Autonomous vehicles need data and updating continuously, so in this case, IoT and Artificial intelligence help to share the information device to the device. In the future, without human help, robots will manufacture autonomous cars using IoT technology based on customer requirements and prefer these vehicles are very safe and comfortable in transportation systems like human traveling or cargo. Everyday autonomous vehicle technology researchers are solving challenges. Level-3 Autonomous cars came out in 2020. For the last ten years, the automobile industry came forward to researching autonomous vehicle technology (Waymo Google, Uber, Tesla, Renault, Toyota, Audi, Volvo, Mercedes-Benz, General Motors, Nissan, Bosch, and Continental's autonomous vehicle, etc.). The present scenario of human beings is addicted to automation and robotics technology using like agriculture, medical, transportation, automobile and manufacturing industries, IT sector, etc. From the past few years, updating automation technology day by day and using all aspects of using in regular human life. ![]() Down the memory line, autonomous vehicle technology experiments started in 1920 only and controlled by radio technology. Whatever the name but the aim of the technology is the same. The vehicle was one of the top five to successfully finish the autonomous vehicle challenge (AVC) in the Hyundai AVC.Īn autonomous car is also called a self-driving car or driverless car or robotic car. The performance of each module has been validated in K-City under multiple scenarios where Clothoid has been driven safely from the starting point to the goal point. The proposed framework enables obstacle avoidance, pedestrian safety, object detection, road blockage avoidance, path planning for single-lane and multi-lane routes, and safe driving of vehicles throughout the journey. ![]() This research presents Clothoid, a unified framework for fully autonomous vehicles, that integrates the modules of HD mapping, localization, environmental perception, path planning, and control while considering the safety, comfort, and scalability in the real traffic environment. The accurate sensing of the environment and safe driving under various scenarios must be ensured to achieve the highest level of autonomy. The autonomous vehicle is expected to increase road safety while reducing road accidents that occur due to human errors. One of the major reasons is the increase in urbanization and mobility demands. Several accidents have been occurred with autonomous vehicles, including Tesla and Volvo XC90, resulting in serious personal injuries and death. However, building a safely operating fully functional autonomous driving framework is still a challenge. Many autonomous driving frameworks have been developed in the past. In recent years, research and development of autonomous driving technology have gained much interest. Based on our high-performance CRA method, the proposed architecture can be regarded as a novel option for CCWS design. ![]() Latencies in CRA service were analyzed, and it was found that powerful computing resources provided by cloud servers can significantly decrease computational cost, which will indirectly compensate for communication costs in the future. Experimental results show that our method outperforms a referenced method in terms of CRA and achieves better robustness in tolerating communication delays and dropouts. The proposed method and architecture are validated and evaluated through extensive real-world experiments. The CRA is provided as a service by a cloud server. Our method is implemented in a novel server-based architecture, which is different from the commonly used vehicle-based controlled CCWSs. Hence, this paper proposes a new collision risk assessment (CRA) method where sigma trajectories that include multiple possible trajectories considering multiple aspects of vehicular motion are designed to cope with vehicular uncertainties. However, most available approaches in this regard did not consider these uncertainties. In most CCWSs, it is vital to have a detection mechanism based on trajectory predictions where the uncertainties associated with vehicular state and motion are complex. In recent years, the concept of a cooperative collision warning system (CCWS) has been introduced and developed to enhance road safety, and it has been seen as a typical Internet of Vehicles application. The Internet of Things plays an indispensable role in the development of connected vehicles, which will pave the way for road safety applications.
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