Heavy-tailed distributions in fatal traffic accidents: role of human activities

TL;DR

This paper investigates how human activities influence the heavy-tailed distributions observed in fatal traffic accidents, using empirical data and simple models to understand their stochastic origins.

Contribution

It introduces mathematical models linking human activities to heavy-tailed accident distributions and validates them with empirical data.

Findings

Heavy-tailed distributions are linked to human activity patterns.

Models successfully replicate empirical heavy-tailed behaviors.

Human activities significantly influence accident statistics.

Abstract

Human activities can play a crucial role in the statistical properties of observables in many complex systems such as social, technological and economic systems. We demonstrate this by looking into the heavy-tailed distributions of observables in fatal plane and car accidents. Their origin is examined and can be understood as stochastic processes that are related to human activities. Simple mathematical models are proposed to illustrate such processes and compared with empirical results obtained from existing databanks.