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Identifying autonomous vehicles (AVs) (e.g., those with adaptive cruise control) from traffic stream benefits enhancing traffic safety, elevating roadway capacity, and assisting autonomous vehicle management. This study tests the feasibility of ...

Reliable vessel detection can improve safety and security in maritime environment. Recently, application of Deep Learning (DL)-based detectors have become popular in autonomous vehicles. The aim of this paper is to study how much a pretrained DL model on ...

Vehicle-to-Anything (V2X) communication is a research topic in automated driving, with recent activities also focused on cooperative perception (CP). The research field of CP is complex, with many sub-fields using different approaches. In this paper, CP ...

The hybrid electric system has good potential for unmanned tracked vehicles due to its excellent power and economy. Due to unmanned tracked vehicles have no traditional driving devices, and the driving cycle is uncertain, it brings new challenges to ...

Imitation learning on real-world data has the potential to improve the simulation of real-world traffic. However, learning from human demonstrations can be challenging since the recorded behavior is typically noisy and multimodal. Most policies used in ...

Autonomous vehicles have a great potential in the application of both civil and military fields, and have become the focus of research with the rapid development of science and economy. This article proposes a brief review on learning-based decision-...

This paper proposes a hierarchical path tracking control framework divided into the upper controller and the lower controller for double motors independently driven unmanned high-speed tracked vehicle. The upper layer generates rolling speed command of ...

Due to the complex and dynamic character of intersection scenarios, the autonomous driving strategy at intersections has been a difficult problem and a hot point in the research of intelligent transportation systems in recent years. This paper gives a ...

Electric, intelligent, and network are the most important future development directions of automobiles. Intelligent electric vehicles have shown great potentials to improve traffic mobility and reduce emissions, especially at unsignalized intersections. ...

This paper presents a method for accelerated evaluation of an automated driving function using the subset simulation method. The focus of the paper is to investigate how the evaluation is affected by the choice of metric that is used to steer the subset ...

Predicting human intention in vehicles, pedestrians and bicyclists interactions can help autonomous vehicles and human drivers to plan their routes in a safer manner and better optimise the use of road space. Several studies have studied human intention ...

This paper presents a matching mechanism for assigning drivers to routes where the drivers pay a toll for the marginal delay they impose on other drivers. The simple matching mechanism is derived from the deterministic algorithm for online bipartite ...

We present a vehicle self-localization method using point-based deep neural networks. Our approach processes measurements and point features, i.e. landmarks, from a high-definition digital map to infer the vehicle's pose. To learn the best ...

Since the effect of faulty measurements on the integrated localization of autonomous vehicle is catastrophic, the combination of Fault Detection, Isolation and Recovery (FDIR) and localization has become a major trend to improve the accuracy and ...

The expansion of mobile devices and their sensors, like IMU and GNSS, increases the number of applications concerning vehicle dynamics and driver behavior monitoring. However, to make this monitoring possible, it is necessary to know the IMU's ...

Lidar-based or vision-based positioning systems are easily affected by bad weather, and RTK-GNSS inertial navigation systems are prone to reduce positioning accuracy in environments with poor GNSS signals. And using radar for positioning can overcome the ...

Among many components in automated driving, localization is one fundamental task that provides the context for scene understanding and motion planning. This contribution focuses on localization in high-definition (HD) maps, which provide detailed ...

Estimating the pose of a vehicle is an essential function for an autonomous vehicle. Numerous methods exist to tackle this problem, but they are often specialised for one particular type of road, as they only use one type of landmarks. This paper ...

Nowadays it is possible to find WiFi access points at almost any place in our cities. The growth of WiFi access points has made possible to consider, in densely populated areas, WiFi technology as a support to GPS. This paper presents different ...

Localization is a key factor in modern Autonomous Vehicles, and the necessity of working in complex scenarios requires accurate and reliable localization. While some localization techniques are able to provide an accurate solution, they are not able to ...

This paper presents a robust method of processing GNSS data for vehicle localization in degraded signal environments where conventional receivers struggle to accurately position. The method relies on cooperation between receivers that use vector tracking, ...

Although people have made great progress in the field of artificial intelligence such as driverless cars, it is quite challenging for artificial intelligence system to detect the errors caused. Once these undetected errors accumulate to some extent, the ...

Future advanced driver assistance systems and autonomous vehicles rely on accurate localization which can be divided into three classes: a) viewpoint localization with regard to local references (e.g., via vision-based localization), b) absolute ...

Autonomous vehicles face big challenges guaranteeing provable safety during driving. One of the major problems is the uncertainty arising from the perception of the surrounding environment, especially due to occlusions. Recent approaches to tackle these ...

Deep neural networks are found to be vulnerable to adversarial examples. These drawbacks can cause the security problem of machine vision systems. For automated driving, it leads to a more lethal safety-critical issue of the perception systems. In this ...

Continuous direct yaw moment control systems such as torque-vectoring controller are an essential part for vehicle stabilization. This controller has been extensively researched with the central objective of maintaining the vehicle stability by providing ...

This paper introduces a class of model predictive safety performance metrics for driving behavior evaluation. Through formulating the interactions of various traffic agents in the dynamic system context, a class of operational safety performance metrics ...

Current driver assistance systems and autonomous driving stacks are limited to well-defined environment conditions and geo fenced areas. To increase driving safety in adverse weather conditions, broadening the application spectrum of autonomous driving ...

This paper presents a method of intention inference of surrounding vehicles' behavior and longitudinal control for autonomous vehicles. A Recurrent Neural Network (RNN) based on Long Short-Term Memory (LSTM) cells has been used to predict the ...

With the advancement in the surrounding sensing technologies for autonomous driving systems, the immense potential is yet to be explored in vehicle safety. A robust binary decision (Yes/No) about the requirement of any irreversible safety action such as ...