Evaluating Transportation Network Mobility and Enhancing Traffic Signal Operations Performance Using Probe Data and Connected Vehicle Technology PDF Download

Author: MD Abu Sufian Talukder
Publisher:
ISBN:
Category : Electronic dissertations
Languages : en
Pages :

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Book Description
High-quality, reliable, and robust data is key to better understanding performance and improvement needs for transportation infrastructure. Predominantly, transportation systems performance has been evaluated using infrastructure-based data, which is often limited by high costs, small sample size, and potential inaccuracy. With recent advancements in technology, previously unobtainable large high-fidelity data, such as probe data and connected vehicle (CV) data, can now be utilized to address many challenges related to transportation systems. This dissertation investigates various research and practical oriented applications for such emerging transportation data sources. The first part of this dissertation develops a novel methodology for characterizing mobility of transportation networks. Using probe vehicle travel times, a route-based travel time reliability metric is proposed for assessing and comparing transportation system's performance from one geographic area to another. The second part of this dissertation uses CV-technology to develop methodology for improving operational efficiency at a signalized intersection. Two innovative traffic signal control algorithms are established to demonstrate real-time delay optimization for both connected and non-connected vehicles. The third part of this dissertation extends the use of CV-technology to facilitate prioritized freight movement in a signalized corridor. An estimated time of arrival (ETA)-based priority logic is developed, and the proposed priority system is deployed along US-82 in Northport and Tuscaloosa, Alabama. Finally, this dissertation explores the application of emerging transportation data collection technologies to characterize and evaluate transportation systems performance. The techniques presented in this dissertation will be helpful to transportation agencies, planners, and practitioners to assess existing performance and need for future transportation infrastructure.

Author: Lawrence A. Klein
Publisher: CRC Press
ISBN: 1351800973
Category : Technology & Engineering
Languages : en
Pages : 574

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Book Description
An intelligent transportation system (ITS) offers considerable opportunities for increasing the safety, efficiency, and predictability of traffic flow and reducing vehicle emissions. Sensors (or detectors) enable the effective gathering of arterial and controlled-access highway information in support of automatic incident detection, active transportation and demand management, traffic-adaptive signal control, and ramp and freeway metering and dispatching of emergency response providers. As traffic flow sensors are integrated with big data sources such as connected and cooperative vehicles, and cell phones and other Bluetooth-enabled devices, more accurate and timely traffic flow information can be obtained. The book examines the roles of traffic management centers that serve cities, counties, and other regions, and the collocation issues that ensue when multiple agencies share the same space. It describes sensor applications and data requirements for several ITS strategies; sensor technologies; sensor installation, initialization, and field-testing procedures; and alternate sources of traffic flow data. The book addresses concerns related to the introduction of automated and connected vehicles, and the benefits that systems engineering and national ITS architectures in the US, Europe, Japan, and elsewhere bring to ITS. Sensor and data fusion benefits to traffic management are described, while the Bayesian and Dempster–Shafer approaches to data fusion are discussed in more detail. ITS Sensors and Architectures for Traffic Management and Connected Vehicles suits the needs of personnel in transportation institutes and highway agencies, and students in undergraduate or graduate transportation engineering courses.

Author: Robert Gordon
Publisher: Springer
ISBN: 3319147684
Category : Technology & Engineering
Languages : en
Pages : 286

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Book Description
Intelligent Transportation Systems: Functional Design for Economical and Efficient Traffic Management provides practical guidance on the efficient use of resources in the design of ITS. The author explains how functional design alternatives can meet project objectives and requirements with optimal cost effectiveness and clarifies how transportation planning and traffic diversion principles relate to functional ITS device selections and equipment locations. Methodologies for translating objectives to functional device types, determining device deployment densities and determining the best placement of CCTV cameras and message signs are provided, as are models for evaluating the benefits of design alternatives based on traffic conditions. Readers will learn how to reduce recurrent congestion, improve incident clearance time in non-recurrent congestion, provide real-time incident information to motorists, and leverage transportation management center data for lane control through important new active transportation and demand management (ATDM) methods. Finally, the author examines exciting developments in connected vehicle technologies, exploring their potential to greatly improve safety, mobility and energy efficiency. This resource will greatly benefit all ITS designers and managers and is of pivotal importance for operating agencies performing evaluations to justify operational funding and system expansions.

Author: Ehsan Bagheri
Publisher:
ISBN:
Category : Intelligent transportation systems
Languages : en
Pages : 168

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Book Description
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: Norris Novat
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
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.

Author: Christopher M. Day
Publisher: Joint Transportation Research Program
ISBN: 9781622602803
Category : Transportation
Languages : en
Pages : 134

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Book Description
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.

Author: Lei Zhang
Publisher:
ISBN:
Category :
Languages : en
Pages : 172

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Book Description
This dissertation discusses network wide signal control strategies base on connected vehicle technology. Traffic congestion on arterials has become one of the largest threats to economic competitiveness, livability, safety, and long-term environmental sustainability in the United States. In addition, arterials usually experience more blockage than freeways, specifically in terms of intersection congestion. There is no doubt that emerging technologies provide unequaled opportunities to revolutionize “retiming” and mitigate traffic congestion. Connected vehicle technology provides unparalleled safety benefits and holds promise in terms of alleviating both traffic congestion and the environmental impacts of future transportation systems. The objective of this research is to improve the mobility, safety and environmental effects at signalized arterials with connected vehicles. The proposed solution of this dissertation is to formulate traffic signal control models for signalized arterials based on connected vehicle technology. The models optimize offset, split, and cycle length to minimize total queue delay in all directions of coordinated intersections. Then, the models are implemented in a centralized system—including closed-loop systems—first, before expanding the results to distributed systems. The benefits of the models are realized at the infant stage of connected vehicle deployment when the penetration rate of connected vehicles is around 10%. Furthermore, the benefits incentivize the growth of the penetration rate for drivers. In addition, this dissertation contains a performance evaluation in traffic delay, volume throughput, fuel consumption, emission, and safety by providing a case study of coordinated signalized intersections. The case study results show the solution of this dissertation could adapt early deployment of connected vehicle technology and apply to future connected vehicle technology development.

Author: Gerard Aguilar Ubiergo
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Book Description
Traffic signals, even though crucial for safe operations of busy intersections, are one of the leading causes of travel delays in urban settings, as well as the reason why billions of gallons of fuel are burned each year by idling engines, releasing tons of unnecessary toxic pollutants to the atmosphere. Recent advances in cellular networks and dedicated short-range communications make Vehicle-to-Infrastructure (V2I) communications a reality, as individual cars and traffic signals can now be equipped with numerous communication and computing devices. In this thesis, an initial comprehensive literature search is carried out on topics related to traffic flow models, connected vehicles, eco-driving, traffic signal timing, and the application of connected vehicle technologies in improving the operation of signalized networks. Then a car-following model and an emission model are combined to simulate the behavior of vehicles at signalized intersections and calculate traffic delays in queues, vehicle emissions and fuel consumption. Next, a strategy to provide mobility and environment improvements in signalized networks is presented. In this strategy, the control variable is the advisory speed limit, which is designed to smooth vehicles' speed profiles taking advantage of Vehicle-to-Intersection communication. Finally, the performance of the control system is studied depending on market penetration rate and traffic conditions, as well as communication, positioning and network characteristics. In particular, savings of around 15% in user delays and around 8% in fuel consumption and CO2 emissions are demonstrated.

Author: Jaume Barceló
Publisher: Springer Science & Business Media
ISBN: 1441960708
Category : Business & Economics
Languages : en
Pages : 202

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Book Description
A nice night of October 2007, in Beijing, during the XV World Conference on ITS a number of colleagues met informally for a dinner party that spontaneously became a vivid discussion on the importance of traffic data for all types of p- poses. Researchers can hardly do any progress in modeling, developing, and te- ing theories without suitable data, and what practitioners can do in real life is limited not only by technology but also by the availability of the required data. Quite frequently, the data and not the technologies are what determine how far we can go. Any discussion about traffic data leads in a natural way to a discussion on the variety of traffic data sources, formats, levels of aggregation, accuracies, and so on. Consequently, we moved to talk on the initiative that Kuwahara had undertaken in his traffic laboratory at the University of Tokyo, known as the International Traffic Data Base, and thus smoothly but inexorably we came to agree that it would be convenient to organize a workshop to continue our discussion at a more formal level, share our points of view with other colleagues, listen what they had to say and, if possible, d- seminate the findings in our professional and academic communities.

Author: Cambridge Systematics
Publisher: Transportation Research Board
ISBN: 0309154928
Category : Transportation
Languages : en
Pages : 87

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Book Description
This guidebook provides methods for integrating performance measures from individual transportation modes and multiple jurisdictions and for developing new measures, if needed, to monitor transportation network performance. These network performance measures can be used to improve system management, planning, and investment decisions and can be applied to various scenarios. The guidebook should be of immediate use to practitioners in state, regional, or local governments; specially designated authorities; or those in the private sector who are responsible for measuring, operating, and investing in the performance of multimodal and/or multijurisdictional transportation networks.