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In autonomous racing, vehicles operate close to the limits of handling and a sensor failure can have critical consequences. To limit the impact of such failures, this paper presents the redundant perception and state estimation approaches…

We address automotive odometry for low-speed driving and parking, where centimeter-level accuracy is required due to tight spaces and nearby obstacles. Traditional methods using inertial-measurement units and wheel encoders require…

机器人学 · 计算机科学 2025-11-05 Luis Diener , Jens Kalkkuhl , Markus Enzweiler

The escalation in urban private car ownership has worsened the urban parking predicament, necessitating effective parking availability prediction for urban planning and management. However, the existing prediction methods suffer from low…

机器学习 · 计算机科学 2024-11-05 Yin Huang , Yongqi Dong , Youhua Tang , Li Li

In this paper, we present a novel formulation to model the effects of a locked differential on the lateral dynamics of an autonomous open-wheel racecar. The model is used in a Model Predictive Controller in which we included a micro-steps…

To improve safety and energy efficiency, autonomous vehicles are expected to drive smoothly in most situations, while maintaining their velocity below a predetermined speed limit. However, some scenarios such as low road adherence or…

系统与控制 · 计算机科学 2017-04-05 Florent Altché , Philip Polack , Arnaud de la Fortelle

We consider the problem of estimating the parameters of a vehicle dynamics model for predictive control in driving applications. Instead of solely using the instantaneous parameters estimated from the vehicle signals, we combine this with…

系统与控制 · 电气工程与系统科学 2025-11-17 Marcus Greiff , Ray Zhang , Takeru Shirasawa , John Subosits

Autonomous vehicles require reliable hazard detection. However, primary sensor systems may miss near-field obstacles, resulting in safety risks. Although a dedicated fast-reacting near-field monitoring system can mitigate this, it typically…

系统与控制 · 电气工程与系统科学 2025-07-22 Junnan Pan , Prodromos Sotiriadis , Vladislav Nenchev , Ferdinand Englberger

Accurate estimation of the vehicle's sideslip angle and tire forces is essential for enhancing safety and handling performances in unknown driving scenarios. To this end, the present paper proposes an innovative observer that combines a…

系统与控制 · 电气工程与系统科学 2026-03-24 Luigi Romano , Ole Morten Aamo , Jan Åslund , Erik Frisk

There are so many vehicles in the world and the number of vehicles is increasing rapidly. To alleviate the parking problems caused by that, the smart parking system has been developed. The parking planning is one of the most important parts…

数据结构与算法 · 计算机科学 2017-08-29 Xuejian Zhao , Kui Zhao , Feng Ha

Current state-of-art traffic microsimulation tools cannot accurately estimate safety, efficiency, and mobility benefits of automated driving systems and vehicle connectivity because of not considering physical and powertrain characteristics…

系统与控制 · 电气工程与系统科学 2020-03-19 Shirin Noei , Xilei Zhao , Carl D. Crane

End-to-end learning has shown great potential in autonomous parking, yet the lack of publicly available datasets limits reproducibility and benchmarking. While prior work introduced a visual-based parking model and a pipeline for data…

机器人学 · 计算机科学 2025-08-04 Kejia Gao , Liguo Zhou , Mingjun Liu , Alois Knoll

In congested urban areas, it remains a pressing challenge to reduce unnecessary vehicle circling for parking while at the same time maximize parking space utilization. In observance of new information technologies that have become readily…

计算机科学与博弈论 · 计算机科学 2015-01-06 Daniel Mackowski , Yun Bai , Yanfeng Ouyang

In this paper, we propose a new macro-micro approach to modeling parking. We first develop a microscopic parking simulation model considering both on- and off-street parking with limited capacity. In the microscopic model, a parking search…

最优化与控制 · 数学 2021-04-29 Ziyuan Gu , Farshid Safarighouzhdib , Meead Saberi , Taha H. Rashidi

Evaluating the effectiveness and benefits of driver assistance systems is crucial for improving the system performance. In this paper, we propose a novel framework for testing and evaluating lane departure correction systems at a low cost…

系统与控制 · 计算机科学 2017-02-21 Wenshuo Wang , Ding Zhao

In this paper, we develop a method to detect vacant parking spaces in an environment with unclear segments and contours with the help of MATLAB image processing capabilities. Due to the anomalies present in the parking spaces, such as…

图像与视频处理 · 电气工程与系统科学 2018-03-14 Chetan Sai Tutika , Charan Vallapaneni , Karthik R , Bharath KP , N Ruban Rajesh Kumar Muthu

Recent transportation research highlights the potential of autonomous vehicles (AV) to improve traffic flow mobility as they are able to maintain smaller car-following distances. However, as a unique class of ground robots, AVs are…

机器人学 · 计算机科学 2025-07-09 Hangyu Li , Xiaotong Sun , Chenglin Zhuang , Xiaopeng Li

Pedestrians and drivers interact closely in a wide range of environments. Autonomous vehicles (AVs) correspondingly face the need to predict pedestrians' future trajectories in these same environments. Traditional model-based prediction…

机器人学 · 计算机科学 2020-06-02 Cyrus Anderson , Ram Vasudevan , Matthew Johnson-Roberson

In order for autonomous vehicles to become a part of the Intelligent Transportation Ecosystem, they are required to guarantee a particular level of safety. For that to happen a safe vehicle control algorithms need to be developed, which…

机器人学 · 计算机科学 2020-03-03 Vladislav Kibalov , Oleg Shipitko

We present an approach towards robust lane tracking for assisted and autonomous driving, particularly under poor visibility. Autonomous detection of lane markers improves road safety, and purely visual tracking is desirable for widespread…

机器人学 · 计算机科学 2017-01-31 Junaed Sattar , Jiawei Mo

In addition to environmental perception sensors such as cameras, radars, etc. in the automatic driving system, the external environment of the vehicle is perceived, in fact, there is also a perception sensor that has been silently dedicated…

机器人学 · 计算机科学 2024-04-09 Han Lei , Baoming Wang , Zuwei Shui , Peiyuan Yang , Penghao Liang