NUP-REPORT 1.0: A Proposed Reporting and Benchmarking Framework for Non-Upright Pedestrian Detection and Pre-Crash Safety Evaluation

Pedestrian-detection research and pre-crash safety assessment predominantly represent upright pedestrians, although prone, supine, lateral, seated, crouched, kneeling, partially collapsed, and fall-transition states alter target geometry, visibility, sensor signatures, and intervention time. Cross-study comparison is further limited by inconsistent posture labels, data provenance, latency boundaries, uncertainty reporting, and vehicle-response assumptions. We developed NUP-REPORT 1.0 as a provisional reporting and benchmarking framework through a structured narrative synthesis of a 45-source derivation corpus covering epidemiology, sensing benchmarks, uncertainty and assurance methods, reporting-guideline methodology, and public safety protocols. A reconstructed decision ledger documented 46 candidate concepts: 30 were retained as checklist items, 10 were assigned to an extended descriptor set, and six were merged. Each retained item was mapped to supporting evidence and classified as universal core (n = 19), component-contingent core (n = 4), or conditional (n = 7). The framework comprises six domains, a scenario-coverage matrix, five non-overlapping event timestamps, detection-referenced stopping equations, and a 30-item checklist. A purposive feasibility audit of 20 publications, including the adjacent pedestrian-detection literature not designed specifically for non-upright evaluation, illustrated checklist use. Within this sample, target orientation and static-versus-transition state were each reported explicitly in five of 20 publications (25%); none of the 17 applicable papers reported both time-to-first-detection and detection distance, none evaluated confidence calibration, and none of the 20 reported independent-unit uncertainty intervals. Vehicle-response items were non-applicable to papers making no intervention claim. These observations are sample-specific and do not estimate field-wide reporting prevalence. NUP-REPORT is not a consensus standard, certification procedure, or safety score; it is a traceable Version 1.0 proposal for study design, retrospective audit, and stakeholder refinement.

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Publication Details

Journal
Sensors
Published
2026-09-09
DOI
https://doi.org/10.3390/s26185710
Primary Topic
Traffic and Road Safety
Type
article
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NUP-REPORT 1.0: A Proposed Reporting and Benchmarking Framework for Non-Upright Pedestrian Detection and Pre-Crash Safety Evaluation

Nick Barua, Masahito Hitosugi
Sensors
Traffic and Road Safety
article

NUP-REPORT 1.0: A Proposed Reporting and Benchmarking Framework for Non-Upright Pedestrian Detection and Pre-Crash Safety Evaluation

Nick Barua, Masahito Hitosugi
article en

Abstract

Pedestrian-detection research and pre-crash safety assessment predominantly represent upright pedestrians, although prone, supine, lateral, seated, crouched, kneeling, partially collapsed, and fall-transition states alter target geometry, visibility, sensor signatures, and intervention time. Cross-study comparison is further limited by inconsistent posture labels, data provenance, latency boundaries, uncertainty reporting, and vehicle-response assumptions. We developed NUP-REPORT 1.0 as a provisional reporting and benchmarking framework through a structured narrative synthesis of a 45-source derivation corpus covering epidemiology, sensing benchmarks, uncertainty and assurance methods, reporting-guideline methodology, and public safety protocols. A reconstructed decision ledger documented 46 candidate concepts: 30 were retained as checklist items, 10 were assigned to an extended descriptor set, and six were merged. Each retained item was mapped to supporting evidence and classified as universal core (n = 19), component-contingent core (n = 4), or conditional (n = 7). The framework comprises six domains, a scenario-coverage matrix, five non-overlapping event timestamps, detection-referenced stopping equations, and a 30-item checklist. A purposive feasibility audit of 20 publications, including the adjacent pedestrian-detection literature not designed specifically for non-upright evaluation, illustrated checklist use. Within this sample, target orientation and static-versus-transition state were each reported explicitly in five of 20 publications (25%); none of the 17 applicable papers reported both time-to-first-detection and detection distance, none evaluated confidence calibration, and none of the 20 reported independent-unit uncertainty intervals. Vehicle-response items were non-applicable to papers making no intervention claim. These observations are sample-specific and do not estimate field-wide reporting prevalence. NUP-REPORT is not a consensus standard, certification procedure, or safety score; it is a traceable Version 1.0 proposal for study design, retrospective audit, and stakeholder refinement.

SensorsVol. 26(18)
Shiga University of Medical Science (JP), Shiga University (JP)
Good health and well-being
Openalex Percentile: Top 11%
Traffic and Road Safety
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