PRISMA: A novel approach for deriving probabilistic surrogate safety measures for risk evaluation

Surrogate Safety Measures (SSMs) are used to express road safety in terms of the safety risk in traffic conflicts. Typically, SSMs rely on assumptions regarding the future evolution of traffic participant trajectories to generate a measure of risk, restricting their applicability to scenarios where these assumptions are valid. In response to...

Safety assessment of automated vehicles using real-world driving scenarios

Automated Vehicles (AVs) have a great potential to change transport fundamentally by making it safer, by reducing travel time, and by increasing mobility and accessibility for all. The level of automation of these vehicles determines the extent to which the driver’s task is accomplished by the AV. With the increasing number of AVs entering the...

Scenario Parameter Generation Method and Scenario Representativeness Metric for Scenario-Based Assessment of Automated Vehicles

The development of assessment methods for the performance of Automated Vehicles (AVs) is essential to enable the deployment of automated driving technologies, due to the complex operational domain of AVs. One candidate is scenario-based assessment, in which test cases are derived from real-world road traffic scenarios obtained from driving...

Risk Quantification for Automated Driving Systems in Real-World Driving Scenarios

The development of safety validation methods is essential for the safe deployment and operation of Automated Driving Systems (ADSs). One of the goals of safety validation is to prospectively evaluate the risk of an ADS dealing with real-world traffic. ISO 26262 and ISO/DIS 21448, the leading standards in automotive safety, provide an approach...

Constrained Sampling from a Kernel Density Estimator to Generate Scenarios for the Assessment of Automated Vehicles

The safety assessment of Automated Vehicles (AVs) is an important aspect of the development cycle of AVs. A scenario-based assessment approach is accepted by many players in the field as part of the complete safety assessment. A scenario is a representation of a situation on the road to which the AV needs to respond appropriately. One way to...

Real-World Scenario Mining for the Assessment of Automated Vehicles

Scenario-based methods for the assessment of Automated Vehicles (AVs) are widely supported by many players in the automotive field. Scenarios captured from real-world data can be used to define the scenarios for the assessment and to estimate their relevance. Therefore, different techniques are proposed for capturing scenarios from real-world...

Safety assessment of automated vehicles: how to determine whether we have collected enough field data?

Objective: The amount of collected field data from naturalistic driving studies is quickly increasing. The data are used for, among others, developing automated driving technologies (such as crash avoidance systems), studying driver interaction with such technologies, and gaining insights into the variety of scenarios in real-world traffic....

Filtering & Identification for Spline based Wavefront Reconstruction in Adaptive Optics

Without any form of compensation, atmospheric turbulence blurs the images obtained by ground-based telescopes. An Adaptive Optics (AO) system compensates for the optical wavefront distortions introduced in a light beam as it propagates through a turbulent medium. The wavefront phase errors are measured with a Wavefront Sensor (WFS) and corrected...