Diane Cleij

• Doctor of Philosophy
• Researcher at Institute for Road Safety Research

While humans are often held accountable for road crashes, human drivers should also be credited for maintaining a traffic system that is safe most of the time. With the anticipated arrival of fully automated vehicles (AVs), understanding how humans navigate traffic safely and efficiently becomes even more important. Automation will not only replace...

Automated vehicles pose a unique challenge to the safety of vulnerable road users. Research on cyclist-automated vehicle interaction has received relatively little attention compared to pedestrian safety. This exploratory study aims to bridge this gap by identifying cyclist-automated vehicle scenarios and providing recommendations for future resear...

This public Deliverable 3.4 describes the on-road evaluations of the vehicle-integrated Mediator system. Three real-life on-road studies were conducted to test the overall performance of the Mediator system and its effects on safety-relevant behaviours, driver reactions and driver opinions.

The objective of this work is to describe guidelines for measuring degraded human performance based on driver state and competences from a real-time driver monitoring perspective. The guidelines integrate state-of-the-art knowledge from the literature with knowhow from the industry and practical results from the Mediator project. The formulated gui...

Connected and automated vehicles have become more common in recent years, increasing the need to assess their societal level impacts. In this paper a methodology is presented to explore and define these impacts as a starting point for quantitative impact assessment. The many interrelations between impacts increases the complexity of obtaining a com...

Automated vehicles pose a unique challenge to the safety of vulnerable road users. Research on cyclist-automated vehicle interaction has received relatively little attention compared to pedestrian safety. This exploratory study aims to bridge this gap by identifying cyclist-automated vehicle scenarios and providing recommendations for future resear...

With increasing implementation of automated driving technology it is expected that different automation modes will be present within the same vehicle and within a single trip. At all times during automated driving the driver needs to have ‘mode awareness’, which is an understanding of the automation mode and the corresponding responsibilities. Yet,...

The ongoing technological development of automated vehicles is bringing their implementation ever closer. Until all vehicles are completely automated there will be a mix of human driven and automated vehicles. To assess impacts of such automated vehicles on traffic safety and flow, techniques involving traffic microsimulations are often used. Here...

In the transition towards higher levels of vehicle automation, one of the key concerns with regards to human factors is to avoid mode confusion, when drivers misinterpret the driving mode and therewith misjudge their own tasks and responsibility. To enhance mode awareness, a clear human centered Human Machine Interface (HMI) is essential. The HMI s...

Connected and automated vehicles have become more common in recent years, increasing the need to assess their societal level impacts. In this paper a methodology is presented to explore and define these impacts as a starting point for quantitative impact assessment. The many interrelations between impacts increases the complexity of obtaining a com...

Connected and automated vehicles have become more common in recent years, increasing the need to assess their societal level impacts. In this paper a methodology is presented to explore and define these impacts as a starting point for quantitative impact assessment. The many interrelations between impacts increases the complexity of obtaining a com...

In this paper the potential of Motion Incongruence Rating (MIR) models for the optimization of Motion Cueing Algorithms (MCAs) is investigated. In a human-in-the-loop simulator experiment, two optimization-based MCAs are compared for a roundabout scenario simulated on a medium-stroke hexapod simulator. The first MCA uses standard cueing error weigh...

Optimization-based motion cueing algorithms based on model predictive control have been recently implemented to reproduce the motion of a car within the limited workspace of a driving simulator. These algorithms require a reference of the future vehicle motion to compute a prediction of the system response. Assumptions regarding the future referenc...

In motion simulation, motion input scaling is often applied to deal with the limited motion envelopes of motion simulators. In this research, the time-varying effects of scaling the lateral specific force up or down during passive curve driving in a car driving simulation are investigated through a simulator experiment. It is concluded that lateral...

Motion cueing algorithms are used in motion simulation to map the inertial vehicle motion onto the limited simulator motion space. This mapping causes mismatches between the unrestricted visual motion and the constrained inertial motion, which results in perceived motion incongruence (PMI). It is still largely unknown what exactly causes visual and...

This paper describes a driving simulation experiment, executed on the Daimler Driving Simulator (DDS), in which a filter-based and an optimization-based motion cueing algorithm (MCA) were compared using a newly developed motion cueing quality rating method. The goal of the comparison was to investigate whether optimization-based MCAs have, compared...

This paper describes a driving simulation experiment, executed on the Daimler Driving Simulator (DDS), in which a filter-based and an optimization-based motion cueing algorithm (MCA) were compared using a newly developed motion cueing quality rating method. The goal of the comparison was to investigate whether optimization-based MCAs have, compared...

Motion cueing algorithms (MCA) are used in motion simulation to map the inertial vehicle motions onto the simulator motion space. To increase fidelity of the motion simulation, these MCAs are tuned to minimize the perceived incoherence between the visual and inertial motion cues. Despite time-invariant MCA dynamics the incoherence is not constant,...

This paper describes a perception-based motion cueing (PBMC) algorithm, which aims to bridge the gap between what is known about human self-motion perception and what is currently used in motion simulation. In PBMC, motion perception knowledge is explicitly incorporated by means of a perception model and a cost function. PBMC has the potential of i...

Haptic shared control is a powerful way of combining the best of humans and intelligent vehicles, keeping humans in the loop while avoiding many automation issues. Literature has shown that haptic shared control can support drivers to increase performance at reduced control effort, but also points out that even then, subtle conflicts occur between...

Negotiating intersections is a complex driving task that is particularly difficult for older drivers. This task requires accurate coordination of multiple driving subtasks, placing high demands on perception, attention and motor control that are known to decline with age. We analyzed intersection negotiation behavior in an instrumented vehicle and...