue, and Interstate 25 and Hampden Avenue) at Denver, Colorado as the potential candidates to model for future retrofit. Four interchange designs (i.e., existing CDI [conventional diamond interchange], DDI, super DDI-1, and super DDI-2) were tested in this study. The operational analysis was conducted using VISSIM and Synchro. Several microsimulation models (120 scenarios with 600 runs in total) were created with three peak hours (a.m., noon, and p.m.) for existing (the year 2020) and projected (the year 2030) traffic volumes. The study considered two simulation networks: (1) when no adjacent traffic signal exists, to determine how the four interchange designs would perform if there were no adjacent signals or they were far away from the interchange; and (2) when there are two adjacent traffic signals, to evaluate the performance of the four interchanges in a bigger corridor with signal coordination needed. An important finding is that super DDI designs outperformed DDI with adjacent signals and higher traffic demand, while DDI performed similarly to or sometimes insignificantly better than super DDI if no adjacent intersections were located in the vicinity and if the demand was lower than the DDI’s capacity.

Start-Up Delays of Queued Vehicles

2005 ◽  
Vol 1934 (1) ◽  
pp. 125-131
Author(s):  
Gary Long
Keyword(s):  
Leading Edge ◽  
Past Research ◽  
Field Studies ◽  
Traffic Signals ◽  
Traffic Signal ◽  
Average Delay ◽  
Start Up ◽  
Delay Times ◽  
Time Required ◽  
Saturation Flow

Start-up delays of queued vehicles have been studied in past research for evaluation of their impacts on saturation flow rates at downstream traffic signals. A more crucial issue, however, can be the effect of start-up delays of queued vehicles at upstream locations where queued vehicles back up from a traffic signal across a railroad crossing. The relationship between queue start-up delays and track clearance times is important in establishing traffic signal preemption settings. This paper presents models that are developed for prediction of the expected maximum time required to mobilize a queue of any length. The models consider not only the average delay times but also the limiting delay times that are expected to accommodate high proportions of queues. For design convenience, queue lengths are converted into distance from the leading edge of a queue rather than being described only by the number of vehicles in a queue. Because the variations in start-up times, in addition to the average times reported in the literature, are needed, two sets of field studies were used to obtain data for model calibration and to investigate various traffic operation effects. Other factors that might be expected to influence queue start-up times are also analyzed.

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