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Author: Nitin Maslekar
Publisher:
ISBN:
Category :
Languages : en
Pages : 156
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Book Description
Traffic signal control, which is an integral part of Intelligent Transportation System (ITS), plays an important role in regulating vehicular flow at road intersections. With the increase of vehicular traffic, there has been a significant degradation in the functional efficiency of signal systems. Traditional systems are not capable of adjusting the timing pattern in accordance with vehicular demand. This results in excessive delays for road users. Hence it is necessary to develop dynamic systems that can adjust the timing patterns according to traffic demand. Of the various available techniques, Vehicular Adhoc Networks (VANETs) are attracting considerable attention from the research community and the automotive industry to implement dynamic systems. In this context, exchanging data among vehicles is one of the key technological enablers through which the density of vehicles approaching the intersection can be predicted. This requires extensive collaboration between vehicles. Inherent properties and limitations of VANETs, distributing information among the vehicles is a very challenging task. In this thesis, an adaptive traffic signal control system based on car-to-car communication (VANETs) is proposed. To achieve this, a data dissemination technique titled, Clustering in DiRectIon in Vehicular Environment (C-DRIVE) is implemented. In C-DRIVE, the formation of clusters is based on the direction metric. Precisely this metric defines the direction a vehicle will travel after crossing the intersection. To attain stability within the clusters and to have accurate estimation of the density of vehicles, two policies are adapted. In the first policy, a clusterhead switching mechanism is defined. In the second method, termed as Modified C-DRIVE (MC-DRIVE), the clusterhead election policy is modified. In this modification the election policy is based on the stable cluster length. Once the clusters are formed, the elected cluster head will compute the density in its clusters and transmits the information to the traffic signal controller (TSC). With the density information of different lanes approaching the intersection, at the TSC an optimal cycle length is computed using the modified Webster's model and based on the demand, required green splits are allotted to the various phase. The efficiency of this method is advocated through simulation results which show that the waiting time for vehicles and queue length at intersections are considerably reduced. It is also shown that the proposed solution is collision free at intersections. The proposed system is compared with a classic pre-timed system and an adaptive fuzzy logic system. The simulations also show that the data convergence time and the communication delay between vehicles and traffic signals do not compromise the efficiency of the system.
Author: Nitin Maslekar
Publisher:
ISBN:
Category :
Languages : en
Pages : 156
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Book Description
Traffic signal control, which is an integral part of Intelligent Transportation System (ITS), plays an important role in regulating vehicular flow at road intersections. With the increase of vehicular traffic, there has been a significant degradation in the functional efficiency of signal systems. Traditional systems are not capable of adjusting the timing pattern in accordance with vehicular demand. This results in excessive delays for road users. Hence it is necessary to develop dynamic systems that can adjust the timing patterns according to traffic demand. Of the various available techniques, Vehicular Adhoc Networks (VANETs) are attracting considerable attention from the research community and the automotive industry to implement dynamic systems. In this context, exchanging data among vehicles is one of the key technological enablers through which the density of vehicles approaching the intersection can be predicted. This requires extensive collaboration between vehicles. Inherent properties and limitations of VANETs, distributing information among the vehicles is a very challenging task. In this thesis, an adaptive traffic signal control system based on car-to-car communication (VANETs) is proposed. To achieve this, a data dissemination technique titled, Clustering in DiRectIon in Vehicular Environment (C-DRIVE) is implemented. In C-DRIVE, the formation of clusters is based on the direction metric. Precisely this metric defines the direction a vehicle will travel after crossing the intersection. To attain stability within the clusters and to have accurate estimation of the density of vehicles, two policies are adapted. In the first policy, a clusterhead switching mechanism is defined. In the second method, termed as Modified C-DRIVE (MC-DRIVE), the clusterhead election policy is modified. In this modification the election policy is based on the stable cluster length. Once the clusters are formed, the elected cluster head will compute the density in its clusters and transmits the information to the traffic signal controller (TSC). With the density information of different lanes approaching the intersection, at the TSC an optimal cycle length is computed using the modified Webster's model and based on the demand, required green splits are allotted to the various phase. The efficiency of this method is advocated through simulation results which show that the waiting time for vehicles and queue length at intersections are considerably reduced. It is also shown that the proposed solution is collision free at intersections. The proposed system is compared with a classic pre-timed system and an adaptive fuzzy logic system. The simulations also show that the data convergence time and the communication delay between vehicles and traffic signals do not compromise the efficiency of the system.
Author: Erfan Shaghaghi
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 264
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Book Description
Author: Qing He
Publisher:
ISBN:
Category :
Languages : en
Pages : 506
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Book Description
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.
Author: André-Luc Beylot
Publisher: John Wiley & Sons
ISBN: 1118648730
Category : Technology & Engineering
Languages : en
Pages : 233
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Book Description
Over the last few years vehicular networks have been receiving a lot of attention from academia, industry, standardization bodies, and the various transportation agencies and departments of many governments around the world. It is envisaged in the next decade that the Intelligent Transportation System (ITS) will become an essential part of our daily life. This book describes models and/or algorithms designed to investigate evolutionary solutions to overcome important issues such as congestion control, routing, clustering, interconnection with long-term evolution (LTE) and LTE advanced cellular networks, traffic signal control and analysis of performances through simulation tools and the generation of vehicular mobility traces for network simulations. It provides an up-to-date progress report on the most significant contributions carried out by the specialized research community in the various fields concerned, in terms of models and algorithms. The proposals and new directions explored by the authors are highly original, and a rather descriptive method has been chosen, which aims at drawing up complete states of the art as well as providing an overall presentation of the personal contributions brought by the authors and clearly illustrating the advantages and limitations as well as issues for future work. Contents 1. Introduction 2. Congestion Control for Safety Vehicular Ad-Hoc Networks 3. Inter-Vehicle Communication for the Next Generation of Intelligent Transport System: Trends in Geographic Ad Hoc Routing Techniques 4. CONVOY: A New Cluster-Based Routing Protocol for Vehicular Networks 5. Complementarity between Vehicular Networks and LTE Networks 6. Gateway Selection Algorithms in a Hybrid VANET-LTE Advanced Network 7. Synthetic Mobility Traces for Vehicular Networking 8. Traffic Signal Control Systems and Car-to-Car Communications About the Authors André-Luc Beylot is Professor in the Telecommunication and Network Department of the ENSEEIHT of IRIT-T, University of Toulouse in France. Houda Labiod is Associate Professor at Telecom ParisTech in the INFRES (Computer Science and Network) Department, France.
Author: Guoyuan Wu
Publisher:
ISBN:
Category :
Languages : en
Pages : 284
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Book Description
With the growth of population and increase of travelling requirements in metropolitan areas, public transit has been recognized as a promising remedy and is playing an ever more important role in sustainable transportation systems. However, the development of the public transit system has not received enough attention until the recent emergence of Bus Rapid Transit (BRT). In the conventional public transit system, little to no communication passes between transit vehicles and the roadside infrastructure, such as traffic signals and loop detectors. But now, thanks to advancements in automatic vehicle location (AVL) systems and wireless communication, real-time and high-resolution information of the movement of transit vehicles has become available, which may potentially facilitate the development of more advanced traffic control and management systems. This dissertation introduces a novel adaptive traffic signal control system, which utilizes the real-time location information of transit vehicles. By predicting the movement of the transit vehicle based on continuous detection of the vehicle motion by the on-board AVL system and estimating the measures of effectiveness (MOE) of other motor vehicles based on the surveillance of traffic conditions, optimal signal timings can be obtained by solving the proposed traffic signal optimization models. Both numerical analysis and simulation tests demonstrate that the proposed system improves a transit vehicle's operation as well as minimizes its negative impacts on other motor vehicles in the traffic system. In summary, there are three major contributions of this dissertation: a) development of a novel AVL-based adaptive traffic signal control system; b) modeling of the associated traffic signal timing optimization problem, which is the key component of the proposed system; c) applications of the proposed system to two real world cases. After presenting background knowledge on two major types of transit operations, i.e., preemption and priority, traffic signal control and AVL systems, the architecture of the proposed adaptive signal control system and the associated algorithm are presented. The proposed system includes a data-base, fleet equipped with surveillance system, traffic signal controllers, a transit movement predictor, a traffic signal timing optimizer and a request server. The mixed integer quadratic programming (MIQP) and nonlinear programming (NP) are used to formulate signal timing optimization problems. Then the proposed system and algorithm are applied to two real-world case studies. The first case study concerns the SPRINTER rail transit service. The proposed adaptive signal control (ASC) system is developed to relieve the traffic congestion and to clear the accumulated vehicle queues at the isolated signal around the grade crossing, based on the location information on SPRINTER from PATH-developed cellular GPS trackers. The second case study involves the San Diego trolley system. With the information provided by the AVL system, the proposed ASC system predicts the arrival times of the instrumented trolley at signals and provides the corresponding optimal signal timings to improve the schedule adherence, thus reducing the delays at intersections and enhancing the trip reliability for the trolley travelling along a signalized corridor in the downtown area under the priority operation. The negative impact (e.g., delay increase) on other traffic is minimized simultaneously. Both numerical analysis and simulation tests in the microscopic environment are conducted using the PARAMICS software to validate the proposed system for the aforementioned applications. The results present a promising future for further field operational testing.
Author: Yi Jiang (Writer on engineering)
Publisher:
ISBN:
Category : Electronic traffic controls
Languages : en
Pages : 74
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Book Description
Author: Airton Gustavo Kohls
Publisher:
ISBN:
Category :
Languages : en
Pages : 104
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Book Description
Over the last 35 years many adaptive traffic signal control systems have been developed presenting alternative strategies to improve traffic signal operations. However, less than 1% of all traffic signals in the United States are controlled by adaptive systems today. The extensive infrastructure necessary including reliable communication and complex calibration leads to a time consuming and costly process. In addition, the most recent National Traffic Signal Report Card indicated an overall grade of D for the nation's traffic signal control and operations. Recent economic adversity adds to the already difficult task of proactively managing aged signal timing plans. Therefore, in an attempt to escape the status quo, a flow based adaptive split signal control model is presented, having the principal objective of updating the split table based solely on real-time traffic conditions and without disrupting coordination. Considering the available typical traffic signal control infrastructure in cities today, a non centralized system is proposed, directed to the improvement of National Electrical Manufacturers Association (NEMA) based systems that are compliant with the National Transportation Communications for Intelligent Transportation System Protocol (NTCIP) standards. The approach encompasses the User Datagram Protocol (UDP) for system communication allowing an external agent to gather flow information directly from a traffic signal controller detector status and use it to better allocation of phase splits. The flow based adaptive split signal control was not able to consistently yield significant lower average vehicle delay than a full actuated signal controller when evaluated on an intersection operating a coordinated timing plan. However, the research proposes the ability of an external agent to seamless control a traffic signal controller using real-time data, suggesting the encouraging results of this research can be improved upon.
Author: Aleksandar Stevanovic
Publisher: Transportation Research Board National Research
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 116
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Book Description
TRB's National Cooperative Highway Research Program (NCHRP) Synthesis 403: Adaptive Traffic Control Systems: Domestic and Foreign State of Practice explores the state of practice of adaptive traffic control systems (ATCSs), also known as real-time traffic control systems, which adjust, in real time, signal timings based on traffic conditions, demand, and system capacity --
Author: Piotr Gaj
Publisher: Springer
ISBN: 3319392077
Category : Computers
Languages : en
Pages : 444
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Book Description
This book constitutes the thoroughly refereed proceedings of the 23rd International Conference on Computer Networks, CN 2016, held in Brunów, Poland, in June 2016. The 32 full papers and the 4 short papers presented were carefully reviewed and selected from 72 submissions. They are organized in topical sections on computer networks architectures and protocols, teleinformatics and telecommunications, new technologies, queueing theory, and innovative applications.
Author: Huaying Xu
Publisher:
ISBN:
Category : Highway communications
Languages : en
Pages : 246
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