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This work examines the role of reinforcement learning in reducing the severity of on-road collisions by controlling velocity and steering in situations in which contact is imminent. We construct a model, given camera images as input, that…

Machine Learning · Computer Science 2019-01-07 Horia Porav , Paul Newman

A robust estimation of road course and traffic lanes is an essential part of environment perception for next generations of Advanced Driver Assistance Systems and development of self-driving vehicles. In this paper, a flexible method for…

Robotics · Computer Science 2017-06-07 Alexey Abramov , Christopher Bayer , Claudio Heller , Claudia Loy

Offroad vehicle movement has to contend with uneven and uncertain terrain which present challenges to path planning and motion control for both manned and unmanned ground vehicles. Knowledge of terrain properties can allow a vehicle to…

Robotics · Computer Science 2022-02-11 Jake Buzhardt , Phanindra Tallapragada

Information about the vehicle sideslip angle is crucial for the successful implementation of advanced stability control systems. In production vehicles, sideslip angle is difficult to measure within the desired accuracy level because of…

Signal Processing · Electrical Eng. & Systems 2019-02-11 Kanwar Bharat Singh

Friction is ubiquitous in daily life, from nanoscale machines to large engineering components. By probing the intricate interplay between system parameters and frictional behavior, scientists seek to unveil the underlying mechanisms that…

Materials Science · Physics 2025-11-26 Yulong Li , Peter Gumbsch , Christian Greiner

The validity of the subjective evaluation of steering feedback in driving simulators is crucial for modern vehicle development. Although there are established objective steering characteristics for the assessment of both stationary and…

Systems and Control · Electrical Eng. & Systems 2025-04-16 Maximilian Böhle , Bernhard Schick , Steffen Müller

The accurate characterization of tire dynamics is critical for advancing control strategies in autonomous road vehicles, as tire behavior significantly influences handling and stability through the generation of forces and moments at the…

Systems and Control · Electrical Eng. & Systems 2026-02-12 Luigi Romano , Ole Morten Aamo , Jan Åslund , Erik Frisk

Understanding the dynamic behavior of tires and their interactions with road plays an important role in designing integrated vehicle control strategies. Accordingly, having access to reliable information about the tire-road interactions…

Signal Processing · Electrical Eng. & Systems 2020-09-29 Bruno Henrique Groenner Barbosa , Nan Xu , Hassan Askari , Amir Khajepour

Granular surfaces subjected to forces due to rolling wheels develop ripples above a critical speed. The resulting pattern, known as "washboard" or "corrugated" road, is common on dry, unpaved roads. We investigated this phenomenon…

Pattern Formation and Solitons · Physics 2017-12-20 Anne-Florence Bitbol , Nicolas Taberlet , Stephen W. Morris , Jim N. McElwaine

Safe mobility for unmanned ground vehicles requires reliable detection of other vehicles, along with precise estimates of their locations and trajectories. Here we describe the algorithms and system we have developed for accurate trajectory…

Robotics · Computer Science 2017-09-26 Daniel Morris , Paul Haley , William Zachar , Steve McLean

Accurate knowledge of the tire-road friction coefficient (TRFC) is essential for vehicle safety, stability, and performance, especially in autonomous racing, where vehicles often operate at the friction limit. However, TRFC cannot be…

This study presents a nonlinear model predictive control (NMPC) formulation for preview-based traction control, which uses the information on the expected tire-road friction coefficient ahead to enhance the wheel slip control performance,…

Systems and Control · Electrical Eng. & Systems 2024-06-05 Gaetano Tavolo , Kai Man So , Davide Tavernini , Pietro Perlo , Aldo Sorniotti

The accurate online estimation of the road-friction coefficient is an essential feature for any advanced brake control system. In this study, a data-driven scheme based on a MLP Neural Net is proposed to estimate the optimum friction…

Systems and Control · Electrical Eng. & Systems 2022-11-21 Francesco Crocetti , G. Costante , M. L. Fravolini , P. Valigi

This research aims to evaluate the performance of the rotors and study the behavior of the human driver in interacting with the rotors. In recent years, rotors have been increasingly used between countries due to their safety, capacity, and…

Machine Learning · Computer Science 2023-09-27 Tasnim M. Dwekat , Ayda A. Almsre , Huthaifa I. Ashqar

The effects of model parameter uncertainty on traffic flow control problems have recently drawn research attention. While the uncertainty in fundamental diagram related parameters has been investigated in the past, few articles have focused…

Optimization and Control · Mathematics 2021-03-09 Hao Liu , Christian Claudel , Randy Machemehl , Kenneth A. Perrine

In this paper, empirical data from the literature are used to develop general power models that capture the impact of a vehicle position, in a platoon of homogeneous vehicles, and the distance gap to its lead (and following) vehicle on its…

Systems and Control · Electrical Eng. & Systems 2021-12-01 Ahmed A. Hussein , Hesham A. Rakha

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…

Robotics · Computer Science 2023-06-08 Agapius Bou Ghosn , Marcus Nolte , Philip Polack , Arnaud de La Fortelle

The design of a mechanical transmission taking into account the transmitted forces is reported in this paper. This transmission is based on Slide-o-Cam, a cam mechanism with multiple rollers mounted on a common translating follower. The…

Robotics · Computer Science 2007-05-23 Damien Chablat , Stéphane Caro , Emilie Bouyer

When humans see a scene, they can roughly imagine the forces applied to objects based on their experience and use them to handle the objects properly. This paper considers transferring this "force-visualization" ability to robots. We…

Robotics · Computer Science 2023-04-13 Ryo Hanai , Yukiyasu Domae , Ixchel G. Ramirez-Alpizar , Bruno Leme , Tetsuya Ogata

We present a method for learning to drive on smooth terrain while simultaneously avoiding collisions in challenging off-road and unstructured outdoor environments using only visual inputs. Our approach applies a hybrid model-based and…

Robotics · Computer Science 2020-04-10 Travis Manderson , Stefan Wapnick , David Meger , Gregory Dudek
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