Next Generation Safety Performance Monitoring at Signalized Intersections Using Connected Vehicle Technology - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Next Generation Safety Performance Monitoring at Signalized Intersections Using Connected Vehicle Technology write by Liteng Zha. This book was released on 2014. Next Generation Safety Performance Monitoring at Signalized Intersections Using Connected Vehicle Technology available in PDF, EPUB and Kindle.
Operation and Safety Performance Assessment of Queue Warning Applications on Signalized Intersections for Connected Freight Vehicles
Operation and Safety Performance Assessment of Queue Warning Applications on Signalized Intersections for Connected Freight Vehicles - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Operation and Safety Performance Assessment of Queue Warning Applications on Signalized Intersections for Connected Freight Vehicles write by Sara Bashir. This book was released on 2020. Operation and Safety Performance Assessment of Queue Warning Applications on Signalized Intersections for Connected Freight Vehicles available in PDF, EPUB and Kindle. Connected Vehicle (CV) technologies have been a core component for the Intelligent Transportation Systems (ITS) due to their capability to support a variety of ITS applications and unite vehicles and infrastructure elements into a well-integrated transportation system. Connected vehicles refer to those that exchange information with each other and the infrastructure using Dedicated Short-Range communication (DSRC), known as Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), and Infrastructure-to-Vehicle (I2V) communications under Vehicular ad hoc Network (VANET). These communications improve safety, mobility, and productivity of transportation systems users. This research develops and tests CV-based algorithms for a Queue Warning (Q-WARN) application for heavy freight vehicles. The Q-WARN application uses CV technologies to allow vehicles within the queue to automatically broadcast their queued status information (e.g., rapid deceleration, disabled status, and lane location) to upstream vehicles as well as to infrastructure. The queue warnings are sent to oncoming vehicles to prevent rear-end or other secondary collisions. It can also provide drivers the appropriate warning to help them safely reduce their speed, make the decision of changing lanes, or use alternative routes through enhancing drivers’ situational awareness. This thesis focuses on Q-WARN applications for freight vehicles at signalized intersections that are located adjacent to I-80 in Wyoming, which are characterized by heavy truck traffic. Four locations in the state of Wyoming, characterized by heavy freight traffic, are selected as the test-case intersections. The algorithms developed are using the latitude/longitude (lat/lon) coordinates of freight CVs and intersections to form a communication link and share information. The tests were performed in VISSIM microsimulation with Econolite ASC/3 Software-in-the-Loop (SIL) traffic signal controller emulator. The scope of analyses is twofold. Firstly, from the traffic operation approach: queuing, total delays, and vehicle spacing were scrutinized at intersection. Secondly, from the traffic safety perspective, Time-to-Collision (TTC) and Post-Encroachment Time (PET), as two commonly used Surrogate Measures of Safety (SMoS), were assessed. Through analyses of simulation results, in-depth comparisons of these traffic flow and safety parameters at baseline (0%), 10%, 25%, 50%, 75%, and 100% CV Market Penetration Rates (MPRs) under the effect of Q-WARN application were performed. The simulation scenarios developed through communication protocol can be easily implemented in the field, since it uses universal technologies. The results from developed Q-WARN algorithms revealed that the application has a remarkable potential to improve traffic operation parameters at signalized intersections, as well as providing safety benefits, especially when applied to heavy freight vehicles. Findings indicated successful traffic operation performance of the developed Q-WARN application in reducing vehicle delays by an average of 2% to 5%, as well as increasing the spacing between vehicles up to 134%, which could be an indicator of safety benefits. The results depicted that as the CV-MPR increases, the means of both SMoS increases, leading to safety enhancement under the impact of Q-WARN application. The abundance of information obtained from CV vehicles can be used to further enhance different control algorithms and applications.
Network Wide Signal Control Strategy Base on Connected Vehicle Technology
Network Wide Signal Control Strategy Base on Connected Vehicle Technology - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Network Wide Signal Control Strategy Base on Connected Vehicle Technology write by Lei Zhang. This book was released on 2018. Network Wide Signal Control Strategy Base on Connected Vehicle Technology available in PDF, EPUB and Kindle. 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.
Smarter New York City
Smarter New York City - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Smarter New York City write by André Corrêa d'Almeida. This book was released on 2018-08-28. Smarter New York City available in PDF, EPUB and Kindle. Innovation is often presented as being in the exclusive domain of the private sector. Yet despite widespread perceptions of public-sector inefficiency, government agencies have much to teach us about how technological and social advances occur. Improving governance at the municipal level is critical to the future of the twenty-first-century city, from environmental sustainability to education, economic development, public health, and beyond. In this age of acceleration and massive migration of people into cities around the world, this book explains how innovation from within city agencies and administrations makes urban systems smarter and shapes life in New York City. Using a series of case studies, Smarter New York City describes the drivers and constraints behind urban innovation, including leadership and organization; networks and interagency collaboration; institutional context; technology and real-time data collection; responsiveness and decision making; and results and impact. Cases include residential organic-waste collection, an NYPD program that identifies the sound of gunshots in real time, and the Vision Zero attempt to end traffic casualties, among others. Challenging the usefulness of a tech-centric view of urban innovation, Smarter New York City brings together a multidisciplinary and integrated perspective to imagine new possibilities from within city agencies, with practical lessons for city officials, urban planners, policy makers, civil society, and potential private-sector partners.
Enhanced Traffic Signal Operation Using Connected Vehicle Data
Enhanced Traffic Signal Operation Using Connected Vehicle Data - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Enhanced Traffic Signal Operation Using Connected Vehicle Data write by Ehsan Bagheri. This book was released on 2017. Enhanced Traffic Signal Operation Using Connected Vehicle Data available in PDF, EPUB and Kindle. 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.
