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.

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.

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.

Traffic Platoon Dispersion Modeling on Arterial Streets

1996 ◽  
Vol 1566 (1) ◽  
pp. 49-53 ◽  
Author(s):  
Abdelaziz Manar ◽  
Karsten G. Baass
Keyword(s):  
Simulation Models ◽  
Traffic Signals ◽  
External Friction ◽  
Dispersion Modeling ◽  
Arterial Streets ◽  
Signal Coordination ◽  
Traffic Volumes ◽  
Platoon Dispersion ◽  
The City ◽  
Maximal Capacity

Platoon dispersion is a key element in traffic simulation models designed to measure arrivals at traffic signals. One of the most popular models is contained in the TRANSYT program. In this program, dispersion is defined by the platoon dispersion factor, which is given for three types of conditions in relation to external friction. This study demonstrates that platoon dispersion depends not only on external friction but also on internal friction between vehicles in the platoon. As volumes and densities increase, platoon dispersion increases up to a maximum, which is attained at half the capacity. As volumes and densities increase further, dispersion decreases and reaches a minimum value at volumes around maximal capacity. Experimental analysis on eight arterial sites in the city of Montreal (Quebec, Canada) has confirmed this relationship between dispersion and traffic volumes. Mathematical models (having a parabolic shape) relating platoon dispersion to internal and external friction were developed for three different categories of arterial streets representing low, moderate, and heavy friction levels. These models could be introduced into signal coordination programs and could contribute to a better simulation of arriving platoons at intersections as volumes change in relation to time.

scholarly journals Adaptive Traffic Signal Control Model on Intersections Based on Deep Reinforcement Learning

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Duowei Li ◽  
Jianping Wu ◽  
Ming Xu ◽  
Ziheng Wang ◽  
Kezhen Hu
Keyword(s):  
Reinforcement Learning ◽  
Waiting Time ◽  
Traffic Signals ◽  
Control Model ◽  
Traffic Signal ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Average Waiting Time ◽  
Adaptive Traffic Signal Control ◽  
Proposed Model

Controlling traffic signals to alleviate increasing traffic pressure is a concept that has received public attention for a long time. However, existing systems and methodologies for controlling traffic signals are insufficient for addressing the problem. To this end, we build a truly adaptive traffic signal control model in a traffic microsimulator, i.e., “Simulation of Urban Mobility” (SUMO), using the technology of modern deep reinforcement learning. The model is proposed based on a deep Q-network algorithm that precisely represents the elements associated with the problem: agents, environments, and actions. The real-time state of traffic, including the number of vehicles and the average speed, at one or more intersections is used as an input to the model. To reduce the average waiting time, the agents provide an optimal traffic signal phase and duration that should be implemented in both single-intersection cases and multi-intersection cases. The co-operation between agents enables the model to achieve an improvement in overall performance in a large road network. By testing with data sets pertaining to three different traffic conditions, we prove that the proposed model is better than other methods (e.g., Q-learning method, longest queue first method, and Webster fixed timing control method) for all cases. The proposed model reduces both the average waiting time and travel time, and it becomes more advantageous as the traffic environment becomes more complex.

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 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 Bandwidth optimization for lane-based traffic signal settings with improved stopping criteria in non-linear TRANSYT delay

2019 ◽  
Vol 272 ◽  
pp. 01049
Author(s):  
C K Wong ◽  
Yi Liu ◽  
Yixin Shen
Keyword(s):  
Branch And Bound ◽  
Traffic Signals ◽  
Traffic Signal ◽  
Mixed Integer ◽  
Branch And Bound Method ◽  
Travel Times ◽  
Stopping Criteria ◽  
Mixed Integer Linear Program ◽  
Bandwidth Optimization ◽  
Traffic Volumes

While assigning given OD demand flows onto network links, travel times along different routes could be varied depending on respective traffic volumes. To achieve equilibrium, all used routes should have the minimum and identical travel times. Such route travel times are composed by link travel times and end of link delay. Upstream and downstream traffic signals are coordinated through bandwidth maximization. Path flows and path travel times are modeled to be responsive to traffic signal settings to enable attractive path choices. Approximated linear function will be established to linearize the end of link delay in TRANSYT model. The problem is formulated as a Binary-Mixed-Integer-Linear-Program and could be solved by standard branch-and-bound method.

scholarly journals Unconventional Intersection Designs for Improving Traffic Operation Along Arterial Roads

2021 ◽  
Author(s):  
Taqwa Hadidi ◽  
Hana Naghawi ◽  
Khair Jadaan
Keyword(s):  
Heavy Traffic ◽  
Travel Speed ◽  
Construction Cost ◽  
Simulation Software ◽  
Signalized Intersection ◽  
Operational Performance ◽  
Microscopic Simulation ◽  
Arterial Road ◽  
Traffic Volumes ◽  
Traffic Operation

The main objective of this paper is to evaluate the effect of implementing four Unconventional Arterial Intersection Designs (UAIDs) including median U-Turn, Superstreet, Jughandle and Single Quadrant Intersection on a major arterial road using SYNCHRO microscopic simulation software. For this purpose, Wadi Saqra Signalized Intersection on Shaker Bin Zaid major arterial road in Amman, Jordan was selected. The simulation results showed that only the Jughandle improved the intersection Level of Service (LOS) slightly, F–E. Nevertheless, the intersection delay was significantly reduced by 64.81%, 76.6%, 91.28% and 75.60% on the proposed Median U-Turn, Superstreet, Jughandle and Single Quadrant unconventional intersection design, respectively. This indicated that these UAIDs don't perform well under heavy traffic volumes. Also, since the Jughandle was the only UAID which improved the LOS on the main intersection, the operational performance of Prince Shaker Bin Zaid arterial after implementing the Jughandle at the main intersection was evaluated including the main intersection: Wadi Saqra intersection, one prior to the main intersection and one after the main intersection. It was found that the use of the Jughandle increased the average travel speed by 35% and decreased the average stopped delay by 28.68% on the arterial road. Also, this paper evaluated the current transportation system and road user's attitude towards UAIDs' implementation through a questionnaire survey. The results indicated high acceptance of UAIDs. Finally, the construction cost for each UAID type was estimated. It was found that the Jughandle had the highest construction cost due to its high acquisition cost.

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