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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.
The problems of urban traffic in the industrially developed countries have been at the top of the priority list for a long time. While making a critical contribution to the economic well being of those countries, transportation systems in general and highway traffic in particular, also have detrimental effects which are evident in excessive congestion, high rates of accidents and severe pollution problems. Scientists from different disciplines have played an important role in the development and refinement of the tools needed for the planning, analysis, and control of urban traffic networks. In the past several years, there were particularly rapid advances in two areas that affect urban traffic: 1. Modeling of traffic flows in urban networks and the prediction of the resulting equilibrium conditions; 2. Technology for communication with the driver and the ability to guide him, by providing him with useful, relevant and updated information, to his desired destination.
It is likely that autonomous vehicles will be the future of mobility. To handle the increase in autonomy, traffic coordination methods will become indispensable. Based on this, an investigation into the performance of Autonomous Vehicle Group Formation (AVGF) based on a decentralized model and a simulative evaluation in urban environments is needed. An Autonomous Vehicle Group (AVG) is a set of vehicles used for transporting people or goods, such as a car, truck, or bus, that are located, gathered, or classed together and are characterized by constant change or progress within the traffic system. The focus is on decentralized autonomous vehicle grouping, which allows the flexibility of single vehicles to be retained while also enabling the use of group coordination to achieve higher throughput in urban networks, as already witnessed in highway vehicular platoons. A known and practiced concept for urban traffic control at traffic signals is to bundle vehicles passively according to green signal phases; the novelty being active coordination of the vehicles in decentralized groups of interests. Likewise, AVGs make coordinated decisions with and without communication depending on the similarities of their vehicle properties and destinations. AVGs coordinate the motion of traffic, making strategic (i.e., group destination) and tactical (i.e., speed and gaps) group decisions in a street network.
Motorway traffic management systems are useful for improving the traffic conditions on urban motorways. One of the most common motorway traffic management systems are variable speed limit systems. These systems adapt the speed limits based on the prevailing traffic conditions measured by roadside detectors and recommended or compulsory speed limits are shown on variable message signs installed on gantries over the road.Thesystems consist of three parts; the control algorithm used to determine which speed limit to be displayed, a method for estimating the traffic conditions to be used as input for the control algorithm and the infrastructure for application of the variable speed limits. The goal of the systems is often to increase safety or efficiency. Recent development in the field of connected vehicles have opened up for a new type of data source, as the status of a connected vehicle and its surroundings can be communicated at arbitrary locations. Hence, by the use of connected vehicles in variable speed limit systems there is a potential of reducing the amount of roadside equipment. It is even possible to control the connected vehicles towards the current speed limit without the use of variable message signs. This allows for the application of variable speed limits at arbitrary locations. The aim of this thesis is to examine how connected vehicles can be used to improve the efficiency of variable speed limit systems. The thesis contribute with new and improved methods using connected vehicles in all three parts of a variable speed limit system. The suggested methods are evaluated by microscopic traffic simulation. The overall conclusion is that the use of connected vehicles in variable speed limit systems can contribute to improvements in traffic efficiency compared to existing systems. The six papers included in the thesis can be summarized as follows. First, it is shown that traditional variable speed limit systems can be effective for improving the traffic conditions on the motorway and the results can be comparable to more costly alterations by reconstruction of the infrastructure to increase the capacity. Next, the usefulness of connected vehicles for application and control of the speed limits in an existing variable speed limit system is investigated. It is concluded that the design of the control algorithm and the accuracy of the estimated traffic conditions have a great effect on the final outcome of the system. The design of the control algorithm is then examined by evaluation of a number of control algorithms with respect to safety, efficiency and environmental impacts. The main benefits and drawbacks of the algorithms are highlighted and desirable characteristics to include when designing a control algorithm are identified. In two studies, methods making use of connected vehicles for estimating the traffic conditions are proposed. The results show that connected vehicles are useful for improving the accuracy of the estimated traffic conditions through the inclusion of more detailed information and information at locations where detector measurements are not available. Finally, a variable speed limit system is proposed in which connected vehicles play a central role in the estimation of the traffic conditions, as well as in the control algorithm and for application of the speed limit. The system is shown to be useful for improving traffic efficiency during an incident at an arbitrary location along the controlled road.
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.
This book takes a look at fully automated, autonomous vehicles and discusses many open questions: How can autonomous vehicles be integrated into the current transportation system with diverse users and human drivers? Where do automated vehicles fall under current legal frameworks? What risks are associated with automation and how will society respond to these risks? How will the marketplace react to automated vehicles and what changes may be necessary for companies? Experts from Germany and the United States define key societal, engineering, and mobility issues related to the automation of vehicles. They discuss the decisions programmers of automated vehicles must make to enable vehicles to perceive their environment, interact with other road users, and choose actions that may have ethical consequences. The authors further identify expectations and concerns that will form the basis for individual and societal acceptance of autonomous driving. While the safety benefits of such vehicles are tremendous, the authors demonstrate that these benefits will only be achieved if vehicles have an appropriate safety concept at the heart of their design. Realizing the potential of automated vehicles to reorganize traffic and transform mobility of people and goods requires similar care in the design of vehicles and networks. By covering all of these topics, the book aims to provide a current, comprehensive, and scientifically sound treatment of the emerging field of “autonomous driving".