Дисертації з теми "Connected and Automated Vehicles (CAVs)"
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Kero, Chanelle. "A Literature Review of Connected and Automated Vehicles : Attack Vectors Due to Level of Automation." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-80322.
Повний текст джерелаNarasimhan, Ramakrishnan Akshra. "Design and Evaluation of Perception System Algorithms for Semi-Autonomous Vehicles." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1595256912692618.
Повний текст джерелаKim, Bumsik. "Modeling Automated Vehicles and Connected Automated Vehicles on Highways." Diss., Virginia Tech, 2021. http://hdl.handle.net/10919/103012.
Повний текст джерелаDoctor of Philosophy
The deployment of Automated Vehicles (AV) is starting to become widespread throughout transportation, resulting in the recognition and awareness by legislative leaders of the potential impact on transportation operations. To assist transportation operators in making the needed preparations for these vehicles, an in-depth study regarding the impact of AV and Connected Automated Vehicles (CAV) is needed. In this research, the impact of AV and CAV on the highway setting is studied. This study addresses car-following models that are currently used for simulating AV and CAV. Diverse car-following models, such as the Intelligent Driver Model (IDM), the IDM with traffic adaptive driving Strategy (SIDM), the Improved IDM (IIDM), the IIDM with Constant-Acceleration Heuristic (CAH), and the MIcroscopic model for Simulation of Intelligent Cruise control (MIXIC) were examined with the state-of-the-art vehicle trajectory data. The Highway Drone dataset (HighD) were analyzed through the implementation of genetic algorithm to gain more insight about the trajectories of these vehicles. In 2020, there is no commercially available gully automated vehicle available to the public, although many companies are conducting in field testing. This research generated AV trajectories based on the actual vehicle trajectories from the High-D dataset and adjusts those trajectories to account for ideal AV operations. The analysis from the fitted trajectory data shows that the calibrated IIDM with CAH provides a best fit on AV behavior. Next, the AV and CAV were modeled in microscopic perspective to show the impact of these vehicles on a corridor. The traffic simulation software, VISSIM, modified by implementing an external driver model to govern the interactions between Legacy Vehicles (LV), AV, and CAV on a basic and merging highway segment as well as a model of the Interstate 95 corridor south of Richmond, Virginia. From the analysis, this research revealed that the AV and CAV could increase highway capacity significantly. Even with a small portion of AV or CAV, the roadway capacity increased. On I-95, CAV performed better than AV because of Cooperative Adaptive Cruise Control (CACC) and platooning due to CAV's ability to coordinate movement through communication; however, in weaving segments, CAV underperformed AV. This result indicates that the CAV algorithms would need to be flexible in order to maintain flow in areas with weaving sections. Lastly, diverse operational conditions, such as different heavy vehicle market penetration and different aggressiveness were examined to support traffic operators transition to the introduction of AV and CAV. Based on the analysis, the study concludes that the different aggressiveness could mitigate congestion in all cases if the proper aggressiveness level is selected considering the current traffic condition. Overall, the dissertation provides guidance to researchers, traffic operators, and lawmakers to model, simulate, and evaluate AV and CAV on highways.
Liu, Peng. "Distributed Model Predictive Control for Cooperative Highway Driving." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1500564857136091.
Повний текст джерелаMangette, Clayton John. "Perception and Planning of Connected and Automated Vehicles." Thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/98812.
Повний текст джерелаMaster of Science
Connected and Automated Vehicles are an emerging area of research that involve integrating computational components to enable autonomous driving. This work considers two of the major challenges in this area of research. The first half of this thesis considers how to design a perception system in the vehicle that can correctly track other vehicles and assess their relative importance in the environment. A sensor fusion system is designed which incorporates information from different sensor types to form a list of relevant target objects. The rest of this work considers the high-level problem of coordination between autonomous vehicles. A planning algorithm which plans the paths of multiple autonomous vehicles that is guaranteed to prevent collisions and is empirically faster than existing planning methods is demonstrated.
Harper, Corey David. "Transitioning to a Connected and Automated Vehicle Environment: Opportunities for Improving Transportation." Research Showcase @ CMU, 2017. http://repository.cmu.edu/dissertations/1007.
Повний текст джерелаMcManus, Ian Patrick. "The Impact of Cyberattacks on Safe and Efficient Operations of Connected and Autonomous Vehicles." Thesis, Virginia Tech, 2021. http://hdl.handle.net/10919/104891.
Повний текст джерелаMaster of Science
The landscape of transportation is quickly shifting as transportation technologies continue to increase in intelligence and complexity. The transportation industry is shifting its focus to Connected and Autonomous Vehicles (CAVs). The move to more autonomous and intelligent transportation systems brings with it a promise of increased transportation equity, efficiency, and safety. However, one aspect that is often overlooked in this shift is cybersecurity. As intelligent systems and vehicles have been introduced, a large amount of research has been conducted showing cyber vulnerabilities in them. With a new connected transportation system emerging, a multidisciplinary approach will be required to prevent and handle attacks. Ensuring protection against cyberattacks is a key objective moving forward. The first step to developing this system is understanding how different cyberattacks can negatively impact the operations of the transportation system. This research aimed to measure the safety and efficiency impacts of an attack on the transportation network. To do so, a simulation was developed to model an intelligent urban road network. Vehicles made reservations at each intersection they passed – effectively simulating an autonomous vehicle network. Denial of Service (DoS) and Man in the Middle (MITM) attacks were simulated by dropping, and delaying vehicle's intersection reservation requests, respectively. These cyberattacks were modeled with varying degrees of severity to test the different impacts on the transportation network. Analysis showed that severe attacks can have significant impact on the transportation network's operations. The worst-case scenario for each attack introduced an over 20% increase in delay per vehicle. The simulation showed also that increasing the number of attacked intersections directly related to decreased safety and operational efficiency. Successful attacks also produced a high level of variance in their impact. One other key finding was that a single compromised RSU had very limited impact on the transportation network. These findings highlight the importance of developing security and resilience in a connected vehicle environment. Building a transportation network that can respond to an initial attack and prevent it from impacting the entire network is crucial in limiting the negative effects of the attack. If proper resilience planning is not implemented for CAVs, hackers could cause great harm to safety and efficiency with relative ease. The next generation of vehicular transportation must be able to withstand cyberattacks to function. Understanding their impact is a key first step for engineers and planners on the long road to ensuring a secure transportation network.
Almobayedh, Hamad Bader. "Simulation of the Impact of Connected and Automated Vehicles at a Signalized Intersection." University of Dayton / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1557207826602638.
Повний текст джерелаEl-Dabaja, Sarah S. "Drivers of "Driverless" Vehicles: A Human Factors Study of Connected and Automated Vehicle Technologies." Ohio University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1576670482075765.
Повний текст джерелаGupta, Shobhit. "Look-Ahead Optimization of a Connected and Automated 48V Mild-Hybrid Electric Vehicle." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1554478434629481.
Повний текст джерелаMonteuuis, Jean-Philippe. "Resilience by design & failures forecasting for a connected autonomous vehicle." Thesis, Institut polytechnique de Paris, 2020. http://www.theses.fr/2020IPPAT003.
Повний текст джерелаAutonomous vehicles with an automation level 5 will drive autonomously in any road scenarios such as highways, snowy roads, urban areas, or traffic jams. The integration of V2X communication, as a new source of perception for the vehicle could remove the limitations of local perception by communicating with an occluded pedestrian or by detecting in advance the presence of a vehicle under a heavy mist. However, this V2X communication may be a new source of attacks threatening the vehicle perception. Current countermeasures are not designed for all autonomous vehicles because these countermeasures require the driver assistance or work with a specific set of sensors. Therefore, the thesis aims to propose a generic failure resilient perception architecture for all types of connected and autonomous vehicles supporting different kinds of sensors. In this thesis, we propose a generic perception architecture named GPA with its failure resilient perception algorithm (FRPA). We propose a new threat analysis and risk assessment method named SARA that identifies and assess the risk of attacks targeting connected and automated vehicles with an automation level 5. To identify where and how these attacks occur, we propose an attacker and a security goal model for all automotive perception systems. We implemented two modules of our failures resilient perception algorithm (FRPA): a Machine Learning based Failure Classifier and a V2X-Sensor Correlation Module considering three kinds of source: camera, radar, and V2X. We highlighted several new attacks in the perception pipeline and raise the need for new security countermeasures such as the physical integrity of road infrastructures and trustworthy perception algorithms. Besides, our countermeasures based on machine learning and sensor correlation showed very accurate results to detect and classifies perception failures (over 90% accuracy score). Finally, the ideas developed in the thesis resulted in 10 filled patents and several publications
Zohdy, Ismail Hisham. "Development and Testing Of The iCACC Intersection Controller For Automated Vehicles." Diss., Virginia Tech, 2013. http://hdl.handle.net/10919/51743.
Повний текст джерелаPh. D.
Alanazi, Fayez K. "Improving Operation Efficiency of A MAjor-Minor T-intersection in Mixed Traffic with Connected Automated Vehicles." University of Akron / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=akron1625770901762184.
Повний текст джерелаZhou, Yue. "Trajectory planning strategies of connected automated vehicles for cooperative on-ramp merging and mainline facilitating Maneuvers." Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/132687/1/Yue_Zhou_Thesis.pdf.
Повний текст джерелаAnnam, Raja Bharat. "Synthetic Innovation to Complex Intersection Control: Intelligent Roundabout in Connected Vehicle Environment." University of Cincinnati / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1623169949508287.
Повний текст джерелаAnany, Hossam. "Effectiveness of a Speed Advisory Traffic Signal System for Conventional and Automated vehicles in a Smart City." Thesis, Linköpings universitet, Kommunikations- och transportsystem, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-156650.
Повний текст джерелаKang, Kyungwon. "Enhancing Freeway Merge Section Operations via Vehicle Connectivity." Diss., Virginia Tech, 2019. http://hdl.handle.net/10919/103198.
Повний текст джерелаDoctor of Philosophy
Driving behaviors considerably affect the traffic flow; especially a lane change occasionally forces rear vehicles in a target lane to decrease speed or stop, hence it is considered as one of primary sources causing traffic congestion. U.S. Department of Transportation (DOT) announced that freeway bottleneck including merge section contributes to freeway traffic congestion more than 40 percent while traffic incidents count for only 25 percent of freeway congestion. This study, therefore, selected a freeway merge section, where mandatory lane changes are required, as a target area for the study. The emerging technologies, such as autonomous vehicles (AVs) and vehicle connectivity, are expected to bring about improvement in mobility, safety, and environment. Based upon these backgrounds, the objective of this study was determined to enhance freeway merge section operations based on the advanced technologies. To achieve the objective, first this study focused on understanding driving behaviors of human drivers. Decision-making for lane-changing behaviors is complicated as the closest following vehicle in the target lane also behaves concerning to the lane change (reaction to the lane-changing intention), i.e., there is apparent interaction between drivers. For example, the vehicle sometimes interferes the merging vehicle's lane-changing by decreasing a gap. To model the decision-making properly, this study modeled the non-cooperative merging behaviors using a game theoretical approach which mathematically explains the interaction (e.g., cooperation or conflict) between intelligent decision-makers. It was modeled for two vehicles, i.e., the merging vehicle in acceleration lane and a following vehicle in freeway rightmost lane, with possible actions of each vehicle. This model includes how each vehicle chooses an action in consideration of rewards. The developed model showed prediction accuracy of approximately 86% against empirical data collected at a merge section on US 101 highway. This study additionally evaluated the proposed model's rational decision-making performance in various merging situations using an agent-based simulation model. These evaluation results indicate that the developed model can depict merging maneuvers based on practical decision-making. Since most existing lane-changing models were developed from the standpoint of the lane-changing vehicle only, this study anticipates that a lane-changing model including practical decision-making process can be used to precisely analyze traffic flow in microscopic traffic simulation. Additionally, an AV should behave as a human-driven vehicle in order to coexist in traditional transportation system, and can predict surrounding vehicle's movement. The developed model in this study can be a part of AV's driving strategy based on perception of human behaviors. In a future transportation environment, vehicle connectivity enables to identify the surrounding vehicles and transfer the data between vehicles. Also, autonomous driving behaviors can be programmed to reduce competition by predicting behaviors of surrounding human-driven vehicles. This study proposed the cooperative maneuver planning which future connected and automated vehicles (CAVs) avoid choosing the non-cooperative actions based on the game model. If a competitive action is anticipated, in other words, a CAV changes its action to be cooperative without selfish driving. Simulation results showed that the proposed cooperative maneuver planning can improve traffic flow at a freeway merge section. Lastly, the optimal lane selection (OLS) algorithm was also proposed to provide a driver the more efficient lane information in consideration of real-time downstream traffic data transferred via a long-range wireless communication. Simulation case study on I-66 highway proved that the proposed OLS can improve the system-wide freeway traffic flow and lane allocation. Overall, the present work addressed developing the game model for merging maneuvers in a traditional transportation system and suggesting use of efficient algorithms in a CAV environment. These findings will contribute to enhance performance of the microscopic simulator and prepare the new era of future transportation system.
Goel, Shlok. "Research, Design, and Implementation of Virtual and Experimental Environment for CAV System Design, Calibration, Validation and Verification." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1595368946630713.
Повний текст джерелаMohammadian, Saeed. "Freeway traffic flow dynamics and safety: A behavioural continuum framework." Thesis, Queensland University of Technology, 2021. https://eprints.qut.edu.au/227209/1/Saeed_Mohammadian_Thesis.pdf.
Повний текст джерелаZhang, Hongchang. "Ordonnancement cyclique robuste appliqué à la gestion des conteneurs dans les ports maritimes de taille moyenne." Thesis, Ecole centrale de Lille, 2014. http://www.theses.fr/2014ECLI0018/document.
Повний текст джерелаThis PhD thesis is dedicated to propose a robust cyclic scheduling methodology applied to container management of medium sized seaport which faces ever changing terminal conditions and the limited predictability of future events and their timing. The robust cyclic scheduling can be seen not just a predictable scheduling to compute a container transportation schedule, but also a reactive scheduling to eliminate the disturbances in real time. In this work, the automated intelligent vehicles (AIV) are used to transport the containers, and the P-time strongly connected event graph (PTSCEG) is used as a graphical tool to model the container transit procedures. Before the arrival of the container vessel, a cyclic container transit schedule can be given by the mixed integer programming (MIP) method in short time. The robustness margins on the nodes of the system can be computed by robustness algorithms in polynomial computing time. After the stevedoring begins, this robust cyclic schedule is used. When a disturbance is observed in system, it should be compared with the known robustness margin. If the disturbance belongs to the robustness margin, the robustness algorithm is used to eliminate the disturbance in a few cycle times. If not, the MIP method is used to compute a new cyclic schedule in short time
(9872492), Tara Radvand. "Sustainable Routing Guidance for a Road Network with Work Zones During the Connected and Automated Vehicles Era." Thesis, 2020.
Знайти повний текст джерелаEmerging technologies in transportation engineering including connected and automated vehicles (CAVs) exhibit much potential to solve a variety of persistent problems that have impaired the safety and mobility performance of transportation systems. A well-known context of such problems is the construction work zone where agencies have grappled with solutions that range from no closure, partial closure to full closure of road sections during construction, rehabilitation, or maintenance work. Road agencies also seek to develop and implement such workzone plans in a manner that does not unduly jeopardize the economic, social and environmental resources of the road users and the community where the workzone is located. In order to ensure that these three components of sustainable development are attained during road construction workzone management, road agencies seek to develop and implement tools that they can use to guide road users in a network to minimize overall delay, emissions, and fuel consumption. This thesis examines this specific context of highway administration. The thesis developed detour routing guidance for the road users in a road network with work zones in case of full closure, in a manner that is consistent with sustainable development. The research did this for the Automated vehicles (this unlikely scenario is merely considered to demonstrate the potential of connectivity in the network) and the era of connected and automated vehicles. In doing this, the thesis identified the potential benefits that CAV technology can offer in sustainable systemwide management of road work zones. The thesis considered the following sustainability-related evaluation criteria: economic (accessibility to businesses, user costs of fuel consumption, and user costs of travel delay; social (rapid access by emergency services such as ambulance); and environmental (noise pollution and Greenhouse Gas (GHG) emissions). The routing optimization was modeled as a linear programming problem and numerical experiments were carried out. The road network of Sioux Falls city was used to demonstrate the study results. The results suggest that the developed optimal sustainable routing scheme yielded significant improvement in terms of the sustainability criteria while maintaining the acceptable levels of service The results also provided insights on the prospective benefits of routing schemes developed via system optimal management (achieved through centrally-guided detour movements that is facilitated by CAV technology) vis-à-vis user equilibrium management, specifically, Nash Equilibrium.
(11173323), Hanlin Chen. "Adaptive Safety and Cyber Security for Connected and Automated Vehicle System." Thesis, 2021.
Знайти повний текст джерелаThis dissertation discussed the potential benefits that CAV systems can bring to the
general well-being, and how the threat lies within the CAV system can affect its performance and
functionality.
Particularly, this dissertation discovered how CAV technology can benefit homeland security and crime investigations involving child abduction crimes. By proposing the initial design network, this dissertation proposed a solution that enhances the current AMBER Alert system using CAV technology. This dissertation also discussed how CAV technology can help perception in corner-case driving scenarios and reduce the risk of traffic accidents, by proposing a dataset that covers various corner cases including different weather and lighting conditions targeting the work zone. Evaluation is made on the collected data and several impact factors have been figured out.
This dissertation also discussed an attack scenario that a ROS-based CAV platform was attacked by DoS attacks. We analized the system response after we attacked the system. Discussion and analysis was made on the functionality and stability of the system.
Overall, we determined that CAV technology can greatly benefit in general well-being, and threats within the CAV system can cast potential negative benefits once the CAV system is being attacked.
"Flocking Modeling, Control, and Optimization of Connected and Automated Vehicles for Safe and Efficient Mobility." Doctoral diss., 2020. http://hdl.handle.net/2286/R.I.57256.
Повний текст джерелаDissertation/Thesis
Doctoral Dissertation Systems Engineering 2020
Zou, Yun. "The Role That Connected and Automated Vehicles Can Play In Re-Organizing Traffic Flow: Work Zones and Emergency Services." Thesis, 2020. http://hdl.handle.net/10453/142435.
Повний текст джерелаThe extensive progresses in computer science and communication technology in recent decades facilitate the development of the connected and automated vehicles (CAV). Since the emergence of the concept, the commercialization of CAV has been looked forward to providing an effective tool to the regulation of the freeway re-organizing traffic flow who normally initiate the evolvement of the congestion. To analyse the benefits of the CAV on traffic dispersion, the re-organizing traffic in the work zone and the incident-affected zone (under emergency services) were adopted as two cases of non-recurrent congestion, and the microscopic simulations were conducted on the basis of various car-following models and lane-change models. Furthermore, collaborative instances were added to the traditional traffic dynamic models to emulate the motions of the CAV. Trajectories data extracted from NGSIM open-access database were applied to calibrate the Bayes-classifier-based lane-change prediction model in order to better emulate the human drivers’ lane-change decision and to assist the CAV’s collaborations. With the increasing percentage of the CAV, the traffic congestion on the aforementioned bottlenecks were significantly mitigated. While CAV are proved to be capable of facilitate the cooperative lane-changes, they were also trained to refuse the lane-change request if there would be great impact on the target lanes. Although the lane-changes would inevitably impact the target lanes owing to the increasing densities and the disturbances during the lane-change motions, the simulation results showed that CAV are capable of minimizing the negative effects for the entire traffic system’s perspective.