Factors Affecting International Border Crossing Delays Based Upon a Rich Bluetooth Dataset

Journal of Big Data Analytics in Transportation(2020)

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Abstract
The international border between Western New York and Southern Ontario presents a unique geographic and transportation challenge, with three key border crossing points servicing the demand of 10 million passenger trips and 1.5 million freight trips annually. The objectives of this were twofold. The first objective was to utilize a newly available real-time border crossing delay information, collected through a new blue-tooth reader system, to study the relationship between the presence of delays and the inclement weather factors, and to validate how certain temporal factors can affect these delays. The second objective was to research how these same factors can influence the magnitude of delays when they occur. To this end, both binary logit and regression based models were developed, validated and their results were mined for insights that that can, not only, lead to better prediction and management of delays at these crossings, but also can be applied to other international border crossings. Among the many insights derived from the study are that delays of passenger cars are 65% more likely to occur during the summer, 41% more likely on days surrounding holidays, and 19% more likely during the day. In terms of weather impacts, passenger cars were 24% more likely to experience delays when visibility was poor and 44% more likely when temperatures were below freezing. For trucks, delay was more likely when visibility was impaired, temperatures were below freezing, and when wind speeds were high.
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Key words
Bluetooth data, Border crossing delay, Discrete choice modeling, Inclement weather
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