Safety challenges for autonomous vehicles in the absence of connectivity

Shetty, Akhil; Yu, Mengqiao; Kurzhanskiy, Alex A.; Grembek, Offer; Tavafoghi, Hamidreza; Varaiya, Pravin

doi:10.1016/j.trc.2021.103133

Cited by 52 publications

(33 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For instance, V2V and V2I technologies could warn about approaching vehicles at intersections or changing weather conditions [22]. Connectivity has been assessed to be a notable factor in ensuring automated vehicle safety [23].…”

Section: Cavs' Safety Impactmentioning

confidence: 99%

The Needed Features of Connected and Automated Vehicles to Prevent Passenger Car Crashes Caused by Driving Errors

Utriainen

Pöllänen

2021

Future Transportation

View full text Add to dashboard Cite

Connected and automated vehicles (CAVs) can enhance traffic safety considerably. However, as CAVs are currently under development, the safety impact cannot be assessed directly. In this study, driver-managed passenger car crashes with fatalities in Finland were investigated qualitatively to evaluate the needed features of the CAVs to avoid these crashes. The focus was on single-car crashes and collisions between passenger cars, in which the immediate risk factor was a driving error (n = 48). Most of the analysed crashes (33 of 48) were due to loss of control with typically adverse weather or road conditions. To avoid these crashes, a CAV should be able to adjust its speed according to the conditions. In 13 of 48 crashes, the car was under control prior to the crash. A reliable capability to recognize other road users is an important CAV feature, because observational errors were common in these cases. In addition, communication between the vehicles could assist in avoiding intersection crashes and crashes caused by a sudden change in weather conditions. This study increases knowledge on crashes related to driving errors and the needed features of CAVs to avoid these crashes. In particular, CAVs’ feature to adjust the speed is important, because cases of loss of control in adverse weather or road conditions were typical events.

show abstract

Section: Cavs' Safety Impactmentioning

confidence: 99%

The Needed Features of Connected and Automated Vehicles to Prevent Passenger Car Crashes Caused by Driving Errors

Utriainen

Pöllänen

2021

Future Transportation

View full text Add to dashboard Cite

show abstract

“…However, as far as the authors know, there is no method to completely define an ODD, therefore the boundary between functional insufficiency and ODD exit might be vague. 4. If this misbehavior is explicitly specified in the logical scenario, it will be considered as a performance limitation, otherwise it will be considered as a specification insufficiency.…”

Section: Safety and The Sources Of Harmmentioning

confidence: 99%

“…Potential lack of Communication: As shown in [172], some functional insufficiencies cannot be resolved without V2V (Vehicle to Vehicle) and V2I (Vehicle to Infrastructure) communication. Examples of such functional insufficiencies include occlusions, traffic violation by other road users, and the uncertainty of behavior prediction.…”

Section: Other Sources Of Harmmentioning

confidence: 99%

“…While this may be very promising in the long term, it is hard to accomplish in the short term given mixed-mode traffic (e.g., manually driven cars together with vehicles at level 4 of automated driving), the complexity of automated driving, and the need to agree on what represents a suitable risk level (compromise between performance and safety). A third avenue would be to leverage collaborating driving and smart infrastructure, however this requires multistakeholder coordination, infrastructure investments and dealing with new security related threats, thus complicating and delaying such an approach, see e.g., [4].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Finding Critical Scenarios for Automated Driving Systems: A Systematic Literature Review

Zhang¹,

Tao²,

Tan³

et al. 2021

Preprint

View full text Add to dashboard Cite

Scenario-based approaches have been receiving a huge amount of attention in research and engineering of automated driving systems. Due to the complexity and uncertainty of the driving environment, and the complexity of the driving task itself, the number of possible driving scenarios that an ADS or ADAS may encounter is virtually infinite. Therefore it is essential to be able to reason about the identification of scenarios and in particular critical ones that may impose unacceptable risk if not considered. Critical scenarios are particularly important to support design, verification and validation efforts, and as a basis for a safety case. In this paper, we present the results of a systematic literature review in the context of autonomous driving. The main contributions are: (i) introducing a comprehensive taxonomy for critical scenario identification methods; (ii) giving an overview of the state-of-the-art research based on the taxonomy encompassing 86 papers between 2017 and 2020; and (iii) identifying open issues and directions for further research. The provided taxonomy comprises three main perspectives encompassing the problem definition (the why), the solution (the methods to derive scenarios), and the assessment of the established scenarios. In addition, we discuss open research issues considering the perspectives of coverage, practicability, and scenario space explosion.

show abstract

“…T HE long and winding road towards high levels of automated driving is fascinating and highly representative of an ongoing technological paradigm shift, see e.g., [1] and further references therein. The past years have seen enormous amounts of funding going into a new automated driving ecosystem of startups, new players and the existing automotive industry, [2], attracting in excess of 80 billion US dollars during the period 2014 to 2017 [3], with likely more than 100 billion US dollars invested the past decade, [4]. As a result, impressive advances have been made and technology has matured.…”

Section: Introductionmentioning

confidence: 99%

Finding Critical Scenarios for Automated Driving Systems: A Systematic Mapping Study

Zhang¹,

Tao²,

Tan

et al. 2023

IIEEE Trans. Software Eng.

View full text Add to dashboard Cite

Scenario-based approaches have been receiving a huge amount of attention in research and engineering of automated driving systems. Due to the complexity and uncertainty of the driving environment, and the complexity of the driving task itself, the number of possible driving scenarios that an Automated Driving System or Advanced Driving-Assistance System may encounter is virtually infinite. Therefore it is essential to be able to reason about the identification of scenarios and in particular critical ones that may impose unacceptable risk if not considered. Critical scenarios are particularly important to support design, verification and validation efforts, and as a basis for a safety case. In this paper, we present the results of a systematic mapping study in the context of autonomous driving. The main contributions are: (i) introducing a comprehensive taxonomy for critical scenario identification methods; (ii) giving an overview of the state-of-the-art research based on the taxonomy encompassing 86 papers between 2017 and 2020; and (iii) identifying open issues and directions for further research. The provided taxonomy comprises three main perspectives encompassing the problem definition (the why), the solution (the methods to derive scenarios), and the assessment of the established scenarios. In addition, we discuss open research issues considering the perspectives of coverage, practicability, and scenario space explosion.

show abstract

Safety challenges for autonomous vehicles in the absence of connectivity

Cited by 52 publications

References 10 publications

The Needed Features of Connected and Automated Vehicles to Prevent Passenger Car Crashes Caused by Driving Errors

The Needed Features of Connected and Automated Vehicles to Prevent Passenger Car Crashes Caused by Driving Errors

Finding Critical Scenarios for Automated Driving Systems: A Systematic Literature Review

Finding Critical Scenarios for Automated Driving Systems: A Systematic Mapping Study

Contact Info

Product

Resources

About