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Author: Maninder Singh Publisher: ISBN: Category : Languages : en Pages : 58
Book Description
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.
Author: Maninder Singh Publisher: ISBN: Category : Languages : en Pages : 58
Book Description
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.
Author: Xiao Liang Publisher: ISBN: Category : Languages : en Pages :
Book Description
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.
Author: Ting Xu Publisher: ISBN: Category : Languages : en Pages :
Book Description
Connected and Autonomous Vehicles (CAVs) provide the opportunity for signal-free intersection navigation. This thesis introduces and demonstrates a centralized cooperative driving algorithm that considers two vehicles approaching a non-signalized multi-way intersection where the safe traversal can be negotiated. It is assumed that the incoming and outgoing directions are known, and individual vehicle velocities are controllable within a specified range of acceleration and for a specified range from the intersection.The proposed algorithm is developed by first considering the time-space interval of possible intersections between the vehicles. This leads to the development of a set of collision patterns that predict intersection situations that do not need to be negotiated. It is shown that these patterns extend readily from two-way intersections to eight-way intersections. In cases where path conflicts are detected within the intersection, the algorithm seeks to minimize the complexity of multi-vehicle coordination by preventing any speed deviation of the first vehicle passing through the intersection. The proposed solution in the algorithm is to redesign velocity profiles of the second vehicle arriving at the intersection, thereby avoiding any interference in the planned trajectory of the first vehicle.The algorithm is agnostic to the number of directions in/out of the intersection, and is readily generalized for ranges in acceleration limits and interaction ranges between vehicles. Based on the different cases where two vehicles original trajectories can cause potential collisions, simulation results show the effectiveness of the algorithm under different approaches, such as allowable velocity ranges, accelerations, and minimum algorithm starting distances.
Author: Abdullah Baz Publisher: ISBN: Category : Autonomous vehicles Languages : en Pages : 98
Book Description
One of the most critical subjects in Intelligent Transportation System (ITS) nowadays is the autonomous vehicle (AV). It is rapidly improving, and it will have a substantial positive effect on traffic safety and efficiency. Most of auto manufacturer companies and tech industries are spending a lot of money on research for developing autonomous vehicles. AV would have an excellent contribution to managing and controlling intersections. This study introduces a decision-making algorithm for autonomous vehicles at an intersection to optimize the intersection capacity and minimize delay time by using Game Theory mathematical models. This model using vehicle-to-infrastructure (V2I) communication features that will be available in AV so that vehicles are able to communicate with roadside unit (RSU) and with each other to determine which one goes first, depending on different factors such as their speeds and locations, and vehicle size, taking in consideration the safety of the vehicles so we can have collision free intersection. Two different mathematical models were developed; one with %100 autonomous vehicles and the other one is when we have mix traffic, autonomous vehicles, and ordinary vehicles. A simulation model was developed using a standard microscopic simulation platform VISSIM to implement this algorithm. A comparison of the proposed method and two other ordinary intersection control method; traffic lights, and roundabout was made to calculate the total delay of the intersection for each intersection management method. The simulation ran on three different traffic volume, High, moderate, and low volume. Moreover, three different speeds for each traffic volume. The results shows that the proposed system reduces the total delay by more than 65 percent compared with the roundabout, and about 85 percent comparing with a signalized intersection. Another simulation was done for the second scenario, mixed traffic, also a comparison between the proposed methods; roundabout, and the signalized intersection was made for the same cases of various speeds and volume. For model two, results show 30% reduction in delay compared to the roundabout and 89% compared to signalized intersections.
Author: Umar Zakir Abdul Hamid Publisher: Springer Nature ISBN: 3030660427 Category : Technology & Engineering Languages : en Pages : 345
Book Description
This book combines comprehensive multi-angle discussions on fully connected and automated vehicle highway implementation. It covers the current progress of the works towards autonomous vehicle highway development, which encompasses the discussion on the technical, social, and policy as well as security aspects of Connected and Autonomous Vehicles (CAV) topics. This, in return, will be beneficial to a vast amount of readers who are interested in the topics of CAV, Automated Highway and Smart City, among many others. Topics include, but are not limited to, Autonomous Vehicle in the Smart City, Automated Highway, Smart-Cities Transportation, Mobility as a Service, Intelligent Transportation Systems, Data Management of Connected and Autonomous Vehicle, Autonomous Trucks, and Autonomous Freight Transportation. Brings together contributions discussing the latest research in full automated highway implementation; Discusses topics such as autonomous vehicles, intelligent transportation systems, and smart highways; Features contributions from researchers, academics, and professionals from a broad perspective.
Author: Michael W. Levin Publisher: ISBN: Category : Automated vehicles Languages : en Pages : 34
Book Description
Autonomous vehicles create new opportunities for innovative intelligent traffic systems. Variable speed limits, which is a speed management systems that can adjust the speed limit according to traffic condition or predefined speed control algorithm on different road segments, can be better implemented with the cooperation of autonomous vehicles. These compliant vehicles can automatically follow speed limits. However, non-compliant vehicles will attempt to pass the moving bottleneck created by the compliant vehicle. This project builds a multi class cell transmission model to represent the relation between traffic flow parameters. This model can calculate flows of both compliant and non-compliant vehicles. An algorithm is proposed to calculate variable speed limits for each cell of the cell transmission model. This control algorithm is designed to reduce the stop-and-go behavior of vehicles at traffic signals. Simulation is used to test the effects of VSLs on an example network. The result shows that VSL is effective at reducing the energy consumption of the whole system and reduce the likelihood of crash occurrence.
Author: Antonio Artuñedo Publisher: Springer Nature ISBN: 3030459055 Category : Technology & Engineering Languages : en Pages : 205
Book Description
This book describes an effective decision-making and planning architecture for enhancing the navigation capabilities of automated vehicles in the presence of non-detailed, open-source maps. The system involves dynamically obtaining road corridors from map information and utilizing a camera-based lane detection system to update and enhance the navigable space in order to address the issues of intrinsic uncertainty and low-fidelity. An efficient and human-like local planner then determines, within a probabilistic framework, a safe motion trajectory, ensuring the continuity of the path curvature and limiting longitudinal and lateral accelerations. LiDAR-based perception is then used to identify the driving scenario, and subsequently re-plan the trajectory, leading in some cases to adjustment of the high-level route to reach the given destination. The method has been validated through extensive theoretical and experimental analyses, which are reported here in detail.
Author: Shaoshan Liu Publisher: Morgan & Claypool Publishers ISBN: 1681731673 Category : Computers Languages : en Pages : 285
Book Description
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.
Author: Slobodan Gutesa Publisher: ISBN: Category : Languages : en Pages : 113
Book Description
The concept evaluation through microsimulation reveals significant mobility improvements compared to contemporary corridor management approach. The results for selected test-bed locations on signalized arterials in New Jersey reveals up to 19.5 % reduction in overall corridor travel time depending on different market penetration and lane configuration scenario. It is also discovered that operational scenarios with a possibility of utilizing reserved lanes for movement of automated vehicles further increases the effectiveness of the proposed algorithm. In addition, the proposed control algorithm is feasible under imperfect C/AV market penetrations showing mobility improvements even with low market penetration rates.
Author: James M. Anderson Publisher: Rand Corporation ISBN: 0833084372 Category : Transportation Languages : en Pages : 215
Book Description
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.
Author: Maninder Singh
Author: Maninder Singh
Author: Xiao Liang
Author: Ting Xu
Author: Abdullah Baz
Author: Umar Zakir Abdul Hamid
Author: Michael W. Levin
Author: Antonio Artuñedo
Author: Shaoshan Liu
Author: Slobodan Gutesa
Author: James M. Anderson