1369805 - Web Portal Development and Site Usage Pattern Analysis for a Multi-state Truck Parking Information Management System (TPIMS)

Truck parking along the Mid-America Association of State Transportation Officials (MAASTO) region’s major freight corridors is complicated by an overall deficit in needed parking spaces, the location of available parking versus needed parking, delivery staging at major logistic centers or urban areas, and Hour-of-Service (HOS) compliance. Combined, these constraints lead to unauthorized or illegal parking. To improve freight operations safety and offer better parking information, the research team and MAASTO collaborated to build the multi-state Truck Parking Information Management System (TPIMS) and the data archival system (TPIMS-DAS). These systems provide real-time parking availability information and historical data accumulations to truck drivers, dispatchers, and traffic management centers (TMCs). Truck operators’ use of this information provides for better planning and decision-making and less wasted search time in securing truck parking.
This paper presents the TPIMS web portal and practical user management experiences in the development of the data management and provision system. The web portal provides truck parking data downloads, user account management, and performance measure report downloads. In particular, truck parking data contains comprehensive information such as available parking numbers, site location, and amenities. The user management tool on the web portal offers a tiered user data access privilege to meet the system administration needs of MAASTO members. Besides, the function of downloading the performance measure report is under-constructed. We also present findings from analyzing the parking utilization data archived by TPIMS-DAS over the last three years. These findings elucidate truck drivers’ work patterns, site utilization patterns in different time intervals, and other patterns, such as holiday trends and regional relationships. Information provided by this data set and this analysis can provide guidance for truck parking management and enhancements.