(Mis-)use of standard Autopilot and Full Self-Driving (FSD) Beta: Results from interviews with users of Tesla's FSD Beta

Tesla's Full Self-Driving Beta (FSD) program introduces technology that extends the operational design domain of standard Autopilot from highways to urban roads. This research conducted 103 in-depth semi-structured interviews with users of Tesla's FSD Beta and standard Autopilot to evaluate the impact on user behavior and perception. It was...

Large Car-following Data Based on Lyft level-5 Open Dataset: Following Autonomous Vehicles vs. Human-driven Vehicles

Car-Following (CF), as a fundamental driving behaviour, has significant influences on the safety and efficiency of traffic flow. Investigating how human drivers react differently when following autonomous vs. human-driven vehicles (HV) is thus critical for mixed traffic flow. Research in this field can be expedited with trajectory datasets...

Herd immunity for traffic safety in mixed automated traffic: what if cars could not crash!?

Traffic safety is arguably the most important traffic metric from a human perspective. Still, many millions of people are killed on roads every year. In this paper, the concept of Herd Immunity for Traffic Safety (HITS) is presented for the first time. This concept focuses on identifying and describing the increased level of safety that is...

How to ensure control of cooperative vehicle and truck platoons using meaningful human control

Vehicle cooperation, not vehicle automation, will yield the greatest benefits on road traffic. However, satisfactory human control over platoons of cooperative vehicles still has a large number of uncertainties and issues to be addressed. This paper aims to address these broader issues of control over a cooperative vehicle platoon by...

A generic multi-level framework for microscopic traffic simulation with automated vehicles in mixed traffic

With an increasing number of automated vehicles (AV) appearing on roads and interacting with conventional traffic, there is a need for improved simulation approaches to replicate and forecast the resulting effects. Interactions between AVs and their drivers, and interaction with other human drivers involve new types of complex behavioural...

A generic multi-scale framework for microscopic traffic simulation part II: Anticipation Reliance as compensation mechanism for potential task overload

The inclusion of human factors (HF) in mathematical models is proving crucial to allow complex driving behaviour and interactions to be explicitly considered to capture driving phenomena. An important area where such integration is required is for the role of anticipation by drivers to compensate for critical traffic situations. In this paper...

A Conceptual Control System Description of Cooperative and Automated Driving in Mixed Urban Traffic With Meaningful Human Control for Design and Evaluation

The introduction of automated vehicles means that some or all operational control over these vehicles is diverted away from a human driver to a technological system. The concept of Meaningful Human Control (MHC) was derived to address control issues over automated systems, allowing a system to explicitly consider human intentions and reasons....

Gaps in the control of automated vehicles on roads

Increased on-road testing and market availability of partially automated vehicles (AV) offers researchers and developers the opportunity to evaluate the AV’s performance. The occurrence of new types of accidents involving AV’s has sparked questions in regard to who is actually in control over and responsible for AV control. In this contribution,...

Human behaviour with automated driving systems: A quantitative framework for meaningful human control

Automated driving systems (ADS) with partial automation are currently available for the consumer. They are potentially beneficial to traffic flow, fuel consumption, and safety, but human behaviour whilst driving with ADS is poorly understood. Human behaviour is currently expected to lead to dangerous circumstances as ADS could place human...

Meaningful Human Control over Automated Driving Systems

Human Factors issues with automated driving systems (ADS) are becoming more apparent with the increasing prevalence of automated vehicles on the public roads. As automated driving demands increased performance of supervisory skills of the driver, rather than vehicle handling skills, a mismatch occurs between the demand and supply of the drivers’...

Meaningful Human Control over Automated Driving Systems

Exploring the effects of perception errors and anticipation strategies on traffic accidents - A simulation study

It is remarkable that drivers (on average) can safely navigate through dense traffic at high speeds—conditions in which the time headways between vehicles are in the same order of magnitude as human reaction times. One explanation for this is the ability of drivers to anticipate on the traffic conditions in their surroundings. In this paper,...