Concepts and Risk Analysis for a Cooperative and Automated Highway Platooning System

Bergenhem, Carl; Majdandzic, Mario; Ursing, Stig

doi:10.1007/978-3-030-58462-7_16

Cited by 3 publications

(3 citation statements)

References 8 publications

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“…A common solution for collaborative AVs, especially for non-road use cases such as mines, harbours, or construction sites, is to use a traffic management system (TMS) to control overall operations (i.e., the orchestrated class in Table I). The TMS acts as a mediator between vehicles by providing instructions when needed, while also controlling the system borders as outlined in [12]. Using a TMS in the digger/truck example, the vehicles could be reliant on the TMS to inform each vehicle of its respective status and responsibilities.…”

Section: B Cooperative and Collaborative Vehicle Domainmentioning

confidence: 99%

Minimal Risk Manoeuvre Strategies for Cooperative and Collaborative Automated Vehicles

Vu,

Warg,

Thorsén

et al. 2023

2023 53rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W)

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During the last decade, there has been significant increase in research focused on automated vehicles (AVs) and ensuring safe operation of these vehicles. However, challenges still remain, some involving the cooperation and collaboration of multiple AVs, including when and how to perform a minimal risk manoeuvre (MRM), leading to a minimal risk condition (MRC) when an AV within one of these systems is unable to complete its original goal. As most literature is focused on individual AVs, there is a need to adapt and extend the knowledge and techniques to these new contexts. Based on existing knowledge of individual AVs, this paper explores MRM strategies involving cooperative and collaborative AV systems with different capabilities. Specifically, collaborative systems have the potential to enact local MRCs, allowing continued productivity despite having one (or several) of its constituents encounter a fault. Definitions are provided for local and global MRCs, alongside discussions of their implications for MRMs. Illustrative examples are also presented for each type of system.

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Section: B Cooperative and Collaborative Vehicle Domainmentioning

confidence: 99%

Minimal Risk Manoeuvre Strategies for Cooperative and Collaborative Automated Vehicles

Vu,

Warg,

Thorsén

et al. 2023

2023 53rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W)

Self Cite

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“…Another method to quantify the risk of a driving scenario is proposed in [43], but this method does not consider the likelihood of encountering the scenario and the role of the back-up operator is not explicitly considered. A quantitative assurance framework is proposed in [44], [45], but this framework assumes that the frequency of accidents is known, whereas this is unknown in a prospective assessment. Furthermore, similar to [42], [44] and [45] do not consider the role of a back-up operator.…”

Section: A Risk Quantification Of Automated Driving Systemsmentioning

confidence: 99%

“…A quantitative assurance framework is proposed in [44], [45], but this framework assumes that the frequency of accidents is known, whereas this is unknown in a prospective assessment. Furthermore, similar to [42], [44] and [45] do not consider the role of a back-up operator.…”

Section: A Risk Quantification Of Automated Driving Systemsmentioning

confidence: 99%

Risk Quantification for Automated Driving Systems in Real-World Driving Scenarios

Gelder¹,

Elrofai²,

Saberi

et al. 2021

IEEE Access

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The development of safety validation methods is essential for the safe deployment and operation of Automated Driving Systems (ADSs). One of the goals of safety validation is to prospectively evaluate the risk of an ADS dealing with real-world traffic. ISO 26262 and ISO/DIS 21448, the leading standards in automotive safety, provide an approach to estimate the risk where the former focuses on risks due to potential malfunctioning of components and the latter focuses on risks due to possible functional insufficiencies. The main shortcomings of the approach provided in ISO 26262 are that it depends on subjective judgments of safety experts and that only a qualitative risk estimation is performed. ISO/DIS 21448 addresses these shortcomings partially by providing statistical methods to guide the safety validation, but no complete method is provided to quantify the risk. The first objective of this article is to propose a method to estimate the risk of an ADS in a more quantitative and objective manner. A data-driven approach is used to rely less on subjective judgments of safety experts. The output of the method is the expected number of injuries in a potential collision. Thus, the method is quantitative, the result is easily interpretable, and the result can be compared with road crash statistics. The second objective is to provide a method that supports the risk assessment as stipulated by the ISO 26262 and ISO/DIS 21448 standards by decomposing the quantified risk into the 3 aspects of risk as mentioned in these standards: exposure, severity, and controllability. The proposed methods are illustrated by means of a case study in which the risk is quantified for a longitudinal controller in 3 different types of scenarios. The code of the case study is publicly available.

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Integrated Overtaking Model and Safety Analysis for Truck Platooning Requirements on Two-Lane Undivided Highways

(Fred) Song

2024

Transportation Research Record: Journal of the Transportation R

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Truck platooning is a promising solution for enhancing efficiency and reducing fuel consumption in freight transportation. However, overtaking truck platoons poses safety challenges that need to be addressed. This paper employs an overtaking model incorporating lane change dynamics, and a collision risk assessment to evaluate the safety risks involved in overtaking truck platoons. The safety assessment is presented through a numerical analysis that considers three aspects: roadway geometry, traffic conditions, and driver behavior. Scenarios representing different truck platoon lengths, driver behavior, and opposing traffic conditions are evaluated, highlighting their impact on safety. Two major findings from the assessment are that the overtaking distance and time increase linearly as the truck platoon length increases, and potential driver hesitation and the presence of opposing vehicles are shown to increase collision risks. Safety implications are that the length of truck platoons needs to be regulated on two-lane undivided highways; and driver behavior should be considered in the safety assessment and regulation of truck platooning, but further investigations are needed. From the perspective of overtaking, this paper emphasizes the need for safety guidelines and regulations for truck platooning. Policymakers, transportation agencies, and industry stakeholders may utilize the findings to establish standardized safety measures and protocols.

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Concepts and Risk Analysis for a Cooperative and Automated Highway Platooning System

Cited by 3 publications

References 8 publications

Minimal Risk Manoeuvre Strategies for Cooperative and Collaborative Automated Vehicles

Minimal Risk Manoeuvre Strategies for Cooperative and Collaborative Automated Vehicles

Risk Quantification for Automated Driving Systems in Real-World Driving Scenarios

Integrated Overtaking Model and Safety Analysis for Truck Platooning Requirements on Two-Lane Undivided Highways

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