Autonomous Driving System Evaluation Metrics
A comprehensive set of evaluation dimensions and metrics to assess the safety, robustness, efficiency, and cost-effectiveness of autonomous driving systems.
- Disengagement Rate: Number of human interventions per 1,000 miles or kilometers driven.
- Accident Rate: Number of collisions or safety-critical incidents per test distance or hours.
- Near-Miss Rate: Number of events where the system narrowly avoided a collision.
- Extreme Scenario Handling Success Rate: Percentage of correct responses in rare or emergency situations (e.g., pedestrian darting into the road, high-speed cut-ins).
- Safety-Critical HMI Alerts: Number of emergency alerts or warnings issued to the driver.
- Weather Coverage: Number of supported weather conditions and test miles under each (clear, cloudy, light/moderate/heavy rain, light/moderate/heavy snow, light/dense fog, hail, strong winds).
- Lighting Conditions Support: Test mileage in daylight, nighttime, dawn, dusk, tunnels, and sudden lighting transitions.
- Visibility Range: Effective perception distance under different visibility levels (fog, rain, snow).
- Road Type Coverage: Proportion of test miles on highways, urban roads, suburban roads, rural roads, and private roads.
- Topology Robustness: Success rate in handling intersections, roundabouts, construction zones, and complex road layouts.
- Traffic Density Adaptability: Average speed and safety metrics under light, moderate, and heavy traffic.
- Dynamic Object Diversity: Detection and avoidance accuracy for various road users (cars, trucks, motorcycles, bicycles, pedestrians, animals).
- Behavioral Edge Cases: Success rate in responding to non-standard behaviors (running red lights, aggressive lane changes, sudden braking).
- Speed Range Compliance: Percentage of time the system stays within specified minimum and maximum speed limits.
- Load & Weight Impact: Variation in braking distance and acceleration under different load conditions (unladen vs. fully loaded).
- Vehicle Type Adaptation: Performance benchmarks for passenger cars, commercial vehicles, and special-purpose vehicles.
- Inference Latency: Average and maximum delay of perception and decision-making modules.
- Throughput: Sustained processing capability (frames per second) at target sensor rates.
- Resource Utilization: CPU, GPU, memory, and network bandwidth usage.
- Power Consumption: Energy usage of the onboard compute platform under typical load.
- Failure Rate: Frequency of software or hardware failures leading to degraded performance or system resets.
- Recovery Time: Time required for the system to return to normal operation after a fault or anomaly.
- Sensor Degradation Handling: Performance retention rate when sensors are partially obstructed or degraded.
- Comfort Metrics: Lateral and longitudinal acceleration variation, counts of harsh acceleration or braking events.
- Ride Smoothness Score: Composite rating based on passenger feedback and acceleration signals.
- Driver Interaction Frequency: Number of manual overrides or driver alerts per distance.
- Operational Efficiency: Average trip time, average speed, and route optimality.
- Operational Cost: Energy consumption per distance and maintenance costs.
- Total Cost of Ownership: Combined hardware, software, maintenance, and operational expenses.
These metrics can be quantified through real-world testing or simulation. Contributions and additions are welcome!