Traffic incident analysis on urban arterials using ESE: A method for moderate length of time window

TL;DR

This paper introduces a novel method using extended spectral envelope and a quality index to accurately detect key incident times on urban arterials within moderate time windows, validated through real traffic incident data.

Contribution

The paper proposes a new approach to determine the optimal moderate time window for incident detection using spectral analysis and a novel quality index.

Findings

Method accurately detects incident times in Beijing traffic data

Significant vertical lines in eigenvectors indicate key incident periods

The proposed quality index effectively measures time window suitability

Abstract

Moderate length of time window can get the best accurate result in detecting the key incident time using extended spectral envelope. This paper presents a method to calculate the moderate length of time window. Two factors are mainly considered: (1) The significant vertical lines consist of negative elements of eigenvectors; (2) the least amount of interruption. The elements of eigenvectors are transformed into binary variable to eliminate the interruption of positive elements. Sine transform is introduced to highlight the significant vertical lines of negative elements. A novel Quality Index (QI) is proposed to measure the effect of different lengths of time window. Empirical studies on four real traffic incidents in Beijing verify the validity of this method.