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Real Time Traffic Signal System Performance Measurement Phase Ii Data And Functionality Enhancement Large Scale Deployment Connected And Automated Vehicles Integration
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Book Synopsis Real-time Traffic Signal System Performance Measurement - Phase II : Data and Functionality Enhancement, Large Scale Deployment, Connected and Automated Vehicles Integration by : Peter J. Jin
Download or read book Real-time Traffic Signal System Performance Measurement - Phase II : Data and Functionality Enhancement, Large Scale Deployment, Connected and Automated Vehicles Integration written by Peter J. Jin and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Enhanced Traffic Signal Operation Using Connected Vehicle Data by : Ehsan Bagheri
Download or read book Enhanced Traffic Signal Operation Using Connected Vehicle Data written by Ehsan Bagheri and published by . This book was released on 2017 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: As traffic on urban road network increases, congestion and delays are becoming more severe. At grade intersections form capacity bottlenecks in urban road networks because at these locations, capacity must be shared by competing traffic movements. Traffic signals are the most common method by which the right of way is dynamically allocated to conflicting movements. A range of traffic signal control strategies exist including fixed time control, actuated control, and adaptive traffic signal control (ATSC). ATSC relies on traffic sensors to estimate inputs such as traffic demands, queue lengths, etc. and then dynamically adjusts signal timings with the objective to minimize delays and stops at the intersection. Despite, the advantages of these ATSC systems, one of the barriers limiting greater use of these systems is the large number of traffic sensors required to provide the essential information for their signal timing optimization methodologies. A recently introduced technology called connected vehicles will make vehicles capable of providing detailed information such as their position, speed, acceleration rate, etc. in real-time using a wireless technology. The deployment of connected vehicle technology would provide the opportunity to introduce new traffic control strategies or to enhance the existing one. Some work has been done to-date to develop new ATSC systems on the basis of the data provided by connected vehicles which are mainly designed on the assumption that all vehicles on the network are equipped with the connected vehicle technology. The goals of such systems are to: 1) provide better performance at signalized intersections using enhanced algorithms based on richer data provided by the connected vehicles; and 2) reduce (or eliminate) the need for fixed point detectors/sensors in order to reduce deployment and maintenance costs. However, no work has been done to investigate how connected vehicle data can improve the performance of ATSC systems that are currently deployed and that operate using data from traditional detectors. Moreover, achieving a 100% market penetration of connected vehicles may take more than 30 years (even if the technology is mandated on new vehicles). Therefore, it is necessary to provide a solution that is capable of improving the performance of signalized intersections during this transition period using connected vehicle data even at low market penetration rates. This research examines the use of connected vehicle data as the only data source at different market penetration rates aiming to provide the required inputs for conventional adaptive signal control systems. The thesis proposes various methodologies to: 1) estimate queues at signalized intersections; 2) dynamically estimate the saturation flow rate required for optimizing the timings of traffic signals at intersections; and 3) estimate the free flow speed on arterials for the purpose of optimizing offsets between traffic signals. This thesis has resulted in the following findings: 1. Connected vehicle data can be used to estimate the queue length at signalized intersections especially for the purpose of estimating the saturation flow rate. The vehicles' length information provided by connected vehicles can be used to enhance the queue estimation when the traffic composition changes on a network. 2. The proposed methodology for estimating the saturation flow rate is able to estimate temporally varying saturation flow rates in response to changing network conditions, including lane blockages and queue spillback that limit discharge rates, and do so with an acceptable range of errors even at low level of market penetration of connected vehicles. The evaluation of the method for a range of traffic Level of Service (LOS) shows that the maximum observed mean absolute relative error (6.2%) occurs at LOS F and when only 10% of vehicles in the traffic stream are connected vehicles. 3. The proposed method for estimating the Free Flow Speed (FFS) on arterial roads can provide estimations close to the known ground truth and can respond to changes in the FFS. The results also show that the maximum absolute error of approximately 4.7 km/h in the estimated FFS was observed at 10% market penetration rate of connected vehicles. 4. The results of an evaluation of an adaptive signal control system based on connected vehicle data in a microsimulation environment show that the adaptive signal control system is able to adjust timings of signals at intersections in response to changes in the saturation flow rate and free flow speed estimated from connected vehicle data using the proposed methodologies. The comparison of the adaptive signal control system against a fixed time control at 20% and 100% CV market penetration rates shows improvements in average vehicular delay and average number of stops at both market penetration rates and though improvements are larger for 100% CV LMP, approximately 70% of these improvements are achieved at 20% CV LMP.
Author :Christopher M. Day Publisher :Joint Transportation Research Program ISBN 13 :9781622602803 Total Pages :134 pages Book Rating :4.6/5 (28 download)
Book Synopsis Performance Measures for Traffic Signal Systems by : Christopher M. Day
Download or read book Performance Measures for Traffic Signal Systems written by Christopher M. Day and published by Joint Transportation Research Program. This book was released on 2014-03-26 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph is a synthesis of research carried out on traffic signal performance measures based on high-resolution controller event data, assembled into a methodology for performance evaluation of traffic signal systems. High-resolution data consist of a log of discrete events such as changes in detector and signal phase states. A discussion is provided on the collection and management of the signal event data and on the necessary infrastructure to collect these data. A portfolio of performance measures is then presented, focusing on several different topics under the umbrella of traffic signal systems operation. System maintenance and asset management is one focus. Another focus is signal operations, considered from the perspectives of vehicle capacity allocation and vehicle progression. Performance measures are also presented for nonvehicle modes, including pedestrians, and modes that require signal preemption and priority features. Finally, the use of travel time data is demonstrated for evaluating system operations and assessing the impact of signal retiming activities.
Book Synopsis Real-Time Arterial Traffic Signal Performance Measures by : Christopher M. Day
Download or read book Real-Time Arterial Traffic Signal Performance Measures written by Christopher M. Day and published by Purdue University Press. This book was released on 2008-04-01 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: Increasing demand for highway system capacity compels transportation agencies to extract as much capacity as possible from existing systems. Traffic signals represent a major component of highway systems. Improvement of traffic signal operation requires accurate performance measures. Despite recent improvements in computing technology, traffic signal controllers are currently not able to capture useful performance measures on a cycle-by-cycle basis. This report presents a set of performance measures that could be collected on a cycle-by-cycle basis by a traffic signal controller given the capability to log phase indications and detector actuations. The performance measures investigated here include the volume-to-capacity ratio and arrival type defined by the Highway Capacity Manual. The effectiveness of these performance measures in evaluating operation at a traffic signal is demonstrated in two comparative case studies. The first study investigates the impact of actuating a portion of the coordinated phases at a coordinated arterial intersection. The second study investigates the results of retiming a traffic signal on a coordinated arterial.
Book Synopsis Development of a Traffic Signal Performance Measurement System (TSPMS) by : Kevin N. Balke
Download or read book Development of a Traffic Signal Performance Measurement System (TSPMS) written by Kevin N. Balke and published by . This book was released on 2005 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this research was to examine the type of performance measures that could be collected at an intersection and develop a system for automatically collecting these performance measures in the field.. We began the research by conducting an assessment ofthe needs of the Texas Department of Transportation (TxDOT) practitioners for an automated system to collect intersection and traffic signal performance measures. We then examined capabilities of some of the existing traffic signal controllers and detection systems to produce the desired performance measures. Based on the findings of the needs assessments and an evaluation of the limitation of the existing detection system, we developed a series of innovative performance measures that practitioners could use to assess traffic operations and the effectiveness of the signal timing at intersections. We then developed a prototype system for automatically collecting these data in the field. We installed the prototype system in two different locations that exhibited different operating characteristics and assessed the ability of the system to collect meaningful and appropriate performance measures.
Book Synopsis Integrating Clarus Data in Traffic Signal System Operation by : Ahmed Shawky Abdel-Rahim
Download or read book Integrating Clarus Data in Traffic Signal System Operation written by Ahmed Shawky Abdel-Rahim and published by . This book was released on 2011 with total page 51 pages. Available in PDF, EPUB and Kindle. Book excerpt: This report presents a prototype of a secure, dependable, real-time weather-responsive traffic signal system. The prototype executes two tasks: 1) accesses weather information that provides near real-time atmospheric and pavement surface condition observations and 2) adapts signal timing in response to inclement weather. The proposed system architecture employs two revolutionary software design approaches: 1) Design for Survivability and 2) software performance measurement at the task level. Furthermore, the software design incorporates self-diagnostic techniques for fault detection and recovery to maximize the survivability and the security of the system. Minimal hardware is required for full implementation of the system as it operates and achieves its potential using current traffic controller and cabinet standards and technologies. As a result, it is compatible with future applications within the FHWA's connected-vehicle framework. The weather-responsive traffic signal system presented in this report serves as a major milestone in the development of secure and dependable real-time traffic control system applications.
Book Synopsis Data-driven Adaptive Traffic Signal Control Via Deep Reinforcement Learning by : Tian Tan
Download or read book Data-driven Adaptive Traffic Signal Control Via Deep Reinforcement Learning written by Tian Tan and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive traffic signal control (ATSC) system serves a significant role for relieving urban traffic congestion. The system is capable of adjusting signal phases and timings of all traffic lights simultaneously according to real-time traffic sensor data, resulting in a better overall traffic management and an improved traffic condition on road. In recent years, deep reinforcement learning (DRL), one powerful paradigm in artificial intelligence (AI) for sequential decision-making, has drawn great attention from transportation researchers. The following three properties of DRL make it very attractive and ideal for the next generation ATSC system: (1) model-free: DRL reasons about the optimal control strategies directly from data without making additional assumptions on the underlying traffic distributions and traffic flows. Compared with traditional traffic optimization methods, DRL avoids the cumbersome formulation of traffic dynamics and modeling; (2) self-learning: DRL self-learns the signal control knowledge from traffic data with minimal human expertise; (3) simple data requirement: by using large nonlinear neural networks as function approximators, DRL has enough representation power to map directly from simple traffic measurements, e.g. queue length and waiting time, to signal control policies. This thesis focuses on building data-driven and adaptive controllers via deep reinforcement learning for large-scale traffic signal control systems. In particular, the thesis first proposes a hierarchical decentralized-to-centralized DRL framework for large-scale ATSC to better coordinate multiple signalized intersections in the traffic system. Second, the thesis introduces efficient DRL with efficient exploration for ATSC to greatly improve sample complexity of DRL algorithms, making them more suitable for real-world control systems. Furthermore, the thesis combines multi-agent system with efficient DRL to solve large-scale ATSC problems that have multiple intersections. Finally, the thesis presents several algorithmic extensions to handle complex topology and heterogeneous intersections in real-world traffic networks. To gauge the performance of the presented DRL algorithms, various experiments have been conducted and included in the thesis both on small-scale and on large-scale simulated traffic networks. The empirical results have demonstrated that the proposed DRL algorithms outperform both rule-based control policy and commonly-used off-the-shelf DRL algorithms by a significant margin. Moreover, the proposed efficient MARL algorithms have achieved the state-of-the-art performance with improved sample-complexity for large-scale ATSC.
Book Synopsis Traffic Signal Timing Manual by : U.s. Department of Transportation
Download or read book Traffic Signal Timing Manual written by U.s. Department of Transportation and published by CreateSpace. This book was released on 2015-02-20 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: This report serves as a comprehensive guide to traffic signal timing and documents the tasks completed in association with its development. The focus of this document is on traffic signal control principles, practices, and procedures. It describes the relationship between traffic signal timing and transportation policy and addresses maintenance and operations of traffic signals. It represents a synthesis of traffic signal timing concepts and their application and focuses on the use of detection, related timing parameters, and resulting effects to users at the intersection. It discusses advanced topics briefly to raise awareness related to their use and application. The purpose of the Signal Timing Manual is to provide direction and guidance to managers, supervisors, and practitioners based on sound practice to proactively and comprehensively improve signal timing. The outcome of properly training staff and proactively operating and maintaining traffic signals is signal timing that reduces congestion and fuel consumption ultimately improving our quality of life and the air we breathe. This manual provides an easy-to-use concise, practical and modular guide on signal timing. The elements of signal timing from policy and funding considerations to timing plan development, assessment, and maintenance are covered in the manual. The manual is the culmination of research into practices across North America and serves as a reference for a range of practitioners, from those involved in the day to day management, operation and maintenance of traffic signals to those that plan, design, operate and maintain these systems.
Book Synopsis Connected Vehicle Corridor Deployment and Performance Measures for Assessment by : Howell Li
Download or read book Connected Vehicle Corridor Deployment and Performance Measures for Assessment written by Howell Li and published by . This book was released on 2019 with total page 29 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Development of a Real-time Arterial Performance Monitoring System Using Traffic Data Available from Existing Signal Systems by : Henry X. Liu
Download or read book Development of a Real-time Arterial Performance Monitoring System Using Traffic Data Available from Existing Signal Systems written by Henry X. Liu and published by . This book was released on 2008 with total page 117 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data collection and performance measurement for signalized arterial roads is an area of emerging focus in the United States. As indicated by the results of the 2005 Traffic Signal Operation Self-Assessment Survey, a majority of agencies involved in the operation and maintenance of traffic signal systems do not monitor or archive traffic system performance and thus have limited means to improve their operation. With support from the Transportation Department of Hennepin County, Minneapolis, MN, a system for high resolution traffic signal data collection and arterial performance measurement has been successfully built. The system, named SMART-SIGNAL (Systematic Monitoring of Arterial Road Traffic Signals), is able to collect and archive event-based traffic signal data simultaneously at multiple intersections. Using the event-based traffic data, SMART-SIGNAL can generate timedependent performance measures for both individual intersections and arterials including intersection queue length and arterial travel time. The SMART-SIGNAL system has been deployed at an 11-intersection corridor along France Avenue in south Minneapolis and the estimated performance measures for both intersection queue length and arterial travel times are highly consistent with the observed data.
Book Synopsis Traffic Signal Control Enhancements Under Vehicle Infrastructure Integration Systems by :
Download or read book Traffic Signal Control Enhancements Under Vehicle Infrastructure Integration Systems written by and published by . This book was released on 2011 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most current traffic signal systems are operated using a very archaic traffic-detection simple binary logic (vehicle presence/non presence information). The logic was originally developed to provide input for old electro-mechanical controllers that were developed in the early 1920s. It is currently in urgent need to improve the performance of traffic control devices. With the development of automatic controls, sensors, and devices, it is now possible to design advanced intersection control systems that can fully utilize advanced technologies of detection and communication as well as the high quality data acquired by such technologies. One example of such systems is Vehicle Infrastructure Integration (VII). VII links vehicles, drivers, and surrounding infrastructure (which includes roadways, traffic controls, etc.) to improve the efficiency of traffic systems and promote transportation safety. It promises to "bridge the gap" between the infrastructure and individual drivers. The purpose of this research is to 1. Investigate the potential to utilize VII data to characterize system operation and estimate system-wide measure of performance, and 2. Develop advanced signal timing procedures that can capitalize on VII data and enhance the operations of traffic signal system operations. Three advanced traffic signal control systems are developed and tested in this research. The advantages of such systems were tested in terms of time savings, the environment, and system improvements.
Download or read book Traffic Signal Systems written by and published by . This book was released on 2008 with total page 119 pages. Available in PDF, EPUB and Kindle. Book excerpt: TRB's Transportation Research Record: Journal of the Transportation Research Board, No. 2080 includes 13 papers that explore the preempt trap of the highway-railway interface, fully actuated versus nonactuated coordinated phases, effectiveness of lead-lag phasing on progression bandwidth, high-resolution gueue discharge and the effect on signal phasing, integration of real-time pedestrian performance measures into traffic signal systems, microsimulation of split-cycle offset optimization technique and coordinated actuated traffic control, and piecewise optimum delay estimation for improved signal control. This issue of the TRR also examines microsimulation of traffic operations at intersections in malfunction flash mode, variable maximum green time to improve rural traffic signal operations, stopping behavior at urban signalized intersections, traffic controller performance of coordinated actuated signal systems during time-of-day transition, unacceptable video detector performance for dilemma zone protection, and robust synchronization of arterial actuated signals.
Book Synopsis Traffic Signal Timing Optimization with Connected Vehicles by : Wan Li
Download or read book Traffic Signal Timing Optimization with Connected Vehicles written by Wan Li and published by . This book was released on 2019 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: The advent and deployment of Connected vehicle (CV) and Vehicle-to-everything (V2X) communications offer the potential to significantly improve the efficiency of traffic signal control systems. The knowledge of vehicle trajectories in the network allows for optimal signal setting and significant improvements in network performance compared to existing traffic signal control systems. This research aims to develop a framework, including modeling techniques, algorithms, and testing strategies, for urban traffic signal optimization with CVs. The objective is to improve the safety, mobility, and sustainability of all vehicles in the study areas utilizing CV data, i.e., real time information on vehicles' locations and speeds, as well as communications to the signal control systems. The proposed framework is able to optimize traffic signal timing for a single intersection and along a corridor under various market penetration of CVs. Under full penetration rate of CVs, the signal timing optimization and coordination problems are first formulated in a centralized scheme as a mixed-integer nonlinear programing (MINLP). Due to the complexity of the model, the problem is decomposed into two levels: an intersection level to optimize phase durations using dynamic programing (DP) and a corridor level to optimize the offsets of all intersections. Under medium-to-high penetration rates of CVs, Kalman filter methods are applied to estimate trajectories of unequipped vehicles given the available trajectories of CVs. The estimated trajectories combined with CV trajectories are utilized in the trajectory-based signal timing optimization process. Under relatively low penetration rates of CVs, a Deep Intersection Spatial Temporal Network (DISTN) is developed to predict short-term movement-based traffic volumes. The predicted volumes are used in a volume-based adaptive signal control method to calculate signal timing parameters. Comprehensive testing and validation of the proposed methods are conducted in traffic simulation and with real world CV (probe vehicle) data. The testing tasks aim to validate that the developed methods are computationally manageable and have the potential to be implemented in CV-based traffic signal applications in the real world.
Book Synopsis Utilizing Simulated Vehicle Trajectory Data from Connected Vehicles to Characterize Performance Measures on an Arterial After an Impactful Incident by : Norris Novat
Download or read book Utilizing Simulated Vehicle Trajectory Data from Connected Vehicles to Characterize Performance Measures on an Arterial After an Impactful Incident written by Norris Novat and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Traffic incidents are unforeseen events known to affect traffic flow because they reduce the capacity of an arterial corridor segment and normally generate a temporary bottleneck. Identification of retiming requirements to enhance traffic signal operations when an incident occurs depends on operations-oriented traffic signal performance measurements when effective and real-time traffic signal performance metrics are employed at traffic control centers, delays, fuel use, and air pollution may all be decreased. The majority of currently available traffic signal performance evaluations are based on high-resolution traffic signal controller event data, which gives data on an intersection-by-intersection basis but requires a substantial upfront expenditure. The necessary detecting and communication equipment also involves costly and periodic maintenance. Additionally, the full manifestation of connected vehicles (CVs) is fast approaching with efforts in place to accelerate the adaptation of CVs and their infrastructures. CV technologies have enormous potential to improve traffic mobility and safety. CVs can provide abundant traffic data that is not otherwise captured by roadway detectors or other methods of traffic data collection. Since the observation is independent of any space restrictions and not impacted by queue discharge and buildup, CV data offers more comprehensive and reliable data that can be used to estimate various traffic signal performance measures. This thesis proposes a conceptual CV simulation framework intended to ascertain the effectiveness of CV trajectory-based measures in characterizing an arterial corridor incident, such as a vehicle crash. Using a four-intersection corridor with vii different signal timing plans, a microscopic simulation model was created in Simulation of Urban Mobility (SUMO), Vehicles in Network Simulation (Veins) and Objective Modular Network Testbed in C++ (OMNeT++) platforms. Furthermore, an algorithm for CVs that defines, detects and disseminates a vehicle crash incident to other vehicles and a roadside unit (RSU) was developed. In the thesis, it is demonstrated how visual performance metrics with CV data may be used to identify an incident. This thesis proposes that traffic signals performance metrics, such as progression quality, split failure, platoon ratios, and safety surrogate measures (SSMs), may be generated using CV trajectory data. The results show that the recommended approaches with access to CV trajectory data would help both performance assessment and operation of traffic control systems. Unlike the current state of the practice (fixed detection technology), the developed conceptual framework can detect incidents that intersection-vicinity-limited does not capture detectors while requiring immediate attention.
Book Synopsis Robust-Intelligent Traffic Signal Control Within a Vehicle-to-Infrastructure and Vehicle-to-Vehicle Communication Environment by : Qing He
Download or read book Robust-Intelligent Traffic Signal Control Within a Vehicle-to-Infrastructure and Vehicle-to-Vehicle Communication Environment written by Qing He and published by . This book was released on 2010 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern traffic signal control systems have not changed significantly in the past 40-50 years. The most widely applied traffic signal control systems are still time-of-day, coordinated-actuated system, since many existing advanced adaptive signal control systems are too complicated and fathomless for most of people. Recent advances in communications standards and technologies provide the basis for significant improvements in traffic signal control capabilities. In the United States, the IntelliDriveSM program (originally called Vehicle Infrastructure Integration - VII) has identified 5.9GHz Digital Short Range Communications (DSRC) as the primary communications mode for vehicle-to-vehicle (v2v) and vehicle-to-infrastructure (v2i) safety based applications, denoted as v2x. The ability for vehicles and the infrastructure to communication information is a significant advance over the current system capability of point presence and passage detection that is used in traffic control systems. Given enriched data from IntelliDriveSM, the problem of traffic control can be solved in an innovative data-driven and mathematical way to produce robust and optimal outputs. In this doctoral research, three different problems within a v2x environment- "enhanced pseudo-lane-level vehicle positioning", "robust coordinated-actuated multiple priority control", and "multimodal platoon-based arterial traffic signal control", are addressed with statistical techniques and mathematical programming. First, a pseudo-lane-level GPS positioning system is proposed based on an IntelliDriveSM v2x environment. GPS errors can be categorized into common-mode errors and noncommon-mode errors, where common-mode errors can be mitigated by differential GPS (DGPS) but noncommon-mode cannot. Common-mode GPS errors are cancelled using differential corrections broadcast from the road-side equipment (RSE). With v2i communication, a high fidelity roadway layout map (called MAP in the SAE J2735 standard) and satellite pseudo-range corrections are broadcast by the RSE. To enhance and correct lane level positioning of a vehicle, a statistical process control approach is used to detect significant vehicle driving events such as turning at an intersection or lane-changing. Whenever a turn event is detected, a mathematical program is solved to estimate and update the GPS noncommon-mode errors. Overall the GPS errors are reduced by corrections to both common-mode and noncommon-mode errors. Second, an analytical mathematical model, a mixed-integer linear program (MILP), is developed to provide robust real-time multiple priority control, assuming penetration of IntelliDriveSM is limited to emergency vehicles and transit vehicles. This is believed to be the first mathematical formulation which accommodates advanced features of modern traffic controllers, such as green extension and vehicle actuations, to provide flexibility in implementation of optimal signal plans. Signal coordination between adjacent signals is addressed by virtual coordination requests which behave significantly different than the current coordination control in a coordinated-actuated controller. The proposed new coordination method can handle both priority and coordination together to reduce and balance delays for buses and automobiles with real-time optimized solutions. The robust multiple priority control problem was simplified as a polynomial cut problem with some reasonable assumptions and applied on a real-world intersection at Southern Ave. & 67 Ave. in Phoenix, AZ on February 22, 2010 and March 10, 2010. The roadside equipment (RSE) was installed in the traffic signal control cabinet and connected with a live traffic signal controller via Ethernet. With the support of Maricopa County's Regional Emergency Action Coordinating (REACT) team, three REACT vehicles were equipped with onboard equipments (OBE). Different priority scenarios were tested including concurrent requests, conflicting requests, and mixed requests. The experiments showed that the traffic controller was able to perform desirably under each scenario. Finally, a unified platoon-based mathematical formulation called PAMSCOD is presented to perform online arterial (network) traffic signal control while considering multiple travel modes in the IntelliDriveSM environment with high market penetration, including passenger vehicles. First, a hierarchical platoon recognition algorithm is proposed to identify platoons in real-time. This algorithm can output the number of platoons approaching each intersection. Second, a mixed-integer linear program (MILP) is solved to determine the future optimal signal plans based on the real-time platoon data (and the platoon request for service) and current traffic controller status. Deviating from the traditional common network cycle length, PAMSCOD aims to provide multi-modal dynamical progression (MDP) on the arterial based on the real-time platoon information. The integer feasible solution region is enhanced in order to reduce the solution times by assuming a first-come, first-serve discipline for the platoon requests on the same approach. Microscopic online simulation in VISSIM shows that PAMSCOD can easily handle two traffic modes including buses and automobiles jointly and significantly reduce delays for both modes, compared with SYNCHRO optimized plans.
Book Synopsis International Aerospace Abstracts by :
Download or read book International Aerospace Abstracts written by and published by . This book was released on 1999 with total page 1032 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Real-time Measures of Traffic Signal Performance by : Kevin N. Balke
Download or read book Real-time Measures of Traffic Signal Performance written by Kevin N. Balke and published by . This book was released on 2005 with total page 4 pages. Available in PDF, EPUB and Kindle. Book excerpt:
