Relationship Between Pedestrian Protection Test Protocols and a Real Scenario
Notice bibliographique
Résumé
Of the one and a half million accidents which occur in the Euro-15 area every year, and which cause nearly 40,000 deaths, pedestrians account for 15% of these, i.e. about 6,000 per year. The percentage of pedestrians killed in road accidents is about 12% for Canada, USA and Australia, while in Korea and Japan pedestrian fatalities account for as much as 30% and 40% of road deaths. Organizations like Euro NCAP, EEVC and the new Regulation, together with vehicle manufacturers are seeking solutions through the development of advanced safety systems and accurate methods for testing these systems. IDIADA carried out two studies related to pedestrian protection and the relation of protocol to real world accidents. The first study was focused on real world accidents involving pedestrians, and was divided into two parts: 1) Assessment of vehicle speed influence. Sixty-two cases, collected by the Municipal Police and the Public Health Service Agency in which pedestrians were involved in accidents were studied in Barcelona city. 75.1% of accidents occurred during the day, with an ISS 4-5 level of injury, and an ISS 3-4 at night; 2) Study about speed as a cause of accidents. 75.3% of drivers made a braking avoidance maneuver. The average speed before the accident was 50.8 km/h and the impact average velocity was 24.78 km/h. As a result, injury level related to vehicle speed was evaluated. The speed threshold between slight and severe injuries is at about 40 km/h. This value is very similar to the impact velocity used in the current tests to evaluate pedestrian protection in passive safety testing, as for example in Euro NCAP. The objective of the second study was to test the influence of the vehicle design, mainly the front end, on pedestrian head injuries in the case of runover. Several accident simulations were performed using the program MADYMO® in which a pedestrian’s head was impacted into a different point of the hood depending on the situation. The head impact position changes according to vehicle category: collisions in compact and roadster sports cars take place within the limits set by Euro NCAP for adult head impactor while, in the offroad 4x4 class, some points are located below the lower limit for the adult head. If the analysis focuses on the pedestrian's head impact angle and speed against the hood of the car, the following conclusions can be expounded: a) For the same vehicle, impact speed and angle of the adult head against the hood are virtually unchanged although the pedestrian’s speed is different; b) If impact speed is higher, the collision involves worse consequences; c) The shape of the front part of the vehicle is not decisive in the severity of pedestrian injuries; and, d) Further testing is needed to verify that parameters defined by the EEVC, Euro NCAP or pedestrian Regulation are entirely valid according to real world scenarios. The main conclusion of the study and the analysis of actual accident data was that current pedestrian testing protocols are reliable enough to be taken into account when a vehicle pedestrian protection level is assessed.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,014 | 0,132 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,003 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».