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20212024
most citedScenario-Based Safety Assessment Framework for Automated Vehicles

5 citations · 8 across the 5 of their papers we have counts for

collaborators

5 papers

eess.SY2024

Why Studying Cut-ins? Comparing Cut-ins and Other Lane Changes Based on Naturalistic Driving Data

Yun Lu, Dejiang Zheng, Rong Su +3

Extensive research has been conducted to explore vehicle lane changes, while the study on cut-ins has not received sufficient attention. The existing studies have not addressed the…

cs.RO2023

Simulation Assessment Guidelines towards Independent Safety Assurance of Autonomous Vehicles

Jim Cherian, Martin Slavik, Andrea Piazzoni +3

This Simulation Assessment Guidelines document is a public guidelines document developed by the Centre of Excellence for Testing & Research of AVs - NTU (CETRAN) in collaboration w…

cs.RO2023★ 3 cited

White paper on Selected Environmental Parameters affecting Autonomous Vehicle (AV) Sensors

James Lee Wei Shung, Andrea Piazzoni, Roshan Vijay +2

Autonomous Vehicles (AVs) being developed these days rely on various sensor technologies to sense and perceive the world around them. The sensor outputs are subsequently used by th…

cs.RO2023

White paper on LiDAR performance against selected Automotive Paints

James Lee Wei Shung, Paul Hibbard, Roshan Vijay +2

LiDAR (Light Detection and Ranging) is a useful sensing technique and an important source of data for autonomous vehicles (AVs). In this publication we present the results of a stu…

cs.RO2021★ 5 cited

Scenario-Based Safety Assessment Framework for Automated Vehicles

J. Ploeg, E. de Gelder, M. Slavík +3

Automated vehicles (AVs) are expected to increase traffic safety and traffic efficiency, among others by enabling flexible mobility-on-demand systems. This is particularly importan…