A Diversity Analysis of Safety Metrics Comparing Vehicle Performance in the Lead-Vehicle Interaction Regime
Vehicle performance metrics analyze data sets consisting of subject vehicle's interactions with other road users in a nominal driving environment and provide certain performance measures as outputs. To the best of the authors' knowledge, the vehicle safety performance metrics research date...
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Zusammenfassung: | Vehicle performance metrics analyze data sets consisting of subject vehicle's
interactions with other road users in a nominal driving environment and provide
certain performance measures as outputs. To the best of the authors' knowledge,
the vehicle safety performance metrics research dates back to at least 1967. To
date, there still does not exist a community-wide accepted metric or a set of
metrics for vehicle safety performance assessment and justification. This issue
gets further amplified with the evolving interest in Advanced Driver Assistance
Systems and Automated Driving Systems. In this paper, the authors seek to
perform a unified study that facilitates an improved community-wide
understanding of vehicle performance metrics using the lead-vehicle interaction
operational design domain as a common means of performance comparison. In
particular, the authors study the diversity (including constructive formulation
discrepancies and empirical performance differences) among 33 base metrics with
up to 51 metric variants (with different choices of hyper-parameters) in the
existing literature, published between 1967 and 2022. Two data sets are adopted
for the empirical performance diversity analysis, including vehicle
trajectories from normal highway driving environment and relatively high-risk
incidents with collisions and near-miss cases. The analysis further implies
that (i) the conceptual acceptance of a safety metric proposal can be
problematic if the assumptions, conditions, and types of outcome assurance are
not justified properly, and (ii) the empirical performance justification of an
acceptable metric can also be problematic as a dominant consensus is not
observed among metrics empirically. |
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DOI: | 10.48550/arxiv.2306.14657 |