Safety assessment of autonomous vehicles using simulations

Since the past few decades, researchers from both automotive and technology industries have focussed their attention on developing vehicles that could drive themselves, so that travel would be less challenging, free from human driver errors and the roads safer for everyone. Self-driving cars are env...

全面介紹

Saved in:
書目詳細資料
主要作者: Ketki, Chaudhary
其他作者: Justin Dauwels
格式: Theses and Dissertations
語言:English
出版: 2018
主題:
在線閱讀:http://hdl.handle.net/10356/76332
標簽: 添加標簽
沒有標簽, 成為第一個標記此記錄!
機構: Nanyang Technological University
語言: English
id sg-ntu-dr.10356-76332
record_format dspace
spelling sg-ntu-dr.10356-763322023-07-04T15:41:34Z Safety assessment of autonomous vehicles using simulations Ketki, Chaudhary Justin Dauwels School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Since the past few decades, researchers from both automotive and technology industries have focussed their attention on developing vehicles that could drive themselves, so that travel would be less challenging, free from human driver errors and the roads safer for everyone. Self-driving cars are envisioned as robots capable of precise driving, never getting distracted, abiding to all the traffic rules and being able to compute the probability of an imminent collision well in advance. Regardless of all these safety precautions, there have been instances of crashes involving big autonomous vehicles developers like Tesla, Uber etc. Undoubtedly, this raises a question of how safe autonomous vehicles are and what are the available methods to assess their safety. The work in this thesis focuses on developing a simulation methodology that can potentially evaluate the safety of highly autonomous vehicles (Level 5) in complex traffic environments. The scope of this thesis is limited to safety analysis of a scenario that involves autonomous obstacle avoidance during a lane changing and highway exit manoeuvre, in the presence of high-paced highway traffic. The purpose of this work is to adopt the minimum spacing requirements for both longitudinal and lateral dynamics of the autonomous vehicle. These requirements are derived using an automotive standard-ISO26262 as a reference and each test scenario is analysed for its compliance to the safe limits. Safety is analysed by recording the vehicle behaviour data, using simulations, and calculating some crucial parameters. An initial trajectory (mission planning) is first planned and whenever an obstacle is detected by the AV, the new set of waypoints (path planning) are computed iteratively. For different configurations of the afore-mentioned, the simulation data is analysed using MATLAB and checked whether or not it meets safety constraints. The thesis is concluded with discussions on the results and possible future extension of the work carried out in this thesis. Master of Science (Computer Control and Automation) 2018-12-19T14:29:04Z 2018-12-19T14:29:04Z 2018 Thesis http://hdl.handle.net/10356/76332 en 64 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Ketki, Chaudhary
Safety assessment of autonomous vehicles using simulations
description Since the past few decades, researchers from both automotive and technology industries have focussed their attention on developing vehicles that could drive themselves, so that travel would be less challenging, free from human driver errors and the roads safer for everyone. Self-driving cars are envisioned as robots capable of precise driving, never getting distracted, abiding to all the traffic rules and being able to compute the probability of an imminent collision well in advance. Regardless of all these safety precautions, there have been instances of crashes involving big autonomous vehicles developers like Tesla, Uber etc. Undoubtedly, this raises a question of how safe autonomous vehicles are and what are the available methods to assess their safety. The work in this thesis focuses on developing a simulation methodology that can potentially evaluate the safety of highly autonomous vehicles (Level 5) in complex traffic environments. The scope of this thesis is limited to safety analysis of a scenario that involves autonomous obstacle avoidance during a lane changing and highway exit manoeuvre, in the presence of high-paced highway traffic. The purpose of this work is to adopt the minimum spacing requirements for both longitudinal and lateral dynamics of the autonomous vehicle. These requirements are derived using an automotive standard-ISO26262 as a reference and each test scenario is analysed for its compliance to the safe limits. Safety is analysed by recording the vehicle behaviour data, using simulations, and calculating some crucial parameters. An initial trajectory (mission planning) is first planned and whenever an obstacle is detected by the AV, the new set of waypoints (path planning) are computed iteratively. For different configurations of the afore-mentioned, the simulation data is analysed using MATLAB and checked whether or not it meets safety constraints. The thesis is concluded with discussions on the results and possible future extension of the work carried out in this thesis.
author2 Justin Dauwels
author_facet Justin Dauwels
Ketki, Chaudhary
format Theses and Dissertations
author Ketki, Chaudhary
author_sort Ketki, Chaudhary
title Safety assessment of autonomous vehicles using simulations
title_short Safety assessment of autonomous vehicles using simulations
title_full Safety assessment of autonomous vehicles using simulations
title_fullStr Safety assessment of autonomous vehicles using simulations
title_full_unstemmed Safety assessment of autonomous vehicles using simulations
title_sort safety assessment of autonomous vehicles using simulations
publishDate 2018
url http://hdl.handle.net/10356/76332
_version_ 1772829116366585856