Rui Zhao - IEEE Xplore Author Profile

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Traffic control at signal-free intersections is extensively studied to facilitate cooperative traffic for connected and autonomous vehicles (CAVs). Reinforcement learning (RL) techniques have proven effective for cooperative intersection management (CIM) challenges, but often involves unsafe states due to the arbitrary exploration of trial-and-error mechanism. To tackle the safety challenges assoc...Show More
Autonomous driving (AD) endows vehicles with the capability to drive partly or entirely without human intervention. AD agents generate driving policies based on online perception results, which are crucial to the realization of safe, efficient, and comfortable driving behaviors, particularly in high-dimensional and stochastic traffic scenarios. Currently, deep reinforcement learning (DRL) techniqu...Show More
Although reinforcement learning (RL) methodologies exhibit potential in addressing decision-making and planning problems in autonomous driving, ensuring the safety of the vehicle under all circumstances remains a formidable challenge in practical applications. Current RL methods are predominantly driven by singular reward mechanisms, frequently encountering difficulties in balancing multiple sub-r...Show More
Connected and automated vehicles (CAVs) have the potential to transform traffic management, especially at intersections. Traditional traffic signals might become obsolete with the implementation of autonomous intersection management (AIM) systems, which aim for efficient and safe vehicle flow. Current AIM methods often rely on optimization control algorithms, which are not computationally efficien...Show More
With the recent advancements in machine learning technology, the accuracy of autonomous driving object detection models has significantly improved. However, due to the complexity and variability of real-world traffic scenarios, such as extreme weather conditions, unconventional lighting, and unknown traffic participants, there is inherent uncertainty in autonomous driving object detection models, ...Show More
To ensure the reliability of autonomous driving, the system must be capable of potential hazard identification and appropriate response to prevent accidents. This involves the prediction of possible developments in traffic situations and an evaluation of the potential danger of future scenarios. Precise Collision Risk Assessment (CRA) faces complex challenges due to uncertainties inherent in vehic...Show More
Accurate trajectory prediction for multiple vehicles in complex social interaction environments is essential for ensuring the safety of autonomous vehicles and improving the quality of their planning and control. The social interactions between vehicles significantly influence their future trajectories. However, traditional trajectory prediction models based on Recurrent Neural Networks (RNN) or C...Show More
Autonomous Intersection Management (AIM) systems present a new paradigm for conflict-free cooperation of connected autonomous vehicles (CAVs) at road intersections, the aim of which is to eliminate collisions and improve the traffic efficiency and ride comfort. Given the challenges of current centralized coordination methods in balancing high computational efficiency and robust safety assurance, t...Show More
Video prediction is a meaningful task for it has a wide range of application scenarios. And it is also a challenging task since it needs to learn the internal representation of a given video for both appearance and motion dynamics. The existing methods regard this problem as a spatiotemporal sequence forecasting problem and try to resolve it in a one-shot fashion, which causes the prediction resul...Show More
TTEthernet is a deterministic, congestion-free, and high-bandwidth communication protocol based on the Ethernet standard that provides a powerful network solution for developing safety-critical distributed real-time automotive systems. With the development of intelligence and networking of vehicles, such systems are becoming increasingly connected to external environments; thus, security has becom...Show More