Browsing by Subject "collision avoidance"

Now showing 1 - 3 of 3
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    Collision avoidance and Drone surveillance using Thread protocol in V2V and V2I communications
    (IEEE, 2019-07) Chitanvis, Rajas; Ravi, Niranjan; Zantye, Tanmay; El-Sharkawy, Mohamed; Electrical and Computer Engineering, School of Engineering and Technology
    According to the World Health Organizations (WHO) report nearly 1.25 million people die in road accidents every year. This creates a need for Advanced Driver Assist Systems (ADAS) which can ensure safe travel. To tackle the above challenge in existing the ADAS, Intra-vehicular communications (V2V) and vehicle to infrastructure communications (V2I) has been one of the predominant research topics nowadays due to the rapid growth of automobile industries and ideology of producing autonomous cars in the near future. The key feature of V2V communication is vehicle to vehicle collision detection by transmitting information like vehicle speed and position of a vehicle to other vehicles in the same location using wireless sensor networks (WSN). On the other hand, Unmanned Aerial Vehicle (UAV) systems are growing at a rapid rate in various aspects of life including dispatch of medicines and undergo video surveillance during an emergency due to less air traffic. This paper demonstrates the practice of integrating V2V communication with Thread, one of the low power WSN for data transmission, to initiate adaptive cruise control in a vehicle during a crisis. Also, UAV systems are employed as a part of V2I system to provide aerial view video surveillance if any accident occurs.
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    Collision-Free Path Planning for Automated Vehicles Risk Assessment via Predictive Occupancy Map
    (IEEE, 2020-11) Shen, Dan; Chen, Yaobin; Li, Lingxi; Chien, Stanley; Electrical and Computer Engineering, School of Engineering and Technology
    Vehicle collision avoidance system (CAS) is a control system that can guide the vehicle into a collision-free safe region in the presence of other objects on road. Common CAS functions, such as forward-collision warning and automatic emergency braking, have recently been developed and equipped on production vehicles. However, these CASs focus on mitigating or avoiding potential crashes with the preceding cars and objects. They are not effective for crash scenarios with vehicles from the rear-end or lateral directions. This paper proposes a novel collision avoidance system that will provide the vehicle with all-around (360-degree) collision avoidance capability. A risk evaluation model is developed to calculate potential risk levels by considering surrounding vehicles (according to their relative positions, velocities, and accelerations) and using a predictive occupancy map (POM). By using the POM, the safest path with the minimum risk values is chosen from 12 acceleration-based trajectory directions. The global optimal trajectory is then planned using the optimal rapidly exploring random tree (RRT*) algorithm. The planned vehicle motion profile is generated as the reference for future control. Simulation results show that the developed POM-based CAS demonstrates effective operations to mitigate the potential crashes in both lateral and rear-end crash scenarios.
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    A Situation-Aware Collision Avoidance Strategy for Car-Following
    (IEEE, 2018-07) Li, Li; Peng, Xinyu; Wang, Fei-Yue; Cao, Dongpu; Mechanical and Energy Engineering, School of Engineering and Technology
    In this paper, we discuss how to develop an appropriate collision avoidance strategy for car-following. This strategy aims to keep a good balance between traffic safety and efficiency while also taking into consideration the unavoidable uncertainty of position/speed perception/measurement of vehicles and other drivers. Both theoretical analysis and numerical testing results are provided to show the effectiveness of the proposed strategy.