A General Measure of Collision Hazard in Traffic

TL;DR

This paper introduces the Streetscope Collision Hazard Measure (SHM), a new safety metric for traffic that uses near-miss data to provide a continuous, quantitative hazard assessment, overcoming limitations of existing measures.

Contribution

The paper presents the SHM, a novel collision hazard measure based on near-misses, that offers a scalable, continuous, and quantitative safety assessment for traffic environments.

Findings

SHM effectively predicts incident likelihood and severity.

SHM overcomes limitations of TTC, RSS, and ISM measures.

Near-miss data is shown to be a reliable predictor of safety risk.

Abstract

A collision hazard measure that has the essential characteristics to provide a measurement of safety that will be useful to AV developers, traffic infrastructure developers and managers, regulators and the public is introduced here. The Streetscope Collision Hazard Measure (SHM) overcomes the limitations of existing measures, and provides an independent leading indication of safety. * Trailing indicators, such as collision statistics, incur pain and loss on society, and are not an ethically acceptable approach. * Near-misses have been shown to be effective predictors of incidents. * Time-to-Collision (TTC) provides ambiguous indication of collision hazards, and requires assumptions about vehicle behavior. * Responsibility-Sensitive Safety (RSS), because of its reliance on rules for individual circumstances, will not scale up to handle the complexities of traffic. * Instantaneous Safety Metric (ISM) relies on probabilistic predictions of behaviors to categorize events (possible, imminent, critical), and does not provide a quantitative measure of the severity of the hazard. * Inertial Measurement Unit (IMU) acceleration data is not correlated with hazard or risk. * A new measure, based on the concept of near-misses, that incorporates both proximity (separation distance) and motion (relative speed) is introduced. * Near-miss data has been shown to be predictive of the likelihood and severity of incidents. The new measure presented here gathers movement data about vehicles continuously and a quantitative score reflecting the hazard encountered or created (from which the riskiness or safeness of the behavior of vehicles can be estimated) is computed nearly continuously.