Song, Rui ORCID: 0000-0002-8695-1522, Wetherall, Jon, Maskell, Simon
ORCID: 0000-0003-1917-2913 and Ralph, Jason F
ORCID: 0000-0002-4946-9948
(2020)
Weather Effects on Obstacle Detection for Autonomous Car.
In: 6th International Conference on Vehicle Technology and Intelligent Transport Systems, 2020-5-2 - 2020-5-4, Prague, Czeh Republic.
Text
Weather Effects on Obstacle Detection for Autonomous Car.pdf - Author Accepted Manuscript Download (1MB) | Preview |
Abstract
Adverse weather conditions have become a critical issue when developing autonomous vehicles and driver assistance systems. Training and testing autonomous vehicles in a simulation environment before deploying them into the market have many benefits due to lower costs and fewer risks. However, there are only a few works about weather influences on sensors in the simulated environment. A more systematic study of weather effects on the sensors used on autonomous cars is required. This paper presents a multi-sensor simulation environment under different weather conditions and examines the influence on environmental perception and obstacle detection for autonomous cars. The simulation system is being developed as part of a collaborative project entitled: Artificial Learning Environment for Autonomous Driving (ALEAD). The system incorporates a suite of sensors typically used for autonomous cars. Each sensor model has been developed to be as realistic as possible - incorporating physical defects and other artefacts found in real sensors. The influence of weather on these sensors has been simulated based on experimental data. The multi-sensor system has been tested under different simulated weather conditions and analysed to determine the effect on detection of a dynamic obstacle and a road lane in a 3D environment.
Item Type: | Conference or Workshop Item (Unspecified) |
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Uncontrolled Keywords: | Autonomous Vehicle, Multiple Sensors, Weather Simulation, Virtual Environment, Object Detection |
Depositing User: | Symplectic Admin |
Date Deposited: | 17 Mar 2020 11:14 |
Last Modified: | 18 Jan 2023 23:57 |
DOI: | 10.5220/0009354503310341 |
Related URLs: | |
URI: | https://livrepository.liverpool.ac.uk/id/eprint/3079344 |