Abnormal Spatial-Temporal Pattern Analysis for Niagara Frontier Border Wait Times

TL;DR

This paper applies a dictionary-based compression algorithm to analyze historical border wait times at Niagara Frontier, identifying abnormal patterns and their contributing factors to improve border crossing management.

Contribution

It introduces a novel anomaly detection method for border wait times using compression algorithms, providing quantitative scores and insights into factors affecting delays.

Findings

Weekend and holiday congestion causes simultaneous anomalies across bridges.

Uneven freight demand contributes to high anomaly scores at specific bridges.

Peak abnormal patterns occur during noon for US-Canada cars and in the afternoon for trucks.

Abstract

Border crossing delays cause problems like huge economics loss and heavy environmental pollutions. To understand more about the nature of border crossing delay, this study applies a dictionary-based compression algorithm to process the historical Niagara Frontier border wait times data. It can identify the abnormal spatial-temporal patterns for both passenger vehicles and trucks at three bridges connecting US and Canada. Furthermore, it provides a quantitate anomaly score to rank the wait times patterns across the three bridges for each vehicle type and each direction. By analyzing the top three most abnormal patterns, we find that there are at least two factors contributing the anomaly of the patterns. The weekends and holidays may cause unusual heave congestions at the three bridges at the same time, and the freight transportation demand may be uneven from Canada to the USA at Peace Bridge and Lewiston-Queenston Bridge, which may lead to a high anomaly score. By calculating the frequency of the top 5% abnormal patterns by hour of the day, the results show that for cars from the USA to Canada, the frequency of abnormal waiting time patterns is the highest during noon while for trucks in the same direction, it is the highest during the afternoon peak hours. For Canada to US direction, the frequency of abnormal border wait time patterns for both cars and trucks reaches to the peak during the afternoon. The analysis of abnormal spatial-temporal wait times patterns is promising to improve the border crossing management