Related papers: A Probabilistic Approach to Driver Assistance for …

Machine learning (ML) classifiers serve as essential tools facilitating classification and prediction across various domains. The performance of these algorithms should be known to ensure their reliable application. In certain fields,…

A key challenge in off-road navigation is that even visually similar terrains or ones from the same semantic class may have substantially different traction properties. Existing work typically assumes no wheel slip or uses the expected…

In this paper, we investigate the coordination of vehicle maneuvers in mixed-traffic corridors where connected and automated vehicles, human-driven vehicles, and buses interact under dedicated bus lane operations. We develop a segment-based…

Trajectory prediction is one of the key components of the autonomous driving software stack. Accurate prediction for the future movement of surrounding traffic participants is an important prerequisite for ensuring the driving efficiency…

In recent years, road safety has attracted significant attention from researchers and practitioners in the intelligent transport systems domain. As one of the most common and vulnerable groups of road users, pedestrians cause great concerns…

Lane-change maneuvers are commonly executed by drivers to follow a certain routing plan, overtake a slower vehicle, adapt to a merging lane ahead, etc. However, improper lane change behaviors can be a major cause of traffic flow disruptions…

We propose a Model Predictive Control (MPC) for collision avoidance between an autonomous agent and dynamic obstacles with uncertain predictions. The collision avoidance constraints are imposed by enforcing positive distance between convex…

In the upstream of the exit ramp of the expressway, the speed limit difference leads to a significant deceleration of the vehicle in the area adjacent to the off-ramp. The friction coefficient of the road surface decreases under rainy…

Predicting on-road abnormalities such as road accidents or traffic violations is a challenging task in traffic surveillance. If such predictions can be done in advance, many damages can be controlled. Here in our wok, we tried to formulate…

To model and forecast flight delays accurately, it is crucial to harness various vehicle trajectory and contextual sensor data on airport tarmac areas. These heterogeneous sensor data, if modelled correctly, can be used to generate a…

This work presents a novel method for predicting vehicle trajectories in highway scenarios using efficient bird's eye view representations and convolutional neural networks. Vehicle positions, motion histories, road configuration, and…

To achieve complete autonomous vehicles, it is crucial for autonomous vehicles to communicate and interact with their surrounding vehicles. Especially, since the lane change scenarios do not have traffic signals and traffic rules, the…

In this paper, a driver's intention prediction near a road intersection is proposed. Our approach uses a deep bidirectional Long Short-Term Memory (LSTM) with an attention mechanism model based on a hybrid-state system (HSS) framework. As…

Road traffic crashes have been the leading cause of death among young people. Most of these accidents occur when the driver becomes distracted and a loss-of-control situation occurs. Steer-by-Wire systems were recently proposed as an…

To navigate safely in urban environments, an autonomous vehicle (ego vehicle) must understand and anticipate its surroundings, in particular the behavior and intents of other road users (neighbors). Most of the times, multiple decision…

Based on requirements of modern vehicle, in- vehicle Controller Area Network (CAN) architecture has been implemented. In order to reduce point to point wiring harness in vehicle automation, CAN is suggested as a means for data communication…

This paper discusses the need for individualizing safety systems and proposes an approach including the Real-Time estimation of the distribution of brake response times for an individual driver. While maintaining high level of safety, the…

In contemporary autonomous driving testing, virtual simulation has become an important approach due to its efficiency and cost effectiveness. However, existing methods usually rely on reinforcement learning to generate risky scenarios,…

Developing autonomous vehicles (AVs) helps improve the road safety and traffic efficiency of intelligent transportation systems (ITS). Accurately predicting the trajectories of traffic participants is essential to the decision-making and…

This paper studies the design of a Model Predictive Controller (MPC) for integrated lateral stability, traction/braking control, and rollover prevention of electric vehicles intended for very high speed (VHS) racing applications. We first…