相关论文: MIT Advanced Vehicle Technology Study: Large-Scale…

The investigation of factors contributing at making humans trust Autonomous Vehicles (AVs) will play a fundamental role in the adoption of such technology. The user's ability to form a mental model of the AV, which is crucial to establish…

Perception-driven approach and end-to-end system are two major vision-based frameworks for self-driving cars. However, it is difficult to introduce attention and historical information of autonomous driving process, which are the essential…

Automated driving systems (ADSs) promise a safe, comfortable and efficient driving experience. However, fatalities involving vehicles equipped with ADSs are on the rise. The full potential of ADSs cannot be realized unless the robustness of…

Deep neural perception and control networks are likely to be a key component of self-driving vehicles. These models need to be explainable - they should provide easy-to-interpret rationales for their behavior - so that passengers, insurance…

Autonomous driving algorithms rely heavily on learning-based models, which require large datasets for training. However, there is often a large amount of redundant information in these datasets, while collecting and processing these…

In future mixed traffic Highly Automated Vehicles (HAV) will have to resolve interactions with human operated traffic. A particular problem for HAVs is detection of human states influencing safety critical decisions and driving behavior of…

This paper presents a comprehensive review of trajectory data of Advanced Driver Assistance System equipped-vehicle, with the aim of precisely model of Autonomous Vehicles (AVs) behavior. This study emphasizes the importance of trajectory…

Autonomous driving, particularly navigating complex and unanticipated scenarios, demands sophisticated reasoning and planning capabilities. While Multi-modal Large Language Models (MLLMs) offer a promising avenue for this, their use has…

Real-world driving involves intricate interactions among vehicles navigating through dense traffic scenarios. Recent research focuses on enhancing the interaction awareness of autonomous vehicles to leverage these interactions in…

The future of transportation is being shaped by technology, and one revolutionary step in improving road safety is the incorporation of robotic systems into driver monitoring infrastructure. This literature review explores the current…

This study investigates the impact of initial contact of drivers with an SAE Level 3 Automated Driving System (ADS) under real traffic conditions, focusing on the Mercedes-Benz Drive Pilot in the EQS. It examines Acceptance, Trust,…

The most common type of accident on the road is a rear-end crash. These crashes have a significant negative impact on traffic flow and are frequently fatal. To gain a more practical understanding of these scenarios, it is necessary to…

Manual traffic surveillance can be a daunting task as Traffic Management Centers operate a myriad of cameras installed over a network. Injecting some level of automation could help lighten the workload of human operators performing manual…

Qatar expects more than a million visitors during the 2022 World Cup, which will pose significant challenges. The high number of people will likely cause a rise in road traffic congestion, vehicle crashes, injuries and deaths. To tackle…

A major challenge for autonomous vehicles is interacting with other traffic participants safely and smoothly. A promising approach to handle such traffic interactions is equipping autonomous vehicles with interaction-aware controllers…

Connected and automated vehicles (CAVs) are supposed to share the road with human-driven vehicles (HDVs) in a foreseeable future. Therefore, considering the mixed traffic environment is more pragmatic, as the well-planned operation of CAVs…

The autonomous car technology promises to replace human drivers with safer driving systems. But although autonomous cars can become safer than human drivers this is a long process that is going to be refined over time. Before these vehicles…

In recent decades, society has witnessed significant advancements in emerging mobility systems. These systems refer to transportation solutions that incorporate digital technologies, automation, connectivity, and sustainability to create…

Current robotic agents, such as autonomous vehicles (AVs) and drones, need to deal with uncertain real-world environments with appropriate situational awareness (SA), risk awareness, coordination, and decision-making. The SymAware project…

In the simulation-based testing and evaluation of autonomous vehicles (AVs), how background vehicles (BVs) drive directly influences the AV's driving behavior and further impacts the testing result. Existing simulation platforms use either…