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Related Concept Videos

Design Consideration01:22

Design Consideration

421
Designing a structure involves a series of considerations, primarily the material's ultimate strength, calculated through tests that measure changes under increased force until the material reaches its breaking point or limit. The ultimate load, where the material breaks, is divided by its original cross-sectional area, resulting in the ultimate normal stress or strength. The ultimate shearing stress is another significant factor taken into account.
The factor of safety is another key...
421
PD Controller: Design01:26

PD Controller: Design

466
In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
466
Sight Distance in a Vertical Curve01:29

Sight Distance in a Vertical Curve

209
Sight distance on vertical curves is critical in roadway design. It ensures drivers can see far enough ahead to identify and respond to hazards effectively. This directly impacts safety, driver comfort, and the overall efficiency of the transportation network.Vertical curves are classified into crest and sag curves based on their geometry. For crest curves, sight distance is determined by the line of sight between a driver's eye and a small object on the road's surface. Design parameters for...
209

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Data Acquisition Protocol for Determining Embedded Sensitivity Functions
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Deriving functional safety (ISO 26262) S-parameters for vulnerable road users from national crash data.

J Krampe1, M Junge2

  • 1University of Mannheim, Mannheim, Germany.

Accident; Analysis and Prevention
|December 28, 2020
PubMed
Summary

This study develops a data-driven approach to estimate injury severity for advanced driver assistance systems (ADAS) and automated vehicles (AV) interacting with vulnerable road users (VRU). Results provide crucial S-parameters for enhancing functional safety in mixed traffic environments.

Keywords:
ADASAutonomous vehicleISO 26262Injury severityPedestrianS-parameterVulnerable road user

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Area of Science:

  • Road safety engineering
  • Automotive functional safety
  • Traffic accident analysis

Background:

  • Advanced driver assistance systems (ADAS) and automated vehicles (AV) operate alongside vulnerable road users (VRU) in shared road spaces.
  • Assessing functional safety (ISO 26262 S-parameters) is critical for minimizing crash frequency and injury severity involving VRUs.

Purpose of the Study:

  • To develop a data-driven method for estimating injury severity (S-parameters) for four VRU types (pedestrians, bicyclists, scooterists, motorcyclists).
  • To enhance population-based accident data (DESTATIS) with in-depth study data (GIDAS) for detailed injury severity mapping to the S-scale.

Main Methods:

  • Transformed injury severity from DESTATIS (4-level scale) to ISS breakpoints (ISS ≥{4, 9, 16}) using GIDAS data, enabling translation to the S-scale.
  • Analyzed crashes by VRU type, vehicle type (BTV, LTV), injury mechanism, and traffic domain (speed limit clusters).
  • Calculated S-parameters (90th-percentile injury severity) with a one-sided 95% confidence level for each VRU, mechanism, and domain.

Main Results:

  • Established a method to translate police-reported injury severities to the S-scale, facilitating the use of population data for 'severe injury' (MAIS 3+) proportion estimation.
  • Derived S-parameters specific to VRU type, vehicle interaction, and traffic environment.
  • Demonstrated applications in evaluating AVs, ADAS, and protective gear for VRUs.

Conclusions:

  • The developed data-driven approach provides essential S-parameters for functional safety assessments in ADAS and AV development.
  • Accurate injury severity estimation is vital for improving the safety of vulnerable road users in mixed traffic scenarios.
  • This methodology enables better utilization of large-scale accident databases for safety-critical automotive applications.