SID: Stereo Image Dataset for Autonomous Driving in Adverse Conditions

El-Shair, Zaid A.; Abu-raddaha, Abdalmalek; Cofield, Aaron; Alawneh, Hisham; Aladem, Mohamed; Hamzeh, Yazan; Rawashdeh, Samir A.

doi:10.1109/naecon61878.2024.10670659

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2024

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SID: Stereo Image Dataset for Autonomous Driving in Adverse Conditions

El-Shair,

Abu-raddaha,

Cofield

et al. 2024

NAECON 2024 - IEEE National Aerospace and Electronics Conference

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SID: Stereo Image Dataset for Autonomous Driving in Adverse Conditions

El-Shair,

Abu-raddaha,

Cofield

et al. 2024

NAECON 2024 - IEEE National Aerospace and Electronics Conference

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A Comprehensive Review of Autonomous Driving Algorithms: Tackling Adverse Weather Conditions, Unpredictable Traffic Violations, Blind Spot Monitoring, and Emergency Maneuvers

Xu,

Sankar

2024

Algorithms

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With the rapid development of autonomous driving technology, ensuring the safety and reliability of vehicles under various complex and adverse conditions has become increasingly important. Although autonomous driving algorithms perform well in regular driving scenarios, they still face significant challenges when dealing with adverse weather conditions, unpredictable traffic rule violations (such as jaywalking and aggressive lane changes), inadequate blind spot monitoring, and emergency handling. This review aims to comprehensively analyze these critical issues, systematically review current research progress and solutions, and propose further optimization suggestions. By deeply analyzing the logic of autonomous driving algorithms in these complex situations, we hope to provide strong support for enhancing the safety and reliability of autonomous driving technology. Additionally, we will comprehensively analyze the limitations of existing driving technologies and compare Advanced Driver Assistance Systems (ADASs) with Full Self-Driving (FSD) to gain a thorough understanding of the current state and future development directions of autonomous driving technology.

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SID: Stereo Image Dataset for Autonomous Driving in Adverse Conditions

Cited by 2 publications

References 23 publications

SID: Stereo Image Dataset for Autonomous Driving in Adverse Conditions

SID: Stereo Image Dataset for Autonomous Driving in Adverse Conditions

A Comprehensive Review of Autonomous Driving Algorithms: Tackling Adverse Weather Conditions, Unpredictable Traffic Violations, Blind Spot Monitoring, and Emergency Maneuvers

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