The automobile revolution and growth in the number of cars produced several issues, and vehicle accidents remain one of the most serious road-related issues. Human mistakes and a failure to brake quickly are the main causes of accidents. There may be...
The assessment of driver assistance system effectiveness in crash scenarios can be conducted through simulations. This approach allows for system improvements and contributes to overall road safety. However, it is important to recognize that simulati...
Traffic accidents continue to increase in Korea as traffic increases, and the resulting loss of life is also on the rise. According to data surveyed by the South Korean National Police Agency, 45,921 pedestrian traffic accidents were reported in 2019...
The rapid growth in the number of electric bicycles (e-bicycles) has greatly improved daily commuting for residents, but it has also increased traffic collisions involving e-bicycles. This study aims to develop an autonomous emergency braking (AEB) s...
Deaths and serious injuries caused by traffic accidents is a concerning public health problem. However, the problem can be mitigated by the Autonomous Emergency Braking (AEB) system, which can avoid the impact. The market penetration of AEB is expone...
To ensure security and stable quality, deeper cybersecurity evaluations are essential for the development of safety features and functionalities in vehicles. Among these, the AEB system is the most relevant. This research presents a comprehensive TAR...
Pedestrian detection by a car is typically performed using camera, LIDAR, or RADAR-based systems. The first two systems, based on the propagation of light, do not work in foggy or poor visibility environments, and the latter are expensive and the pro...
A pre-emptive braking control method is proposed to improve the stability of autonomous vehicles during emergency collision avoidance, aiming to imitate the realistic human driving experience. A linear model predictive control is used to derive the f...
The AEB-P (Autonomous Emergency Braking Pedestrian) system has the functional requirements of avoiding the pedestrian collision and ensuring the pedestrian’s life safety. By studying relevant theoretical systems, such as TTC (time to collision)...
Nowadays, due to the advances and the increasing implementation of the autonomous braking systems in vehicles, the non-collision accident is expected to become more common than a crash when a sudden stop happens. The most common injury in this kind o...
Steering has more potential than braking to prevent rear-end collisions at higher relative velocities. A path tracking controller based on multi-input multi-output (MIMO) model predictive control (MPC) is proposed to enhance the handling performance...
The automated guided vehicle (AGV) is widely used in industrial environments for goods transportation. However, issues such as mechanical wear, reduced battery life, navigation error accumulation, and decreased operational efficiency caused by freque...
With the continuous development of assisted driving technology, the autonomous emergency braking (AEB) system has emerged as a critical innovation in preventing collisions and improving vehicular safety. In this paper, to test the performance of the...
Due to the particularity of the structure, the dynamic properties of multiunit articulated rubber-wheel autonomous rail rapid transit system are very complex, which increases the difficulty of studying its braking stability. In this paper, a dynamic...
Currently, deep learning and IoT collaboration is heavily invading automotive applications especially in autonomous driving throughout successful assistance functionalities. Crash avoidance, path planning, and automatic emergency braking are essentia...
Traffic regulations provide a solid foundation for the safety of all road users; however, the ambiguous provisions and unclear safety thresholds within these regulations pose significant challenges to compliance, particularly concerning the safe oper...
With the increasing consumer focus on automotive safety, Autonomous Emergency Braking (AEB) systems, recognized as effective active safety technologies for collision avoidance and the mitigation of collision-related injuries, are gaining wider applic...
The study of vulnerable road users (VRUs) behavior is key to designing and optimizing driving assistance systems, such as the autonomous emergency braking (AEB) system. These kinds of devices could help lower the VRU accident rate, which is of partic...
To address the growing need for field calibration of the optical properties of pedestrian targets used in autonomous emergency braking (AEB) tests, a novel three-dimensional multi-faceted standard body (TDMFSB) was developed. A camera-based analytica...
The automatic emergency braking (AEB) system plays a crucial role in reducing rear-end collisions and is mandatory on certain heavy-duty vehicles, with future regulations extending to passenger cars. However, most current AEB systems are designed bas...
Conventional autonomous emergency braking (AEB) systems derive the relative distance of a curve using a curvature calculated through an in-vehicle sensor. However, as the AEB system cannot reflect geometric factors of a curve with variable curvature,...
In autonomous driving, using a variety of sensors to recognize preceding vehicles at middle and long distances is helpful for improving driving performance and developing various functions. However, if only LiDAR or cameras are used in the recognitio...
Rare and safety-critical traffic situations remain challenging for autonomous driving (AD) because they are underrepresented in common training data and may include objects outside standard detector classes. This paper presents a real-time RGB-LiDAR...
Robust monocular distance estimation under varying illumination conditions is critical for autonomous driving safety. While state-of-the-art monocular 3D detection models achieve high accuracy in daylight conditions, they rely on computationally heav...
The role of powered two-wheeler (PTW) transport from the perspective of a more sustainable mobility system is undermined by the associated high injury risk due to crashes. Motorcycle-based active safety systems promise to avoid or mitigate many of th...
This paper proposes a combined system (OPREVU-AES) that integrates optimized AEB and Automatic Emergency Steering (AES) to generate evasive maneuvers, and it provides an assessment of its effectiveness when compared to a commercial AEB system. The op...
This paper proposes a novel control approach for vehicle collision avoidance of urban vehicles. For safe driving in urban environments, this paper presents both one-dimensional and two-dimensional solutions, which can be applied to the collision avoi...
Few prior works study self-driving cars by deep learning with IoT collaboration. SDC-Net, which is an end-to-end multitask self-driving car camera cocoon IoT-based system, is one of the research areas that tackles this direction. However, by design,...
Ego-vehicle state prediction represents a complex and challenging problem for self-driving and autonomous vehicles. Sensorial information and on-board cameras are used in perception-based solutions in order to understand the state of the vehicle and...
Nowadays, autonomous vehicles are increasing, and the driving scenario that includes both autonomous and human-driven vehicles is a fact. Knowing the driving styles of drivers in the process of automating vehicles is interest in order to make driving...
The objective of this study was to analyze the effects of variables such as pre-crash emergency braking and reclined posture on human injuries in autonomous vehicle collisions using an active human model and through crash analysis. To achieve this, t...
Autonomous vehicles are increasingly being adopted, with manufacturers competing to enhance automation capabilities. While full automation eliminates human input, lower levels still require driver intervention under specific conditions. This study pr...
Motor vehicle crashes remain a leading cause of life and property loss to society. Autonomous vehicles can mitigate the losses by making appropriate emergency decision, and the crash injury severity prediction model is the basis for autonomous vehicl...
With the development of automobile electrification and intelligence, new requirements have been put forward for automotive braking technologies. Under this background, the One-box EHB (Electro-Hydraulic Braking system) brake-by-wire technology has em...
The high redundant brake-by-wire system reveals vehicular safety handling ability and rarely emerges in the automotive area at the present time. This paper presents a novel brake-by-wire system, DREHB (Double Redundant Electro-Hydraulic Brake), with...
Autonomous vehicles (AVs) are supposed to identify obstacles automatically and form appropriate emergency strategies constantly to ensure driving safety and improve traffic efficiency. However, not all collisions will be avoidable, and AVs are requir...
Truck skidding crashes on horizontal curves pose a significant road safety concern, with improper braking being the primary cause. A data- and model-integrated driven method is proposed to investigate the mechanism and recommend the maximum safe brak...
In response to the fact that autonomous vehicles cannot avoid obstacles by emergency braking alone, this paper proposes an active collision avoidance method for autonomous vehicles based on model predictive control (MPC). The method includes trajecto...
Predicting potential collisions with leading vehicles is a fundamental capability of autonomous and assisted driving systems. In particular, automatic emergency braking (AEB) demands reaction times on the order of microseconds. A key limitation of ex...
The need for autonomous vehicles has started rising rapidly. Many autonomous technologies, such as Cruise Control, the self-parking system, and the emergency braking system, are implemented in contemporary cars. These systems do not make the car full...
There are a large number of unstructured scenes and special targets in the construction machinery application scene, which brings greater interference to the environment sensing system for Construction Machinery Autonomous Operation Application. The...
Accurate braking-distance prediction for heavy-duty multi-axle trucks remains challenging due to the large gross vehicle weight, tandem-axle interactions, and strong transient load transfer during emergency braking. Recent studies on tire–road...
As electric vehicles (EVs) continue to advance toward widespread adoption, innovations in power electronics are playing a pivotal role in improving efficiency, performance, and sustainability. This review presents recent progress in bidirectional con...
In recent years, research concerning autonomous driving has gained momentum to enhance road safety and traffic efficiency. Relevant concepts are being applied to the fields of perception, planning, and control of automated vehicles to leverage the ad...
The collision avoidance capability of autonomous vehicles in extreme traffic conditions remains a focal point of research. This paper introduces an Adaptive Cruise Control (ACC) strategy based on Model Predictive Control (MPC) and Responsibility-Sens...
As smart cities become a global topic, interest in smart mobility, the core of smart cities, is also growing. The technology that comes closest to general users is “autonomous driving”. In particular, the successful market entry and establishment of...
In this paper, we propose a method for the generation of simulated test scenarios for autonomous driving. Based on the requirements of standard regulatory test scenarios, we can generate virtually simulated scenarios and functional scenario libraries...
The current prioritisation of road safety enhancement in the automotive sector is leading toward the near future implementation of Advanced Driver Assistance Systems (ADASs), aiming at the simultaneous intervention of braking and steering for impact...
The rapid deployment of autonomous haulage systems (AHSs) in open-pit mining has significantly altered haul road geometric design requirements, as autonomous trucks operate under strict kinematic constraints related to turning radius, gradient, and b...
To maintain a safe distance between the autonomous vehicle and the leader, ensure that the vehicle runs at its expected speed as far as possible, and achieve various control requirements such as speed, distance and collision avoidance, a model-free p...
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