相关论文: A Practical-Driven Framework for Transitioning Dri…

Accurate positioning is known to be a fundamental requirement for the deployment of Connected Automated Vehicles (CAVs). To meet this need, a new emerging trend is represented by cooperative methods where vehicles fuse information coming…

The field of autonomous vehicle research is advancing rapidly, necessitating platforms that meet real-time performance, safety, and security requirements for practical deployment. AUTOSAR Adaptive Platform (AUTOSAR AP) is widely adopted in…

Sensor fusion is crucial for an accurate and robust perception system on autonomous vehicles. Most existing datasets and perception solutions focus on fusing cameras and LiDAR. However, the collaboration between camera and radar is…

For autonomous vehicles to operate without human intervention, information sharing from local sensors plays a fundamental role. This can be challenging to handle with bandwidth-constrained communication systems, which calls for the adoption…

As transportation technology advances, the demand for connected vehicle infrastructure has greatly increased to improve their efficiency and safety. One area of advancement, Cooperative Driving Automation (CDA) still relies on expensive…

It is widely acknowledged that drivers should remain in the control loop of automated vehicles before they completely meet real-world operational conditions. This paper introduces an `indirect shared control' scheme for steer-by-wire…

Automated driving system - dedicated vehicles (ADS-DVs), specially designed for people with various disabilities, can be beneficial to improve their mobility. However, research related to autonomous vehicles (AVs) for people with cognitive…

Comprehensive and efficient validation of connected and automated vehicles (CAVs) is critical prior to real-world deployment. While simulation-based testing offers scalability, existing approaches often lack seamless integration with real…

Real-time perception and motion planning are two crucial tasks for autonomous driving. While there are many research works focused on improving the performance of perception and motion planning individually, it is still not clear how a…

This paper addresses the challenge of collision-free motion planning in automated navigation within complex environments. Utilizing advancements in Deep Reinforcement Learning (DRL) and sensor technologies like LiDAR, we propose the TD3-DWA…

Autonomous driving systems (ADS) are increasingly deployed in real traffic, yet testing remains fundamentally challenging due to open environments, complex scenarios, and the lack of established processes and metrics. Despite extensive…

With the rapid development of intelligent vehicles and Advanced Driver-Assistance Systems (ADAS), a new trend is that mixed levels of human driver engagements will be involved in the transportation system. Therefore, necessary visual…

In this paper, we present our software sensor fusion framework for self-driving cars and other autonomous robots. We have designed our framework as a universal and scalable platform for building up a robust 3D model of the agent's…

Scalable systems for automated driving have to reliably cope with an open-world setting. This means, the perception systems are exposed to drastic domain shifts, like changes in weather conditions, time-dependent aspects, or geographic…

Advanced Driver Assistance Systems (ADAS) and Advanced Driving Systems (ADS) are key to improving road safety, yet most existing implementations focus primarily on the vehicle ahead, neglecting the behavior of following vehicles. This…

Autonomous motion planning under unknown nonlinear dynamics presents significant challenges. An agent needs to continuously explore the system dynamics to acquire its properties, such as reachability, in order to guide system navigation…

Scenario-based testing for automated driving systems (ADS) must be able to simulate traffic scenarios that rely on interactions with other vehicles. Although many languages for high-level scenario modelling have been proposed, they lack the…

Autonomous vehicle platforms of varying spatial scales are employed within the research and development spectrum based on space, safety and monetary constraints. However, deploying and validating autonomy algorithms across varying…

The paper proposes a method for the correct by design coordination of autonomous driving systems (ADS). It builds on previous results on collision avoidance policies and the modeling of ADS by combining descriptions of their static…

We present a LiDAR-based and real-time capable 3D perception system for automated driving in urban domains. The hierarchical system design is able to model stationary and movable parts of the environment simultaneously and under real-time…