Will Weather Dampen Self-Driving Vehicles?

Walker, Charles F.; Boyce, Brenda; Albrecht, Christopher; Siems-Anderson, Amanda

doi:10.1175/bams-d-19-0035.1

Cited by 11 publications

(3 citation statements)

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“…However, severe weather conditions can impair the autonomous driving perception system and prevent it from detecting and recognizing on-road objects and sign boards. This can cause selfdriving cars to make wrong decisions or fail to make decisions in such situations [5,6,[55][56][57]. In other words, bad weather can hinder autonomous driving capabilities.…”

Section: A Inclement Weathermentioning

confidence: 99%

“…Since there are two sides to a coin, it is good to be aware of the disadvantages of autonomous vehicles too. One of the main limitations of self-driving technology is its inability to operate effectively in all weather and road conditions [5,6]. For instance, self-driving cars may have difficulty navigating through heavy rain or snow, which can affect the car's sensors and cameras, leading to accidents.…”

Section: Introductionmentioning

confidence: 99%

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A Comprehensive Review on Limitations of Autonomous Driving and Its Impact on Accidents and Collisions

Chougule,

Chamola,

Sam

et al. 2024

IEEE Open J. Veh. Technol.

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The emergence of autonomous driving represents a pivotal milestone in the evolution of the transportation system, integrating seamlessly into the daily lives of individuals due to its array of advantages over conventional vehicles. However, selfdriving cars pose numerous challenges contributing to accidents and injuries annually. This paper aims to comprehensively examine the limitations inherent in autonomous driving and their consequential impact on accidents and collisions. Using data from the DMV, NMVCCS, and NHTSA, the paper reveals the key factors behind self-driving car accidents. It delves into prevalent limitations faced by self-driving cars, encompassing issues like adverse weather conditions, susceptibility to hacking, data security concerns, technological efficacy, testing and validation intricacies, information handling, and connectivity glitches. By meticulously analyzing reported accidents involving self-driving cars during the period spanning 2019 to 2022, the research evaluates statistical data pertaining to fatalities and injuries across diverse accident classifications. Additionally, the paper delves into the ethical and regulatory dimensions associated with autonomous driving, accentuating the legal complexities that arise from accidents involving self-driving vehicles. This review assists researchers and professionals by identifying current autonomous driving limitations and offering insights for safer adoption. Addressing these limitations through research can transform transportation systems for the better.

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Section: A Inclement Weathermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Comprehensive Review on Limitations of Autonomous Driving and Its Impact on Accidents and Collisions

Chougule,

Chamola,

Sam

et al. 2024

IEEE Open J. Veh. Technol.

View full text Add to dashboard Cite

show abstract

“…Due to the visibility reduction, fog can affect human activities in many fields like free-space optical (FSO) communication, aviation or ground transportation [43,44,75]. In this latter field, adverse weather conditions are issues for the development of intelligent vehicle and autonomous driving since perceptive sensors like camera, radar and lidar are largely employed [90,70,81,33,91,71]. To evaluate the impact of these adverse conditions on optical sensors, the French research and technical center Cerema operates the European Rain and Fog PAVIN platform (Figure 1) in which optical sensors and cars can be submitted to controlled artificial fog and rain [19,23,28,29].…”

Section: Introductionmentioning

confidence: 99%

Identification of fog Particle Size Distribution by a radiative transfer equation inversion

Krayem,

Bernardin,

Münch

2024

Journal of Quantitative Spectroscopy and Radiative Transfer

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The use of vehicle‐based observations in weather prediction and decision support

Siems‐Anderson

2024

Meteorological Applications

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Vehicle‐based mobile observations are taken across the world every day by operational and research meteorological organizations, public transportation agencies, and private car manufacturers. Whether directly weather‐related (e.g., air temperature) or not (e.g., wiper speed), the coverage and frequency of these observations holds the promise of filling in gaps between fixed observing stations and greatly improving situational awareness and weather forecasting, from road surface condition‐specific applications and winter road maintenance to urban and street‐level numerical weather prediction and beyond. However, in order to take advantage of these observations, the weather, water, and climate enterprise must work together with the transportation enterprise across academic, public, and private sectors to provide a mechanism for obtaining these data, so that the benefits of using these unconventional observations may be realized.

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Will Weather Dampen Self-Driving Vehicles?

Abstract: Capsule Summary Self-driving vehicles will revolutionize society; however, their safe and reliable implementation in all weather conditions requires critical partnerships between the meteorological, transportation, and vehicle manufacturer communities.

Cited by 11 publications

References 11 publications

A Comprehensive Review on Limitations of Autonomous Driving and Its Impact on Accidents and Collisions

A Comprehensive Review on Limitations of Autonomous Driving and Its Impact on Accidents and Collisions

Identification of fog Particle Size Distribution by a radiative transfer equation inversion

The use of vehicle‐based observations in weather prediction and decision support

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