In this paper, we introduce the preview-follower theory for modeling the trajectory-tracking controller of an automated system using model predictive control (MPC). The primary contribution of this research lies in enhancing tracking accuracy and dri...
Shared control algorithms have emerged as a promising approach for enabling real-time driver automated system cooperation in automated vehicles. These algorithms allow human drivers to actively participate in the driving process while receiving conti...
The “classical” SAE LoA for automated driving can present several drawbacks, and the SAE-L2 and SAE-L3, in particular, can lead to the so-called “irony of automation”, where the driver is substituted by the artificial system, but is still regarded as...
Road vehicles include more and more assistance systems that perform tasks to facilitate driving and make it safer and more efficient. However, the automated vehicles currently on the market do not exceed SAE level 2 and only in some cases reach level...
This paper proposes a new haptic shared control concept between the human driver and the automation for lane keeping in semi-autonomous vehicles. Based on the principle of human-machine interaction during lane keeping, the level of cooperativeness fo...
Driving environment perception for automated vehicles is typically achieved by the use of automotive remote sensors such as radars and cameras. A vehicular wireless communication system can be viewed as a new type of remote sensor that plays a centra...
Cooperation between road users based on V2X communication has the potential to make road traffic safer and more efficient. The exchange of information enables the cooperative orchestration of critical traffic situations, such as truck overtaking mane...
In this paper we describe cooperation and social dilemmas in multiagent systems, with an analogy applied to road traffic. Cooperative human drivers, based on their perception of trust and fairness, find efficient solutions for such dilemmas. In the d...
Currently, a significant gap exists between academic and industrial research in automated driving development. Despite this, there is common sense that cooperative control approaches in automated vehicles will surpass the previously favored takeover...
The Society of Automotive Engineers (SAE) defines six levels of driving automation, ranging from Level 0 to Level 5. Automated driving systems perform entire dynamic driving tasks for Levels 3–5 automated vehicles. Delegating dynamic driving tasks fr...
With the increasing emergence of intelligent vehicles, novel accident patterns have gradually emerged. In human–machine cooperative driving (HMCD) states, despite driving automation systems being capable of controlling lateral and longitudinal...
With the recent deployment of the latest generation of Tesla’s Full Self-Driving (FSD) mode, consumers are using semi-autonomous vehicles in both highway and residential driving for the first time. As a result, drivers are facing complex and un...
Timely and accurate traffic information is crucial for maintaining safety and efficiency on motorway networks. This research examines time delays in traffic information transmission through intelligent transport systems (ITSs) and cooperative intelli...
The Shared Control (SC) cooperation scheme, where the driver and automated driving system control the vehicle together, has been gaining attention through the years as a promising option to improve road safety. As a result, advanced interaction metho...
Intelligent vehicles gradually enter the vehicular fleet with advanced driver-assistance technologies. Their impact on traffic should, therefore, be considered by transportation decision-makers. This paper examines the effect of vehicles with differe...
The increasing integration of autonomous driving technologies into heavy-duty road transport requires a clear understanding of how these systems affect professional drivers’ working time, vehicle utilization, and regulatory compliance. This stu...
In order to study the heterogeneous traffic environment generated by connected automated vehicles (CAVs) and human-driven vehicles (HDVs), the car-following model and basic graph model of the mixed traffic flows of connected automated vehicles and hu...
Today’s urban environments are complex, highly congested traffic scenarios that suffer from multiple unsolved problems such as traffic jams and congestion. These problems pose a significant increase in the risks and probability of traffic accid...
The emerging connected and automated vehicle (CAV) has the potential to improve traffic efficiency and safety. With the cooperation between vehicles and intersection, CAVs can adjust speed and form platoons to pass the intersection faster. However, p...
The literature regarding innovation drivers is usually based on variables taken from some theoretical approach and validated within a methodology. Some authors have included COVID-19 as a driver for innovations. In this paper, we address the pandemic...
While automated-driving technology is advancing rapidly, human-centered research is still in its early stages. Research on negative user responses to automated driving is particularly limited in complex roadway environments such as roundabouts, where...
Road traffic crashes are a major safety problem, with one of the leading factors in crashes being human error. Automated and connected vehicles (CAVs) that are equipped with Advanced Driver Assistance Systems (ADAS) are expected to reduce human error...
This paper presents the results of the Move Over law compliance study. This study was carried out for The Federal Highway Administration in cooperation with ten State Highway agencies that provided the data (video recordings). This paper describes an...
Significant progress has recently been made in transportation automation to alleviate human faults in traffic flow. Recent breakthroughs in artificial intelligence have provided justification for replacing human drivers with digital control systems....
In signalized urban road networks, periodic signal phase switching is a key factor influencing traffic-flow stability and operational efficiency. With the rapid development of Connected and Automated Vehicle (CAV) technologies, exploiting their enhan...
Autonomous driving technology and vehicle-to-vehicle communication technology make the hybrid driving of connected and automated vehicles (CAVs) and regular vehicles (RVs) a long-existing phenomenon in the coming future. Among the existing studies, I...
Truck platooning refers to a group of heavy-duty vehicles travelling in close succession through cooperative driving technologies and inter-vehicle communication. This transport solution is increasingly investigated as a promising strategy to enhance...
Variable speed limit (VSL) control is an effective technology to improve safety near freeway bottlenecks. This study aims to develop a control strategy for mixed traffic flow consisting of both human-driven vehicles (HDVs) and connected and automated...
Cooperative intelligent transport systems (C-ITS) are expected to considerably influence road safety, traffic efficiency and comfort. Nevertheless, their market penetration is still limited, on the one hand due to the high costs of installation and m...
At intersections, road users need to comprehend the intentions of others while also implicitly expressing their own intentions using dynamic information. Identifying patterns of this implicit communication between human drivers and vulnerable road us...
Shorter development times, increased standards for vehicle emissions and a greater number of vehicle variants result in a higher level of complexity in the vehicle development process. Efficient development of powertrain and driver assistance functio...
Connected and automated vehicles (CAVs) present significant potential for improving road safety and mitigating traffic congestion for the future mobility system. However, cooperative driving vehicles are more vulnerable to cyberattacks when communica...
In the typical landscape of road transportation, about 90% of traffic accidents result from human errors. Vehicle automation enhances road safety by reducing driver fatigue and errors and improves overall mobility efficiency. The advancement of auton...
The growth of the automobile industry in recent decades and the overuse of personal vehicles have amplified problems directly related to road safety, such as the increase in traffic congestion and number of accidents, as well as the degradation of th...
Understanding the spatial dynamics of China’s marine economic geography is essential for sustainable coastal development and marine spatial governance. This study examines the spatial distribution patterns and influencing factors of spatial dif...
In an effort to reach accident-free milestones or drastically reduce/eliminate road fatalities rates and traffic congestion and to create disruptive, transformational mobility systems and services, different parties (e.g., automakers, universities, g...
High-precision and lane selective position estimation is of fundamental importance for prospective advanced driver assistance systems (ADAS) and automated driving functions, as well as for traffic information and management processes in intelligent t...
Wetlands in dryland regions are rapidly degrading under the combined effects of climate change and human regulation, yet long-term, seasonally resolved assessments of surface water extent (SWE) and its dynamics remain scarce. Here, we map and analyze...