scholarly journals Traffic Signal Control with Connected Vehicles

2020 ◽  
Author(s):  
Noah J. Goodall ◽  
Brian L. Smith ◽  
B. Brian Park
Keyword(s):  
Adaptive Control ◽  
Objective Function ◽  
Traffic Control ◽  
Control Algorithm ◽  
Control Strategies ◽  
Traffic Signal Control ◽  
Connected Vehicles ◽  
Microscopic Simulation ◽  
Improved Performance ◽  
Vehicle Information

The operation of traffic signals is currently limited by the data available from traditional point sensors. Point detectors, often in-ground inductive loop sensors, can provide only limited vehicle information at a fixed location. The most advanced adaptive control strategies are often not implemented in the field due to their operational complexity and high-resolution detection requirements. However, a new initiative known as connected vehicles would allow for the wireless transmission of vehicles’ positions, headings, and speeds to be used by the traffic controller. A new traffic control algorithm, the predictive microscopic simulation algorithm (PMSA), was developed in this research to utilize these new, more robust data. The decentralized, fully adaptive traffic control algorithm uses a rolling horizon strategy, where the phasing is chosen to optimize an objective function over a 15-second period in the future. The objective function uses either delay-only, or a combination of delay, stops, and decelerations. To measure the objective function, the algorithm uses a microscopic simulation driven by present vehicle positions, headings, and speeds. Unlike most adaptive control strategies, the algorithm is relatively simple, does not require point detectors or signal-to-signal communication, and is completely responsive to immediate vehicle demands. To ensure drivers’ privacy, the algorithm stores no memory of individual or aggregate vehicle locations. Results from simulation show that the algorithm maintains or improves performance compared to a state-of-practice coordinated-actuated timing plan optimized by Synchro at low- and mid-level volumes, but performance worsens during saturated and oversaturated conditions. Testing also showed improved performance during periods of unexpected high demand and the ability to automatically respond to year-to-year growth without retiming.

Evaluation of New Jersey Route 18 OPAC/MIST Traffic-Control System

1997 ◽  
Vol 1603 (1) ◽  
pp. 150-155 ◽  
Author(s):  
Christina M. Andrews ◽  
S. Manzur Elahi ◽  
James E. Clark
Keyword(s):  
Adaptive Control ◽  
New Jersey ◽  
Traffic Control ◽  
Intelligent Transportation Systems ◽  
Control Strategies ◽  
Time Of Day ◽  
Transportation Systems ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Traffic Demand

Conventional traffic-control strategies have limitations in handling unanticipated traffic demands. An adaptive traffic-signal control is expected to mitigate this problem and improve overall system performance. Furthermore, with the increasing needs of evolving intelligent transportation systems, traffic signals are expected to provide significantly greater functionalities, which can be achieved only by adaptive control. A product of many years of development, Optimized Policies for Adaptive Control (OPAC) represents a significant step forward in adaptive signal-control research. The OPAC strategy was field-tested at a New Jersey site. The performance of OPAC was compared against a well-designed time-of-day signal control. The evaluation was performed under various traffic-demand conditions and included both isolated intersections and arterial sections. The analysis indicated a highly significant improvement with OPAC control. OPAC showed its best performance during oversaturated conditions. It reduced the travel time and number of stops by about 26 percent and 55 percent, respectively, for the entire arterial section. OPAC also improved traffic performance during changing demand conditions. It significantly improved the performance of an isolated intersection during undersaturated traffic conditions. OPAC reduced stopped delay on the major-street approach by 40 percent without affecting the minor-street performance.

scholarly journals Towards Data-Driven Vehicle Estimation for Signalised Intersections in a Partially Connected Environment

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8477
Author(s):  
Roozbeh Mohammadi ◽  
Claudio Roncoli
Keyword(s):  
Traffic Control ◽  
Partial Information ◽  
Control Strategies ◽  
Synthetic Data ◽  
Real Data ◽  
Significant Loss ◽  
Data Driven ◽  
Estimation Methods ◽  
Connected Vehicles ◽  
Vehicle Data

Connected vehicles (CVs) have the potential to collect and share information that, if appropriately processed, can be employed for advanced traffic control strategies, rendering infrastructure-based sensing obsolete. However, before we reach a fully connected environment, where all vehicles are CVs, we have to deal with the challenge of incomplete data. In this paper, we develop data-driven methods for the estimation of vehicles approaching a signalised intersection, based on the availability of partial information stemming from an unknown penetration rate of CVs. In particular, we build machine learning models with the aim of capturing the nonlinear relations between the inputs (CV data) and the output (number of non-connected vehicles), which are characterised by highly complex interactions and may be affected by a large number of factors. We show that, in order to train these models, we may use data that can be easily collected with modern technologies. Moreover, we demonstrate that, if the available real data is not deemed sufficient, training can be performed using synthetic data, produced via microscopic simulations calibrated with real data, without a significant loss of performance. Numerical experiments, where the estimation methods are tested using real vehicle data simulating the presence of various penetration rates of CVs, show very good performance of the estimators, making them promising candidates for applications in the near future.

scholarly journals Integrated Traffic Control for Freeways using Variable Speed Limits and Lane Change Control Actions

2019 ◽  
Vol 2673 (9) ◽  
pp. 602-613 ◽  
Author(s):  
Vasileios Markantonakis ◽  
Dimitrios Ilias Skoufoulas ◽  
Ioannis Papamichail ◽  
Markos Papageorgiou
Keyword(s):  
Control Strategy ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Communication Systems ◽  
Feedforward Control ◽  
Control Strategies ◽  
Connected Vehicles ◽  
Variable Speed ◽  
Speed Limits ◽  
Variable Speed Limits

The wide deployment of vehicle automation and communication systems (VACS) in the next decade is expected to influence traffic performance on freeways. Apart from safety and comfort, one of the goals is the alleviation of traffic congestion which is a major and challenging problem for modern societies. The paper investigates the combined use of two feedback control strategies utilizing VACS at different penetration rates, aiming to maximize throughput at bottleneck locations. The first control strategy employs mainstream traffic flow control using appropriate variable speed limits as an actuator. The second control strategy delivers appropriate lane-changing actions to selected connected vehicles using a feedback-feedforward control law. Investigations of the proposed integrated scheme have been conducted using a microscopic simulation model for a hypothetical freeway featuring a lane-drop bottleneck. The results demonstrate significant improvements even for low penetration rates of connected vehicles.

Remote Simulation to Evaluate Real-Time Traffic Control Strategies

2000 ◽  
Vol 1727 (1) ◽  
pp. 95-100 ◽  
Author(s):  
David E. Lucas ◽  
Pitu B. Mirchandani ◽  
K. Larry Head
Keyword(s):  
Adaptive Control ◽  
Control System ◽  
Control Systems ◽  
Real Time ◽  
Traffic Control ◽  
Control Strategies ◽  
Remote Access ◽  
Hardware In The Loop ◽  
Simulation Environment ◽  
Real Time Traffic

Simulation is a valuable tool for evaluating the effects of various changes in a transportation system. This is especially true in the case of real-time traffic-adaptive control systems, which must undergo extensive testing in a laboratory setting before being implemented in a field environment. Various types of simulation environments are available, from software-only to hardware-in-the-loop simulations, each of which has a role to play in the implementation of a traffic control system. The RHODES (real-time hierarchical optimized distributed effective system) real-time traffic-adaptive control system was followed as it progressed from a laboratory project toward actual field implementation. The traditional software-only simulation environment and extensions to a hardware-in-the-loop simulation are presented in describing the migration of RHODES onto the traffic controller hardware itself. In addition, a new enhancement to the standard software-only simulation that allows remote access is described. The enhancement removes the requirement that both the simulation and the traffic control scheme reside locally. This architecture is capable of supporting any traffic simulation package that satisfies specific input-output data requirements. This remote simulation environment was tested with several different types of networks and was found to perform in the same manner as its local counterpart. Remote simulation has all of the advantages of its local counterpart, such as control and flexibility, with the added benefit of distribution. This remote environment could be used in many different ways and by different groups or individuals, including state or local transportation agencies interested in performing their own evaluations of alternative traffic control systems.

scholarly journals Intelligent Intersection Control for Delay Optimization: Using Meta-Heuristic Search Algorithms

2020 ◽  
Vol 12 (5) ◽  
pp. 1896 ◽  
Author(s):  
Arshad Jamal ◽  
Muhammad Tauhidur Rahman ◽  
Hassan M. Al-Ahmadi ◽  
Irfan Ullah ◽  
Muhammad Zahid
Keyword(s):  
Objective Function ◽  
Traffic Control ◽  
Intelligent Transportation System ◽  
Signalized Intersections ◽  
Traffic Signal ◽  
Traffic Signal Control ◽  
Solution Quality ◽  
Simulation And Optimization ◽  
Study Results ◽  
Vehicle Delay

Traffic signal control is an integral component of an intelligent transportation system (ITS) that play a vital role in alleviating traffic congestion. Poor traffic management and inefficient operations at signalized intersections cause numerous problems as excessive vehicle delays, increased fuel consumption, and vehicular emissions. Operational performance at signalized intersections could be significantly enhanced by optimizing phasing and signal timing plans using intelligent traffic control methods. Previous studies in this regard have mostly focused on lane-based homogenous traffic conditions. However, traffic patterns are usually non-linear and highly stochastic, particularly during rush hours, which limits the adoption of such methods. Hence, this study aims to develop metaheuristic-based methods for intelligent traffic control at isolated signalized intersections, in the city of Dhahran, Saudi Arabia. Genetic algorithm (GA) and differential evolution (DE) were employed to enhance the intersection’s level of service (LOS) by optimizing the signal timings plan. Average vehicle delay through the intersection was selected as the primary performance index and algorithms objective function. The study results indicated that both GA and DE produced a systematic signal timings plan and significantly reduced travel time delay ranging from 15 to 35% compared to existing conditions. Although DE converged much faster to the objective function, GA outperforms DE in terms of solution quality i.e., minimum vehicle delay. To validate the performance of proposed methods, cycle length-delay curves from GA and DE were compared with optimization outputs from TRANSYT 7F, a state-of-the-art traffic signal simulation, and optimization tool. Validation results demonstrated the adequacy and robustness of proposed methods.

scholarly journals Cross-Comparison and Calibration of Two Microscopic Traffic Simulation Models for Complex Freeway Corridors with Dedicated Lanes

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Xingan (David) Kan ◽  
Lin Xiao ◽  
Hao Liu ◽  
Meng Wang ◽  
Wouter J. Schakel ◽  
...  
Keyword(s):  
Traffic Control ◽  
Traffic Simulation ◽  
Control Strategies ◽  
Extended Period ◽  
Simulation Models ◽  
Microscopic Simulation ◽  
Microscopic Traffic Simulation ◽  
Freeway Corridors ◽  
Flow Phenomena ◽  
Varying Demand

Realistic microscopic traffic simulation is essential for prospective evaluation of the potential impacts of new traffic control strategies. Freeway corridors with interacting bottlenecks and dedicated lanes generate complex traffic flow phenomena and congestion patterns, which are difficult to reproduce with existing microscopic simulation models. This paper discusses two alternative driving behavior models that are capable of modeling freeways with multiple bottlenecks and dedicated lanes over an extended period with varying demand levels. The models have been calibrated using archived data from a complicated 13-mile long section of the northbound SR99 freeway near Sacramento, California, for an 8-hour time period in which the traffic fluctuated from free-flow to congested conditions. The corridor includes multiple bottlenecks, multiple entry and exit ramps, and an HOV lane. Calibration results show extremely good agreement between field data and model predictions. The models have been cross-validated and produced similar macroscopic traffic performance. The main behavior that should be captured for successful modeling of such a complex corridor includes the anticipative and cooperative driver behavior near merges, lane preference in presence of dedicated lanes, and variations in desired headway along the corridor.

Evaluation of the effectiveness of single-lane two-way traffic control at maintenance and reconstruction zones

2006 ◽  
Vol 33 (9) ◽  
pp. 1217-1226 ◽  
Author(s):  
Ahmed Al-Kaisy ◽  
Eric Kerestes
Keyword(s):  
Adaptive Control ◽  
Traffic Control ◽  
Control Strategies ◽  
Stochastic Approach ◽  
Fixed Time ◽  
Work Zone ◽  
Average Delay ◽  
Zone Length ◽  
Time Control ◽  
Study Results

This paper presents a study on evaluating traffic control at single-lane closures on two-lane two-way highways. Four traffic control strategies were investigated by this study. Those strategies involved fixed-time control, fixed-queue control, "static optimum" or convoy rule, and adaptive control. Traffic control strategies were modeled using two approaches; a deterministic approach in spreadsheet application and a stochastic approach in microscopic traffic simulation. Parametric analyses were performed using several variables that are related to traffic control at this type of lane closure. Those variables involved work zone length, average speed at work zone, lost time, traffic level, directional split, and interruptions to traffic by movement of construction vehicle and (or) equipment into and out of the construction site. Study results suggest that significant savings in average delay can be accrued by using more advanced traffic control strategies. Those savings could be as high as 53% for the range of conditions investigated by this research.Key words: work zone, flaggers, adaptive control, simulation, optimization.

Evaluation of Multiple Hardware and Software in the Loop Signal Controllers in Simulation Environment

2018 ◽  
Vol 2672 (18) ◽  
pp. 93-106
Author(s):  
Sharmin-E-Shams Chowdhury ◽  
Aleksandar Stevanovic ◽  
Nikola Mitrovic
Keyword(s):  
Traffic Control ◽  
Control Strategies ◽  
Traffic Signal ◽  
Signal Timing ◽  
Hardware In The Loop ◽  
Microscopic Simulation ◽  
The Impact ◽  
Signal Operations ◽  
Traffic Signal Operations

This study evaluates two groups of methods to model traffic signal operations in microscopic simulation: hardware-in-the-loop simulation (HILS) and software-in-the-loop simulation (SILS). These methods have become standards for accurate modeling of traffic signal operations, but in spite of the large number of available options there are no studies that have conducted relevant comparative evaluations. This study bridges this gap by investigating signal timing and operational differences of these two methods in basic actuated operations of a single signalized intersection. The emphasis is given to broad examination of various platforms as opposed to more complex experiments done with individual platforms. A representative number of 65-minute simulation runs was executed for each experimental scenario. The results showed that differences between various HILS and SILS platforms are large enough that one cannot confidently switch between the platforms without affecting the final outcomes. The study confirmed previous findings about the impact of the initialization process on the simulation results, but the initialization itself does not seem to be the major source of discrepancy. Further investigation is needed to reveal role of consistency of internal NEMA-based controller logics among various controllers. These findings put a considerable dilemma/restriction on how various HILS and SILS platforms, either alone or in conjunction with other higher forms of traffic control strategies, can be used in joint fashion.

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