Evidence map›Paper›PMID 39771717›Full record

ArticleSensors (Basel, Switzerland)2024

Development of Test Cases for Automated Vehicle Driving Safety Assessment Using Driving Trajectories.

Woori Ko, Minkyu Shim, Sangmin Park, Soomok Lee, Ilsoo Yun

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. 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

5 authors.

Woori KoDepartment of Transportation Engineering, Ajou University, Suwon 16499, Republic of Korea.ORCID 0000-0003-3817-3719
Minkyu ShimMobility Department, TÜV SÜD Korea Ltd., Seoul 07326, Republic of Korea.
Sangmin ParkDepartment of Road Transport Research, The Korea Transport Institute, Sejong 30147, Republic of Korea.ORCID 0000-0002-9210-5381
Soomok LeeDepartment of AI Mobility Engineering, Ajou University, Suwon 16499, Republic of Korea.ORCID 0000-0001-6633-997X
Ilsoo YunDepartment of Transportation System Engineering, Ajou University, Suwon 16499, Republic of Korea.ORCID 0000-0001-5618-7933

Funding

Korea Agency for Infrastructure Technology Advancement (KAIA) grant funded by the Ministry of Land, Infrastructure, and Transport RS-2021-KA160637
6 · The paper itself

Abstract

For consumers to have confidence in the safety of automated vehicles (AVs), AVs must be assessed using systematically developed scenarios to verify driving safety and reliability. In particular, verification using scenarios has been widely performed for the assessment and certification of AVs. This study aims to develop test cases based on driving trajectories to assess the driving safety of AVs. To achieve this, concrete scenarios were systematically developed from functional and logical scenarios. Drone video data analysis was conducted to extract representative lane-change trajectories for AVs on expressway ramp sections. Subsequently, the test cases were selected from concrete scenarios through simulations using time-to-steer (TTS). Finally, the effectiveness of utilizing trajectories for scenario-based driving safety assessments was verified. Furthermore, it is expected that this approach can be applied to other driving patterns by providing a detailed procedure for the test case developed in this study.

Indexed as

assessmentautomated vehiclesdriving safetytest casestrajectory

Identifiers

PMID39771717
PMCPMC11679205

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.