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Traffic Signal Control In A Connected And Autonomous Vehicle Environment Considering Pedestrians
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Book Synopsis Traffic Signal Control in a Connected and Autonomous Vehicle Environment Considering Pedestrians by : Xiao Liang
Download or read book Traffic Signal Control in a Connected and Autonomous Vehicle Environment Considering Pedestrians written by Xiao Liang and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Traffic signals help to maintain order in urban traffic networks and reduce vehicle conflicts by dynamically assigning right-of-way to different vehicle movements. However, by temporarily stopping vehicle movements at regular intervals, traffic signals are a major source of urban congestion and cause increased vehicle delay, fuel consumption, and environmental pollution. Connected and Autonomous Vehicle technology may be utilized to optimize traffic operations at signalized intersections, since connected vehicles have the ability to communicate with the surrounding infrastructure and autonomous vehicles can follow the instructions from the signal or a central control system. Connected vehicle information received by a signal controller can be used to help adjust signal timings to tailor to the specific dynamic vehicle demand. Information about the signal timing plan can then be communicated back to the vehicles so that they can adjust their speeds/trajectories to further improve traffic operations. Based on a thorough literature review of existing studies in the area of signal control utilizing information from connected and autonomous vehicles, three research gaps are found: 1) application are limited to unrealistic intersection configurations; 2) methods are limited to a single mode; or, 3) methods only optimize the average value of measure of effectiveness while ignoring the distribution among vehicles. As a part of this dissertation, several methods will be proposed to increase computational efficiency of an existing CAV-based joint signal timing and vehicle trajectory optimization algorithm so that it can be applied to more realistic intersection settings without adding computational burden. Doing so requires the creation of new methods to accommodate features like multiple lanes on each approach, more than two approaches and turning maneuvers. Methods to incorporate human-driven cooperative vehicles and pedestrians are also proposed and tested. A more equitable traffic signal control method is also designed.
Book Synopsis Extended Development and Testing of Optimized Signal Control with Autonomous and Connected Vehicles by :
Download or read book Extended Development and Testing of Optimized Signal Control with Autonomous and Connected Vehicles written by and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This report discusses the development of sensor fusion and LiDAR detection for pedestrians at a signalized intersection, and a new approach to data sharing between the infrastructure and the autonomous vehicle to maximize safety based on increased information regarding the surrounding environment. It also presents the procedure developed to accommodate pedestrians within the signal control optimization environment and the field testing conducted at FDOT’s Traffic Engineering and Research Lab (TERL) to evaluate the hardware and software system.
Book Synopsis Incorporating Social Information Into An Autonomous Vehicle's Decision-Making Process and Control by : Kasra Mokhtari
Download or read book Incorporating Social Information Into An Autonomous Vehicle's Decision-Making Process and Control written by Kasra Mokhtari and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: How can autonomous vehicles offer safer behavior by accounting for social information? Social information includes not only information about the number of pedestrians, but also pedestrians' behavior, age, course of action, etc. While driving, the interaction of a vehicle and the other road users is complicated because each operator acts dynamically and according to their own will, thus creating additional uncertainties for an autonomous vehicle to consider. To address some of these uncertainties and to avoid collisions human drivers use a variety of tricks and heuristics learned during their time driving. However, substituting human drivers with autonomous control systems comes at the price of eliminating the underlying social intelligence of human drivers that makes these predictions possible. Steps should, therefore, be taken to imbue autonomous vehicles with the ability to use social information to increase safety since information about the social environment may provide autonomous vehicles with valuable data influencing how these systems select and moderate their actions. This dissertation develops well-defined methods that will enable an autonomous vehicle to use social information to adjust the vehicle's course of action with the hope of providing a much safer environment for pedestrians, other car drivers, and AV passengers. We first generate our social information dataset by repeatedly driving in State College, PA along the different paths. We then present an initial examination of how social information (i.e. pedestrian density) could be used first for path recognition and then for predicting the number of pedestrians that the vehicle will encounter in the future which is intuitively related to the risk of traveling down a path for autonomous vehicles. Moreover, we develop a method for an AV operating near a college campus to evaluate the risk associated with different options and to select the minimal risk option in the hope of improving safety. We then design a decision-making framework for controlling an autonomous vehicle as it navigates through an unsignalized intersection crowded with pedestrians in both cases where it receives true state of the environment and noisy observations. We hope that the research presented in this dissertation will inspire future researchers to develop autonomous vehicles that more intelligently and efficiently account for pedestrian information in their decision-making framework to make a collision-free world.
Book Synopsis Multi-scale Signal-vehicle Coupled Control with Connected and Autonomous Vehicles by : Qiangqiang Guo
Download or read book Multi-scale Signal-vehicle Coupled Control with Connected and Autonomous Vehicles written by Qiangqiang Guo and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the rise of connected and autonomous vehicles (CAV) and vehicle-to-everything communication technologies, advanced urban traffic control (UTC) has been receiving increasing attention due to the abundant data and control freedom brought by the new techniques. The UTC is a multi-scale problem in both spatial and temporal domains. The goal of this study is to investigate the multi-scale UTC problems in the environment of CAVs. Firstly, we propose a general modeling and control framework for the multi-scale UTC problem and identify the key research needs. We then use this framework to explicitly model, analyze, and solve the two-scale signal-vehicle coupled control problem in the environment of single intersection with 100% CAV penetration, and demonstrate the performance of the proposed method using numerical experiments. Then, we extend the signal-vehicle coupled control algorithm to the environment of multiple intersections with mixed traffic flows of human driven vehicles and CAVs. Considering that for explicit model based methods, the computation burden increases with the size of the traffic network, we develop an imitation learning enhanced method to improve the algorithm efficiency. We conduct various numerical experiments to validate the performance of the proposed model-based and learning-enhanced algorithms.
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 Dynamic Traffic Routing and Adaptive Signal Control in a Connected Vehicles Environment by : Huajun Chai
Download or read book Dynamic Traffic Routing and Adaptive Signal Control in a Connected Vehicles Environment written by Huajun Chai and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation aims to study effective and efficient ways for both travelers and transportation authorities to consider the actions of the other side when they make their corresponding travel or management decisions, such that certain common goals, such as mitigating congestion, reducing cost in travel expenses and improving the overall reliability of the transportation system can be achieved. A novel dynamic traffic routing (DTR) with an adaptive signal control framework is developed to utilize the fast developing wireless communication technologies that makes V2X (Vehicle To Everything) possible. The hyper-path based dynamic traffic routing method takes stochasticity of link travel time into consideration, which ensures robust and reliable routing decisions. In addition, online travel time updating is incorporated into the DTR model. The online updating presented in this dissertation uses both historical information (a priori knowledge) and new information, thanks to the V2X system, to form a posteriori knowledge about the link travel time. Various distributed traffic signal control methods are proposed and tested with the DTR model to cope with the different levels of the traffic demand. The joint dynamic traffic routing and adaptive signal control model developed in this dissertation performs well in most cases. However, the underlying logic of DTR does not guarantee to prevent deadlock from happening. To address this issue, following the study of dynamic traffic routing and adaptive signal control, I formulate a deadlock avoidance model under dynamic user equilibrium with queue spillback. In the proposed model, travelers' route choice is governed by a simple "DLA (DeadLock Avoidance) Routing" rule which is proved to generate deadlock free routing result. Potential deadlocks during the optimization of the model are detected with an algorithm modified based on Floyd Warshall Algorithm. The algorithm then assigns a deadlock potential value to each potential deadlock. The model minimizes this potential, and meanwhile tries to maintain the total travel time in the network at a reasonably low level. Many transportation applications can potentially take advantage of the research results in this dissertation. We explored one interesting and important application scenario-the parking search problem in the final chapter of this dissertation.
Book Synopsis Network Traffic Signal Control with Short-term Origin Destination Demand in a Connected Vehicle Environment Via Mobile Edge Computing by : Can Zhang
Download or read book Network Traffic Signal Control with Short-term Origin Destination Demand in a Connected Vehicle Environment Via Mobile Edge Computing written by Can Zhang and published by . This book was released on 2021 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis develops and analyzes centralized and decentralized network-level traffic signal control system under in a connected vehicle (CV) environment with mobile edge computing (MEC). The goal is to provide a framework of decentralized signal control (DSC) system especially for real-time control and large-scale traffic network. Short-term origin-destination (OD) demand is used as an input given that the technological paradigm assumed is within the CV environment, unlike most previous works that look at network control but in a current technological paradigm. Considering short-term OD demand as inputs, a queue-based dynamic traffic assignment (DTA) model is proposed to predict traffic dynamics in traffic networks with signal control. Although DTA has been an effective tool to describe traffic dynamics for traffic optimization, and many researchers have considered traffic signal control in their models, signal timings have been simplified without considering complex, but realistic, phase sequence and duration restrictions. This work formulates traffic signal timing as a component of the link performance function with three control variables: cycle length, phase split, and offset. In addition, both user-optimal (UO) and system-optimal (SO) DTA problems are solved within a single corridor network. Finally, this thesis provides a simulation-based framework of both centralized and decentralized signal control to solve the network-level traffic signal control optimization problem. For the centralized system, this work solves the issue of optimal control using a three-step naïve method. Because the optimization of large-scale network traffic signals is a Nondeterministic Polynomial Time (NP)-complete problem, the centralized system is further decomposed into a decentralized system where the network is divided into subnetworks. - Each subnetwork has its own agent that optimizes signals within the subnetwork. The proposed control systems are applied to a set of test scenarios constructed using different demand levels in different grid networks. This work also investigates the impact of network decomposition strategy on the signal control system performance. Results show that network decomposition with smaller subnetworks results in less Computational Time (CT), but also increased Average Travel Time (ATT) and Total Travel Delay (TTD). This thesis contributes to the literature by a queue-based DTA model for traffic network with real traffic signal timing plan, a simulation-based framework of DSC system within the MEC-enabled CV environment, and a scalable and extendable decomposition method for a DSC system.
Book Synopsis Autonomous Vehicle Technology by : James M. Anderson
Download or read book Autonomous Vehicle Technology written by James M. Anderson and published by Rand Corporation. This book was released on 2014-01-10 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: The automotive industry appears close to substantial change engendered by “self-driving” technologies. This technology offers the possibility of significant benefits to social welfare—saving lives; reducing crashes, congestion, fuel consumption, and pollution; increasing mobility for the disabled; and ultimately improving land use. This report is intended as a guide for state and federal policymakers on the many issues that this technology raises.
Book Synopsis Implementation of Intersection Management Algorithm Considering Autonomous and Connected Vehicles by : Maninder Singh
Download or read book Implementation of Intersection Management Algorithm Considering Autonomous and Connected Vehicles written by Maninder Singh and published by . This book was released on 2013 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt: Autonomous vehicle development is on its peak these days. The thought of having self-driving cars is close to fruition. A lot of work has been done in the last decade in the field of Autonomous Systems. There are cars that can drive better than humans on highways. They allow for higher speed and safety. But infrastructure does not exist that is friendly to autonomous vehicles such as at intersections. Autonomous vehicles cannot use existing infrastructure to operate efficiently as the current infrastructure has been designed keeping human driven vehicles in mind. New algorithms need to be developed which will allow autonomous vehicles to use existing infrastructure without entirely changing the infrastructure. In this way both human driven and autonomous vehicles can use the infrastructure and human driven vehicles can also take advantage of developments done in the autonomous vehicle field. This can be achieved using smarter intersections which can communicate with the vehicles using vehicle-to-vehicle (V2V) communication and can use the data from the vehicles to optimize signal phase and timing. Additionally such an intersection can also control the flow of traffic by controlling the speed of vehicles.
Book Synopsis Traffic Signal Control Strategies for Pedestrians and Bicyclists by :
Download or read book Traffic Signal Control Strategies for Pedestrians and Bicyclists written by and published by . This book was released on 2022 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the United States, traffic signal timing is traditionally developed to minimize motor vehicle delay at signalized intersections, with minimal attention paid to the needs of pedestrians and bicyclists. The unintended consequence is often diminished safety and mobility for pedestrians and bicyclists. The TRB National Cooperative Highway Research Program's NCHRP Research Report 969: Traffic Signal Control Strategies for Pedestrians and Bicyclists is a guidebook that provides tools, performance measures, and policy information to help agencies design and operate signalized intersections in a way that improves safety and service for pedestrians and bicyclists while still meeting the needs of motorized road users. Supplemental to the report are presentations of preliminary findings, strategies, and summary overview.
Book Synopsis Global Practices on Road Traffic Signal Control by : Keshuang Tang
Download or read book Global Practices on Road Traffic Signal Control written by Keshuang Tang and published by Elsevier. This book was released on 2019-05-03 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Global Practices on Road Traffic Signal Control is a valuable reference on the current state-of-the-art of road traffic signal control around the world. The book provides a detailed description of the common principles of road traffic signal control using a well-defined and consistent format that examines their application in countries and regions across the globe. This important resource considers the differences and special considerations across countries, providing useful insights into selecting control strategies for signal timing at intersections and pedestrian crosswalks. The book's authors also include success stories for coping with increasing traffic-related problems, examining both constraints and the reasons behind them. Presents a comprehensive reference on country-by-country practices on road traffic signal control Compiles and compares approaches across countries Covers theories and common principles Examines the most current systems and their implementation
Book Synopsis Connected and Autonomous Vehicles by : Stephen Parkes
Download or read book Connected and Autonomous Vehicles written by Stephen Parkes and published by Taylor & Francis. This book was released on 2023-02-24 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past decade has seen substantial progress towards the development of Connected and Autonomous Vehicles (CAVs). Accompanying the technological developments, there has been much dialogue around the potential for CAVs to help solve a range of economic, social, and environmental issues. Some of CAVs purported benefits include, for example, greater efficiency in the use of existing transport infrastructure, improved safety through removing human error, and widening access to automobility. However, there are also many potential downsides, and whether and how CAVs will deliver on their promise remains shrouded in much uncertainty and not a small degree of scepticism. This book views developments around CAVs through the lens of local policymakers and the towns and cities they represent. We argue it is now time to expand the dialogue to include consideration for towns and cities beyond those early adopters to understand how they will fare, and how CAVs might interact with other important policy agendas facing them. We discuss the different challenges that CAVs will pose for the urban built environment and the required forms of preparedness for these. We also explore how CAVs will interact with other uses and users of cities, including potentially competing efforts to enhance urban wellbeing and liveability. Finally, we consider how responses to CAVs are being developed and what the implications of these are. This book will appeal to policymakers, practitioners, and academics interested in the potential impacts of CAVs and in understanding more about how they will shape and interact with cities and regions in the near future.
Book Synopsis Network Wide Signal Control Strategy Base on Connected Vehicle Technology by : Lei Zhang
Download or read book Network Wide Signal Control Strategy Base on Connected Vehicle Technology written by Lei Zhang and published by . This book was released on 2018 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Traffic Operations Assessment by : Andalib Shams
Download or read book Traffic Operations Assessment written by Andalib Shams and published by . This book was released on 2018 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt: As traffic congestion increases day by day, it becomes necessary to improve the existing roadway facilities to maintain satisfactory operational and safety performances. Moreover, Deployment of Connected and Autonomous Vehicles (CAV) will increase roadway capacity, but their induced demand may lead to further congestion. Increasing roadway capacity can reduce traffic congestion up to a certain extent, but it can be very costly and sometimes conventional methods are not suitable enough. Using innovative intersection designs, such as the Continuous Flow Intersection (CFI), instead of conventional four-legged intersections, have proven to be beneficial in increasing capacity and reducing congestion. Public transit systems that run in mixed traffic also experience increased travel times and reduction in reliability due to the increased levels of congestion. Implementing transit preferential treatments, often in conjunction with rapid transit modes, is a proven way to improve transit operations along congested corridors. This study focuses on assessing future traffic and transit conditions in year 2040, and potential improvement alternatives along sections of Redwood Road in Salt Lake and Utah Counties, Utah through VISSIM traffic simulation. In addition to the models of existing conditions, five scenarios were developed for 2040: Do-Nothing, Street Widening, implementation of a CFI, Transit Exclusive Lanes, and implementation of Transit Signal Priority (TSP) in conjunction with exclusive lanes. Among the developed scenarios, CFI scenario have been implemented only at the intersection of 9000 S and Redwood Road. Results suggests that, without any improvement, it would be impossible to maintain a satisfactory level of performance in 2040. In the street widening scenario number of lane have been updated to four. This street widening scenario is a possible improvement option, but still underperforms along certain segments and intersections. The conventional four-legged intersection of Redwood Road and 9000 S was replaced with a CFI, which helped in reducing the total delay for both passenger cars and transit. In the Transit Exclusive Lane scenario a lane have been added over the street widening scenario exclusively for transits. So, in this scenario four lanes are for vehicles and one lane is dedicated for transits. Transit exclusive lanes reduced the total intersection transit delay by 20% compared to Do-Nothing. The Transit Signal Priority scenario have been included over the Transit Exclusive Lane scenario. Combining TSP with transit exclusive lanes resulted in a 61% reduction in transit delays, while the vehicular traffic along the corridor also benefited from it. The cross street traffic mostly benefited from street widening, while it experienced some impact with TSP, although it was not statistically significant. TSP also performed well at the introduced CFI, where transit experienced 42% reduction in delay, with an improved performance for vehicular traffic compared to Do-Nothing. In the recent years, improvements in vehicular technology has been significant. Even after this improvement, right now it is only a fraction of what is being expected in the future. Vehicles in the future will be able to sense its environment and navigate the surroundings without any sort of human input. Moreover, vehicles will be able to communicate with other vehicles, infrastructures, pedestrians, and the cloud. These vehicles are introduced as Connected and Autonomous Vehicles. Driving behavior of these vehicles will be different than conventional vehicles. With the help of automation, these vehicles will have a shorter headway, faster perception-reaction time and more uniform speed than conventional vehicles. Using connected technology, vehicles will be able to form platoons and optimize their speed profile and routing decisions. Though it is known that CAV will act more cooperatively than conventional vehicles, there is little development in the improvement of driving behaviors or intersection control strategies to make them more cooperative. Considering these issues, this study developed signalized intersection control strategy algorithm based on TSP and tested the performance of the Intelligent Driver Model which does not consider the human-reaction time along with the developed algorithm. For the developed algorithms it has been assumed that vehicles are fully connected and the automation level is at least four. Alternative scenarios have been developed over the 2040 Do-Nothing scenario with 25%, 50%, 75% and 100% CAV penetration. CAV’s performance has also been assessed in comparison with the Transit Signal Priority scenario which includes all the traditional and innovative improvement strategies implemented in this study. Results suggest that travel delay at intersections and travel time at road segment would decrease with the increase in CAV penetration. Overall network delay and travel time would also decrease with increased CAV penetration. Though initially number of stops increased and average speed decreased, with more penetration both of the parameter performs better.
Book Synopsis Creating Autonomous Vehicle Systems by : Shaoshan Liu
Download or read book Creating Autonomous Vehicle Systems written by Shaoshan Liu and published by Morgan & Claypool Publishers. This book was released on 2017-10-25 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the first technical overview of autonomous vehicles written for a general computing and engineering audience. The authors share their practical experiences of creating autonomous vehicle systems. These systems are complex, consisting of three major subsystems: (1) algorithms for localization, perception, and planning and control; (2) client systems, such as the robotics operating system and hardware platform; and (3) the cloud platform, which includes data storage, simulation, high-definition (HD) mapping, and deep learning model training. The algorithm subsystem extracts meaningful information from sensor raw data to understand its environment and make decisions about its actions. The client subsystem integrates these algorithms to meet real-time and reliability requirements. The cloud platform provides offline computing and storage capabilities for autonomous vehicles. Using the cloud platform, we are able to test new algorithms and update the HD map—plus, train better recognition, tracking, and decision models. This book consists of nine chapters. Chapter 1 provides an overview of autonomous vehicle systems; Chapter 2 focuses on localization technologies; Chapter 3 discusses traditional techniques used for perception; Chapter 4 discusses deep learning based techniques for perception; Chapter 5 introduces the planning and control sub-system, especially prediction and routing technologies; Chapter 6 focuses on motion planning and feedback control of the planning and control subsystem; Chapter 7 introduces reinforcement learning-based planning and control; Chapter 8 delves into the details of client systems design; and Chapter 9 provides the details of cloud platforms for autonomous driving. This book should be useful to students, researchers, and practitioners alike. Whether you are an undergraduate or a graduate student interested in autonomous driving, you will find herein a comprehensive overview of the whole autonomous vehicle technology stack. If you are an autonomous driving practitioner, the many practical techniques introduced in this book will be of interest to you. Researchers will also find plenty of references for an effective, deeper exploration of the various technologies.
Book Synopsis Smart Transport for Cities and Nations by : Christian Claudel
Download or read book Smart Transport for Cities and Nations written by Christian Claudel and published by . This book was released on 2018-06-30 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Deep Learning and Its Applications for Vehicle Networks by : Fei Hu
Download or read book Deep Learning and Its Applications for Vehicle Networks written by Fei Hu and published by CRC Press. This book was released on 2023-05-12 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning (DL) is an effective approach for AI-based vehicular networks and can deliver a powerful set of tools for such vehicular network dynamics. In various domains of vehicular networks, DL can be used for learning-based channel estimation, traffic flow prediction, vehicle trajectory prediction, location-prediction-based scheduling and routing, intelligent network congestion control mechanism, smart load balancing and vertical handoff control, intelligent network security strategies, virtual smart and efficient resource allocation and intelligent distributed resource allocation methods. This book is based on the work from world-famous experts on the application of DL for vehicle networks. It consists of the following five parts: (I) DL for vehicle safety and security: This part covers the use of DL algorithms for vehicle safety or security. (II) DL for effective vehicle communications: Vehicle networks consist of vehicle-to-vehicle and vehicle-to-roadside communications. This part covers how Intelligent vehicle networks require a flexible selection of the best path across all vehicles, adaptive sending rate control based on bandwidth availability and timely data downloads from a roadside base-station. (III) DL for vehicle control: The myriad operations that require intelligent control for each individual vehicle are discussed in this part. This also includes emission control, which is based on the road traffic situation, the charging pile load is predicted through DL andvehicle speed adjustments based on the camera-captured image analysis. (IV) DL for information management: This part covers some intelligent information collection and understanding. We can use DL for energy-saving vehicle trajectory control based on the road traffic situation and given destination information; we can also natural language processing based on DL algorithm for automatic internet of things (IoT) search during driving. (V) Other applications. This part introduces the use of DL models for other vehicle controls. Autonomous vehicles are becoming more and more popular in society. The DL and its variants will play greater roles in cognitive vehicle communications and control. Other machine learning models such as deep reinforcement learning will also facilitate intelligent vehicle behavior understanding and adjustment. This book will become a valuable reference to your understanding of this critical field.
