10 Evaluation and Naturalistic Data Flashcards
V-Diagram
** \ :**
* Crash scenarios and causation mechanisms
* User Needs & Requirements Concept of Operations
* Requirements Analysis & System Specification
* System Design
V:
* Hard- & Software Development
- System Integration & Testing
- Sys Verification & Development
- Sys Validation
- Cost-benefit analysis/ safety-benefit analysis
/:
Validation vs verification
Verification:
* Does the system/sub-system/component satisfy requirements and regulations?
* Did we build the system correctly, according to the specs?
Validation:
* Does the system meet the operational needs of the user?
* Did we build the system so that it deliver the intended benefits?
Active safety evalution
- all parts of an active safety system must be evaluated individually and within subsystems
- several tools are used in the evaluation
Methods for active safety
evaluation (development)
- Simulator (low-fidelity)
- Simulator (high-fidelity)
- Test-Track
- Real-world (controlled observation)
- Real word (FOT = Field Operational Text & NDS = Naturalistic Driving Study)
- Counterfactual simulations
Simulator (low-fidelity)
- duration: low
- control: high
- cost: low
- validity: low
- risk: low
Simulator (high-fidelity)
- duration: low
- control: high
- cost: low/medium
- validity: low/medium
- risk: low
Test-Track
- duration: middle
- control: middle
- cost: low/medium
- validity: middle
- risk: high
Real-world (controlled observation)
- duration: middle
- control: middle
- cost: low/medium
- validity: high
- risk: highest
Real word (FOT = Field Operational Text & NDS = Naturalistic Driving Study)
- duration: highest
- control: low
- cost: highest
- validity: highest
- risk: highest
Counterfactual simulations
- duration: low
- control: high
- cost: low
- validity: low
- risk: low
We focus on naturalistic data as a tool to evaluate active safety
because
- high ecological validity (genuine driver behaviour).
- increasingly available
- most genuine road-user behaviour.
Naturalistic data
- Naturalistic data is big data collected in
real-traffic (in the wild), by road users
performing their usual daily activities. - Traditionally recorded from instrumented
cars and trucks.
Naturalistic data (Pro/con)
Pro:
* Captures genuine driver behavior → High ecological validity.
* Includes behavior just before crashes → Crucial for crash causation analysis.
* Shows driver interaction with technology (e.g., ADAS, automation).
* Assesses the real impact of safety systems (requires large datasets).
* Supports virtual safety assessments of new ADAS/automation features.
Con:
* Biases (Vehicles, Drivers, Geography, Seasonal changes)
* can only prove association and not causality
Heinrich’s triangle in traffic safety
- 1 Fatality
- 10 Severe Injuries
- 100 Minor Injuries
- 1000 Property Damages
- 2Million Near-Crashes
Naturalistic study - Data types
Objective
* Videos
* CAN (environment, driver, vehicle)
* Extra sensors (eye tracking)
* Maps (e.g. Navteq)
Subjective
* Interviews
* Diaries
* Demographics
* Annotations (manual coding of videos)