Human awareness versus Autonomous Vehicles view: comparison of reaction times during emergencies

Aleksander Rydzewski; Paweł Czarnul

doi:10.1109/iv48863.2021.9575602

Human awareness versus Autonomous Vehicles view: comparison of reaction times during emergencies

Abstract

Human safety is one of the most critical factors when a new technology is introduced to the everyday use. It was no different in the case of Autonomous Vehicles (AV), designed to replace generally available Conventional Vehicles (CV) in the future. AV rules, from the start, focus on guaranteeing safety for passengers and other road users, and these assumptions usually work during normal traffic conditions. However, there is still a problem with proper reaction time to sudden, dangerous and unexpected scenarios like a running animal on a rural road during the night. In this paper, we compare human and AV responses to sudden scenarios and accidents. As the AV topic can be analyzed as an ICT system, we review modern sensors, computer architectures and algorithms designed for this type of problems. Beside regular analysis, we also show which algorithms can run simultaneously and if vehicles have proper tools to guarantee safety during regular system delays. As a final result, we present a diagram which depicts Autonomous Vehicle logic and allows to identify bottlenecks. Additionally, the analysis shows how different refresh rates and algorithm execution times can affect the braking distance thus safety of other road users.

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Category:: Conference activity
Type:: publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
Title of issue:: 2021 IEEE Intelligent Vehicles Symposium (IV) strony 732 - 739
Language:: English
Publication year:: 2021
Bibliographic description:: Rydzewski A., Czarnul P.: Human awareness versus Autonomous Vehicles view: comparison of reaction times during emergencies// 2021 IEEE Intelligent Vehicles Symposium (IV)/ : , 2021, s.732-739
DOI:: Digital Object Identifier (open in new tab) 10.1109/iv48863.2021.9575602
Verified by:: Gdańsk University of Technology