Traffic intersections are incredibly dangerous for drivers and pedestrians. Statistics from both Canada and the U.S. show a high number of fatalities and serious injuries related to crashes at intersections. In Canada...Traffic intersections are incredibly dangerous for drivers and pedestrians. Statistics from both Canada and the U.S. show a high number of fatalities and serious injuries related to crashes at intersections. In Canada, during 2019, the National Collision Database shows that 28% of traffic fatalities and 42% of serious injuries occurred at intersections. Likewise, the U.S. National Highway Traffic Administration (NHTSA) found that about 40% of the estimated 5,811,000 accidents in the U.S. during the year studied were intersection-related crashes. In fact, a major survey by the car insurance industry found that nearly 85% of drivers could not identify the correct action to take when approaching a yellow traffic light at an intersection. One major reason for these accidents is the “yellow light dilemma,” the ambiguous situation where a driver should stop or proceed forward when unexpectedly faced with a yellow light. This situation is even further exacerbated by the tendency of aggressive drivers to inappropriately speed up on the yellow just to get through the traffic light. A survey of Canadian drivers conducted by the Traffic Injury Research Foundation found that 9% of drivers admitted to speeding up to get through a traffic light. Another reason for these accidents is the increased danger of making a left-hand turn on yellow. According to the National Highway Traffic Safety Association (NHTSA), left turns occur in approximately 22.2% of collisions—as opposed to just 1.2% for right turns. Moreover, a study by CNN found left turns are three times as likely to kill pedestrians than right turns. The reason left turns are so much more likely to cause an accident is because they take a driver against traffic and in the path of oncoming cars. Additionally, most of these left turns occur at the driver’s discretion—as opposed to the distressingly brief left-hand arrow at busy intersections. Drive Safe Now proposes a workable solution for reducing the number of accidents occurring during a yellow light at intersections. We believe this fairly simple solution will save lives, prevent injuries, reduce damage to public and private property, and decrease insurance costs.展开更多
The study of vehicular networks has attracted considerable interest in academia and the industry.In the broad area,connected vehicles and autonomous driving are technologies based on wireless data communication betwee...The study of vehicular networks has attracted considerable interest in academia and the industry.In the broad area,connected vehicles and autonomous driving are technologies based on wireless data communication between vehicles or between vehicles and infrastructures.A Vehicle-to-Infrastructure(V2I)system consists of communications and computing over vehicles and related infrastructures.In such a system,wireless sensors are installed in some selected points along roads or driving areas.In autonomous driving,it is crucial for a vehicle to figure out the ideal routes by the communications between its equipped sensors and infrastructures then the vehicle is automatically moving along the routes.In this paper,we propose a Bezier curve based recursive algorithm,which effectively creates routes for vehicles through the communication between the On-Board Unit(OBU)and the Road-Side Units(RSUs).In addition,this approach generates a very low overhead.We conduct simulations to test the proposed algorithm in various situations.The experiment results demonstrate that our algorithm creates almost ideal routes.展开更多
With the rapid development of connected autonomous vehicles(CAVs),both road infrastructure and transport are experiencing a profound transformation.In recent years,the cooperative perception and control supported infr...With the rapid development of connected autonomous vehicles(CAVs),both road infrastructure and transport are experiencing a profound transformation.In recent years,the cooperative perception and control supported infrastructure-vehicle system(IVS)attracted increasing attention in the field of intelligent transportation systems(ITS).The perception information of surrounding objects can be obtained by various types of sensors or communication networks.Control commands generated by CAVs or infrastructure can be executed promptly and accurately to improve the overall performance of the transportation system in terms of safety,efficiency,comfort and energy saving.This study presents a comprehensive review of the research progress achieved upon cooperative perception and control supported IVS over the past decade.By focusing on the essential interactions between infrastructure and CAVs and between CAVs,the infrastructure-vehicle cooperative perception and control methods are summarized and analyzed.Furthermore,the mining site as a closed scenario was used to show the current application of IVS.Finally,the existing issues of the cooperative perception and control technology implementation are discussed,and the recommendation for future research directions are proposed.展开更多
本文提出了一种用于未来自动驾驶场景的虚拟车道技术,旨在突破当前自动驾驶行业的发展瓶颈,并为未来融合飞行汽车交通系统(Flying Car Transportation Systems,FCTS)的自动驾驶场景提供一种创新性技术方案.虚拟车道技术伴随自动驾驶等...本文提出了一种用于未来自动驾驶场景的虚拟车道技术,旨在突破当前自动驾驶行业的发展瓶颈,并为未来融合飞行汽车交通系统(Flying Car Transportation Systems,FCTS)的自动驾驶场景提供一种创新性技术方案.虚拟车道技术伴随自动驾驶等级的提升协同发展,从面向有人驾驶,到面向全智能驾驶,再到面向本文所提出的L6空地全域自动驾驶,从而实现空地一体化交通的愿景.本文结合了自动驾驶、数字孪生、物联网(Internet of Things,IoT)、人工智能(Artificial Intelligence,AI)等各领域的最新技术对虚拟车道技术在每个发展阶段的应用场景和具体实现方法进行了详细介绍以及可行性分析,对自动驾驶行业明晰未来总体发展趋势和关键技术导向具有开创式的启发意义.展开更多
文摘Traffic intersections are incredibly dangerous for drivers and pedestrians. Statistics from both Canada and the U.S. show a high number of fatalities and serious injuries related to crashes at intersections. In Canada, during 2019, the National Collision Database shows that 28% of traffic fatalities and 42% of serious injuries occurred at intersections. Likewise, the U.S. National Highway Traffic Administration (NHTSA) found that about 40% of the estimated 5,811,000 accidents in the U.S. during the year studied were intersection-related crashes. In fact, a major survey by the car insurance industry found that nearly 85% of drivers could not identify the correct action to take when approaching a yellow traffic light at an intersection. One major reason for these accidents is the “yellow light dilemma,” the ambiguous situation where a driver should stop or proceed forward when unexpectedly faced with a yellow light. This situation is even further exacerbated by the tendency of aggressive drivers to inappropriately speed up on the yellow just to get through the traffic light. A survey of Canadian drivers conducted by the Traffic Injury Research Foundation found that 9% of drivers admitted to speeding up to get through a traffic light. Another reason for these accidents is the increased danger of making a left-hand turn on yellow. According to the National Highway Traffic Safety Association (NHTSA), left turns occur in approximately 22.2% of collisions—as opposed to just 1.2% for right turns. Moreover, a study by CNN found left turns are three times as likely to kill pedestrians than right turns. The reason left turns are so much more likely to cause an accident is because they take a driver against traffic and in the path of oncoming cars. Additionally, most of these left turns occur at the driver’s discretion—as opposed to the distressingly brief left-hand arrow at busy intersections. Drive Safe Now proposes a workable solution for reducing the number of accidents occurring during a yellow light at intersections. We believe this fairly simple solution will save lives, prevent injuries, reduce damage to public and private property, and decrease insurance costs.
基金the Presidential Incentive Awards(No.1103 and No.1105)MCCB summer research award in the University of North Georgia.
文摘The study of vehicular networks has attracted considerable interest in academia and the industry.In the broad area,connected vehicles and autonomous driving are technologies based on wireless data communication between vehicles or between vehicles and infrastructures.A Vehicle-to-Infrastructure(V2I)system consists of communications and computing over vehicles and related infrastructures.In such a system,wireless sensors are installed in some selected points along roads or driving areas.In autonomous driving,it is crucial for a vehicle to figure out the ideal routes by the communications between its equipped sensors and infrastructures then the vehicle is automatically moving along the routes.In this paper,we propose a Bezier curve based recursive algorithm,which effectively creates routes for vehicles through the communication between the On-Board Unit(OBU)and the Road-Side Units(RSUs).In addition,this approach generates a very low overhead.We conduct simulations to test the proposed algorithm in various situations.The experiment results demonstrate that our algorithm creates almost ideal routes.
基金National Key R&D Program of China under Grant 2020YFB1600302.
文摘With the rapid development of connected autonomous vehicles(CAVs),both road infrastructure and transport are experiencing a profound transformation.In recent years,the cooperative perception and control supported infrastructure-vehicle system(IVS)attracted increasing attention in the field of intelligent transportation systems(ITS).The perception information of surrounding objects can be obtained by various types of sensors or communication networks.Control commands generated by CAVs or infrastructure can be executed promptly and accurately to improve the overall performance of the transportation system in terms of safety,efficiency,comfort and energy saving.This study presents a comprehensive review of the research progress achieved upon cooperative perception and control supported IVS over the past decade.By focusing on the essential interactions between infrastructure and CAVs and between CAVs,the infrastructure-vehicle cooperative perception and control methods are summarized and analyzed.Furthermore,the mining site as a closed scenario was used to show the current application of IVS.Finally,the existing issues of the cooperative perception and control technology implementation are discussed,and the recommendation for future research directions are proposed.
文摘本文提出了一种用于未来自动驾驶场景的虚拟车道技术,旨在突破当前自动驾驶行业的发展瓶颈,并为未来融合飞行汽车交通系统(Flying Car Transportation Systems,FCTS)的自动驾驶场景提供一种创新性技术方案.虚拟车道技术伴随自动驾驶等级的提升协同发展,从面向有人驾驶,到面向全智能驾驶,再到面向本文所提出的L6空地全域自动驾驶,从而实现空地一体化交通的愿景.本文结合了自动驾驶、数字孪生、物联网(Internet of Things,IoT)、人工智能(Artificial Intelligence,AI)等各领域的最新技术对虚拟车道技术在每个发展阶段的应用场景和具体实现方法进行了详细介绍以及可行性分析,对自动驾驶行业明晰未来总体发展趋势和关键技术导向具有开创式的启发意义.
