A new collision warning system for lead vehicles in rear-end collisions

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A vehicle's steering is a particular system in that it is exposed to individual subjective reviews based on criteria that are hard to assess quantitatively. Haptic design of such systems is a prime concern that has been at the center of industrial developm ...

The thesis at hand is concerned with robots' navigation in human crowds. Specifically, methods are developed for planning a mobile robot's local motion between pedestrians, and they are evaluated in experiments where a robot interacts with real pedestrians ...

In this thesis, we address the complex issue of collision avoidance in the joint space of robots. Avoiding collisions with both the robot's own body parts and obstacles in the environment is a critical constraint in motion planning and is crucial for ensur ...

This paper studies the routing and charging behaviors of electric vehicles in a competitive ride-hailing market. When the vehicles are idle, they can choose whether to continue cruising to search for passengers, or move a charging station to recharge. The ...

We apply inverse reinforcement learning (IRL) with a novel cost feature to the problem of robot navigation in human crowds. Consistent with prior empirical work on pedestrian behavior, the feature anticipates collisions between agents. We efficiently learn ...

The field of artificial intelligence is set to fuel the future of mobility by driving forward the transition from advanced driver-assist systems to fully autonomous vehicles (AV). Yet the current technology, backed by cutting-edge deep learning techniques, ...

Forecasting pedestrians' future motions is essential for autonomous driving systems to safely navigate in urban areas. However, existing prediction algorithms often overly rely on past observed trajectories and tend to fail around abrupt dynamic changes, s ...

The ability to predict pedestrian behaviour is crucial for road safety, traffic management systems, Advanced Driver Assistance Systems (ADAS), and more broadly autonomous vehicles. We present a vision-based system that simultaneously locates where pedestri ...

Teleoperators rely on both visual and haptic feedback to perform drone teleoperation tasks, such as obstacle avoidance. Haptic feedback becomes essential when visual feedback is compromised, either due to visual occlusions or poor depth perception. However ...

This thesis introduces new operational management policies for two types of on-demand shared mobility systems, the now well-studied one-way carsharing systems and a new innovative semi-autonomous last-mile transportation system. In addition, two associated ...

Flying robots are increasingly used for tasks such as aerial mapping, fast exploration, video footage and monitoring of buildings. Autonomous flight at low altitude in cluttered and unknown environments is an active research topic because it poses challen ...

Human ability to foresee the near future plays a key role in everyone's life to prevent potentially dangerous situations. To be able to make predictions is crucial when people have to interact with the surrounding environment. Modeling such capability can ...

Understanding human motion behavior is critical for autonomous moving platforms (like self-driving cars and social robots) if they are to navigate human-centric environments. This is challenging because human motion is inherently multimodal: given a histor ...

Modern cars can support their drivers by assessing and autonomously performing different driving maneuvers based on information gathered by in-car sensors. We propose that brain–machine interfaces (BMIs) can provide complementary information that can ease ...

Accomplishment of many interactive tasks hinges on the compliance of humans. Humans demonstrate an impressive capability of complying their behavior and more particularly their motions with the environment in everyday life. In humans, compliance emerges fr ...

The degree of intelligence built-in in today's vehicles in constantly on the rise. The vehicles are being equipped with sensors, with the goal to estimate the state of the vehicle and the environment surrounding it. Intelligent algorithms that process the ...

With current overuse of the road transportation system and planned increase in traffic, inno- vative solutions that overcome environmental and financial cost of the current system should be assessed. A promising idea is the use of the third dimension for p ...

The field of Unmanned Aerial Vehicles (UAVs), also known as drones, is rapidly growing, both in terms of size and of number of applications. Civil applications range from mapping, inspection, search and rescue, taking aerial footage, to art show, entertain ...

One-way electric vehicle carsharing systems are receiving increasing attention due to their mobility, environmental, and societal benefits. One of the major issues faced by the operators of these systems is the optimization of the relocation operations of ...

The City Automated Transport System (CATS) was a collaborative FP7 European project that lasted from 2010 to 2014. Its objective was to evaluate the feasibility and acceptability of driverless electric vehicles in European cities. This contribution explain ...

A new collision warning system for lead vehicles in rear-end collisions

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Haptics based collaborative steering control in automated driving environments

Geometric and Learning Methods for Robots to Navigate in Human Crowds with Application to Smart Mobility Devices

Implicit Distance Functions: Learning and Applications in Robotics

Routing and charging game in ride-hailing service with electric vehicles

Inverse Reinforcement Learning of Pedestrian-Robot Coordination

Reshaping Perception for Autonomous Driving with Semantic Keypoints

Pedestrian Stop and Go Forecasting with Hybrid Feature Fusion

Pedestrian intention prediction: A convolutional bottom-up multi-task approach

Arm-wrist haptic sleeve for drone teleoperation

Optimization of operational decisions for on-demand shared mobility systems

Insect-Inspired Visual Perception for Flight Control and Collision Avoidance

Long-term path prediction in urban scenarios using circular distributions

Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks

Decoding Neural Correlates of Cognitive States to Enhance Driving Experience

Compliant control of Uni/ Multi- robotic arms with dynamical systems

Cooperative Perception Algorithms for Networked Intelligent Vehicles

Aerial Human-Comfortable Collision-free Navigation in Dense Environments

Vision-Based Sense and Avoid Algorithms for Unmanned Aerial Vehicles

An integrated optimization-simulation framework for vehicle and personnel relocations of electric carsharing systems with reservations

Pioneering Driverless Electric Vehicles in Europe: The City Automated Transport System (CATS)