Evidence map›Paper›PMID 35700684›Full record

ArticleAccident; analysis and prevention2022

Driver models for the definition of safety requirements of automated vehicles in international regulations. Application to motorway driving conditions.

Konstantinos Mattas, Giovanni Albano, Riccardo Donà, Maria Christina Galassi, Ricardo Suarez-Bertoa, Sandor Vass, Biagio Ciuffo

Abstract read
In one paragraph

Article in Accident; analysis and prevention, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Konstantinos MattasEuropean Commission Joint Research Centre, Ispra, Ispra, Italy.
Giovanni AlbanoEuropean Commission Joint Research Centre, Ispra, Ispra, Italy.
Riccardo DonàEuropean Commission Joint Research Centre, Ispra, Ispra, Italy.
Maria Christina GalassiEuropean Commission Joint Research Centre, Ispra, Ispra, Italy.
Ricardo Suarez-BertoaEuropean Commission Joint Research Centre, Ispra, Ispra, Italy.
Sandor VassEuropean Commission Joint Research Centre, Ispra, Ispra, Italy.
Biagio CiuffoEuropean Commission Joint Research Centre, Ispra, Ispra, Italy. Electronic address: biagio.ciuffo@ec.europa.eu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

UN Regulation 157, the first global regulation regarding the type-approval of Automated Driving Systems (ADS), has been adopted in 2021. In it, safety performance requirements are being defined for vehicles of automation Level 3, according to the SAE J3016, with a limited Operational Design Domain (ODD). In particular, for three types of events that are related to motorway driving, two models are provided to distinguish between preventable traffic scenarios, for which the ADS is expected to avoid an accident, and unpreventable traffic scenarios, for which accidents cannot be avoided and the ADS can only mitigate their severity. The models recreate the short-term behavior of a driver who reacts to an emergency. Two possible actions are predicted: either no reaction or full braking when danger is identified. In the present paper the two models are analyzed and compared with two additional models: an industry proposed model, the Responsibility Sensitive Safety framework (RSS), and the Fuzzy Safety Model (FSM) proposed by the authors. As in the case of the two regulation models, also the RSS, although more sophisticated, assumes that the possible reaction by the driver is binary. This approach neglects the ability of a human driver to drive defensively and anticipate possible risks. Defensive drivers, indeed, may use comfortable decelerations in anticipation, to avoid finding themselves in an emergency situation. The FSM uses fuzzy logic to mimic this behavior. Results show that anticipation plays a very important role to reduce the number of unpreventable traffic scenarios. In addition, by validating the classification capabilities of the four models with real traffic data, the FSM proved to be the most suitable of the investigated models. On the basis of these results, the FSM has been included in the proposal for amending UN Regulation 157, thus allowing to set higher safety standards for the first automated vehicles that will be introduced into the market.

Indexed as

Accidents, TrafficAutomobile DrivingAutomationAutonomous VehiclesHumansSafetyConnected and automated vehiclesDriver modelFuzzy logicSafety requirements

Identifiers

PMID35700684
PMCPMC9378973

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.