This study explored how crowdsourced data can be used to better understand cross-border trips and travel patterns. Transportation officials can use these results to develop robust, data-driven policies regarding cross-border trips that, in turn, should make for more efficient, safe, and secure travel.
Quick and seamless passage across the U.S.-Mexico border has long been the Holy Grail for any commercial interest whose success depends on transportation efficiency. And for just as long, the safety inspection process at the border has represented the most persistent roadblock to that aspiration.
Currently, U.S. Customs and Border Protection (CBP) publishes the number of lanes open at the land ports of entry (LPOEs) on their website. This information is updated once every hour in most cases. However, it has been observed that in some cases this information is not updated for several hours, and in other cases, the information has proven unreliable.
In a reliable transportation system, motorists know with a high degree of certainty when they will arrive to their destination. Numerous factors directly affect reliability such as signal timing, work zones, incidents, unusually high demand, special events, weather, and the performance of complementary and competing modes). The purpose of a travel-time reliability monitoring system (TTRMS) is to collect travel-time data from various sources and to monitor travel-time reliability. Such a system allows transportation agencies to quantify travel-time reliability of their transportation networks and evaluate the impact of transportation network improvements on reliability. Moreover, freight carriers can make more informed decisions to minimize their travel times and possibly reducing transportation costs.