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In this paper, we present a novel probabilistic safe control framework for human-robot interaction that combines control barrier functions (CBFs) with conformal risk control to provide formal safety guarantees while considering complex…

机器人学 · 计算机科学 2026-03-12 Jake Gonzales , Kazuki Mizuta , Karen Leung , Lillian J. Ratliff

Technological advancements focus on developing comfortable and acceptable driving characteristics in autonomous vehicles. Present driving functions predominantly possess predefined parameters, and there is no universally accepted driving…

系统与控制 · 电气工程与系统科学 2024-10-28 Johann Haselberger , Maximilian Böhle , Bernhard Schick , Steffen Müller

The prediction of road users' future motion is a critical task in supporting advanced driver-assistance systems (ADAS). It plays an even more crucial role for autonomous driving (AD) in enabling the planning and execution of safe driving…

计算机视觉与模式识别 · 计算机科学 2023-08-16 Maximilian Schäfer , Kun Zhao , Anton Kummert

Smart roads have become an essential component of intelligent transportation systems (ITS). The roadside perception technology, a critical aspect of smart roads, utilizes various sensors, roadside units (RSUs), and edge computing devices to…

信号处理 · 电气工程与系统科学 2023-12-18 Rui Chen , Lu Gao , Yutian Liu , Yong Liang Guan , Yan Zhang

For autonomous driving or advanced driving assistance, it is key to monitor the vehicle dynamics behavior. Accurate models of this behavior include acceleration, but also the side-slip angle, that eventually results from the complex…

机器人学 · 计算机科学 2023-06-08 Agapius Bou Ghosn , Marcus Nolte , Philip Polack , Arnaud de La Fortelle

We present a real-time safety filter for motion planning, including those that are learning-based, using Control Barrier Functions (CBFs) to provide formal guarantees for collision avoidance with road boundaries. A key feature of our…

机器人学 · 计算机科学 2026-03-25 Jianye Xu , Chang Che , Bassam Alrifaee

Trajectory planning for autonomous driving is challenging because the unknown future motion of traffic participants must be accounted for, yielding large uncertainty. Stochastic Model Predictive Control (SMPC)-based planners provide…

系统与控制 · 电气工程与系统科学 2024-07-31 Tommaso Benciolini , Michael Fink , Nehir Güzelkaya , Dirk Wollherr , Marion Leibold

Connected automated vehicles have shown great potential to improve the efficiency of transportation systems in terms of passenger comfort, fuel economy, stability of driving behavior and mitigation of traffic congestions. Yet, to deploy…

系统与控制 · 电气工程与系统科学 2023-09-04 Tamas G. Molnar , Gabor Orosz , Aaron D. Ames

This paper describes the comprehensive safety framework that underpinned the development, release process, and regulatory approval of BMW's first SAE Level 3 Automated Driving System. The framework combines established qualitative and…

机器人学 · 计算机科学 2025-03-27 Moritz Werling , Rainer Faller , Wolfgang Betz , Daniel Straub

With the fast development of driving automation technologies, user psychological acceptance of driving automation has become one of the major obstacles to the adoption of the driving automation technology. The most basic function of a…

机器人学 · 计算机科学 2023-07-04 Weishun Deng , Fan Yu , Zhe Wang , Dengbo He

Extensive evaluation of perception systems is crucial for ensuring the safety of intelligent vehicles in complex driving scenarios. Conventional performance metrics such as precision, recall and the F1-score assess the overall detection…

机器人学 · 计算机科学 2025-12-18 Jörg Gamerdinger , Sven Teufel , Stephan Amann , Lukas Marc Listl , Oliver Bringmann

How many scenarios are sufficient to validate the safe Operational Design Domain (ODD) of an Automated Driving System (ADS) equipped vehicle? Is a more significant number of sampled scenarios guaranteeing a more accurate safety assessment…

机器人学 · 计算机科学 2021-11-16 Bowen Weng , Linda Capito , Umit Ozguner , Keith Redmill

The development of Automated Driving Systems (ADS) has the potential to revolutionise the transportation industry, but it also presents significant safety challenges. One of the key challenges is ensuring that the ADS is safe in the event…

软件工程 · 计算机科学 2025-03-26 Milin Patel , Rolf Jung

Safety validation of autonomous driving systems requires high-risk scenario coverage, clear collision semantics, executable trajectories, and attributable multi-vehicle interactions. Existing safety-critical scenario generation methods…

机器人学 · 计算机科学 2026-05-20 Cheng Wang , Chen Xiong , Ziwen Wang , Yuchen Zhou , Qiang Liu

Ensuring safety and driving consistency is a significant challenge for autonomous vehicles operating in partially observed environments. This work introduces a consistent parallel trajectory optimization (CPTO) approach to enable safe and…

机器人学 · 计算机科学 2026-05-12 Lei Zheng , Rui Yang , Minzhe Zheng , Michael Yu Wang , Jun Ma

To build a smarter and safer city, a secure, efficient, and sustainable transportation system is a key requirement. The autonomous driving system (ADS) plays an important role in the development of smart transportation and is considered one…

计算机视觉与模式识别 · 计算机科学 2024-09-25 Abu Shad Ahammed , Md Shahi Amran Hossain , Roman Obermaisser

In this work, we propose a compositional data-driven approach for the formal estimation of collision risks for autonomous vehicles (AVs) while acting in a stochastic multi-agent framework. The proposed approach is based on the construction…

系统与控制 · 电气工程与系统科学 2022-07-21 Abolfazl Lavaei , Luigi Di Lillo , Andrea Censi , Emilio Frazzoli

Connected automated vehicles (CAVs) have brought new opportunities to improve traffic throughput and reduce energy consumption. However, the uncertain lane-change behaviors (LCBs) of surrounding vehicles (SVs) as an uncontrollable factor…

系统与控制 · 电气工程与系统科学 2022-09-05 Bohui Wang , Rong Su

Cooperative decision-making of Connected Autonomous Vehicles (CAVs) presents a longstanding challenge due to its inherent nonlinearity, non-convexity, and discrete characteristics, compounded by the diverse road topologies encountered in…

机器人学 · 计算机科学 2024-01-11 Zhenmin Huang , Shaojie Shen , Jun Ma

According to data from the United Nations, more than 3000 people have died each day in the world due to road traffic collision. Considering recent researches, the human error may be considered as the main responsible for these fatalities.…

计算机与社会 · 计算机科学 2018-02-13 Andrés E. Gómez , Tiago C. dos Santos , Carlos M. Massera , Arthur de M. Neto , Denis F. Wolf
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