Research Team: Stephen G. Ritchie (lead), Kanok Boriboonsomsin, Matt Barth, Andre Tok, and Yiqiao Li
UC Campus(es): UC Irvine, UC Riverside
Problem Statement: California has three major truck border crossings with Mexico, averaging 4,000 trucks in each direction daily. Over 90% of these border crossings are made by Mexican-domiciled motor carriers. The Advanced Clean Fleets (ACF) regulation mandates that these trucks transition to zero-emission vehicles (ZEVs), necessitating new fueling infrastructure, including battery charging and hydrogen stations. The transition to medium- and heavy-duty ZEVs is a significant concern at both state and federal levels. Currently, there's a lack of data on the environmental impact and activity of border-crossing trucks. Moreover, several AB 617 communities, selected by the California Air Resources Board (CARB) for its Community Air Protection Program, are heavily affected by truck emissions near the border crossings. The most impacted are the Calexico-El Centro-Heber Community near the Calexico Border Crossing and the International Border Community near the Otay Mesa Border Crossing. Mexican trucks entering California often have dual license plate registrations. However, automated license plate readers can effectively recognize only one of the two plates, making it impossible to determine which trucks have dual registrations from a single captured plate. This data gap hinders the understanding of fleet characteristics, such as age distribution and fleet size, which CARB needs to estimate the emissions profile of Mexican trucks in California. Also, Mexican-based trucks engage in drayage and long-haul movements through Southern California to Arizona and Nevada, but little is known about their activity distribution. This lack of data affects the ability to plan infrastructure investments for the transition of Mexican trucks to zero-emission technologies in the future.
Project Description: This project involves a synergistic multicampus effort to collect two complementary datasets that will elucidate heavy-duty truck border crossing characteristics and activity. UC Irvine will pilot a new license plate reader algorithm designed specifically to identify and capture the dual license plate registrations of Mexican trucks crossing into California. The system will be deployed to monitor the entry and exit of trucks at Otay Mesa and Calexico and will be integrated with other advanced technologies such LiDAR and inductive loop signatures. The integration of these technologies will allow UC Irvine to identify critical truck characteristics, such as the year, make and model of the vehicle. UC Riverside will recruit fleet operators on both sides of the California-Mexico border to participate in GPS truck data collection. The data collection will target trucks that frequently cross the border in short- and long-haul applications. UC Riverside researchers will then analyze the data for truck activity information, such as travel distance, travel time, and fuel consumption at both the trip- and the tour-level. Taken together, the data collected in this study will help CARB understand the impact of the ACF on border communities and highlight the grid infrastructure needs for the transition to ZEV trucks at the border.
Status: In Progress