Anderson, Paul

The Minnesota Department of Transportation (MnDOT) operates 137 truck stations and 18 headquarter sites. Replacement of 80 of these truck stations will be required within the next 20 years based on expected life cycles. There is a need to optimize the locations of truck stations on a statewide basis. Truck stations serve several functions for MnDOT maintenance operations. They exist to maintain the state's trunk highway system and provide a base of operation for many personnel and maintenance vehicles. Alternative locations were developed for each truck station and optimized individually. Truck station locations were optimized using a GIS optimization model to determine operational outputs. The outputs of each optimization model were used in a cost-analysis model to determine the 50-year life-cycle savings of each alternative. The cost analysis included factors for the number of events per year; number of cycles per event; wages; over time versus straight time; and vehicle operating costs. Implementation optimization was conducted to determine which alternatives should be implemented and in what order. The implementation modeling was an iterative process where each optimal location replaced the existing location and became the baseline scenario to which the next iteration was compared. Results indicated that 123 truck stations should be rebuilt on site; 24 should be relocated; and 2 should be combined. The total expected cost savings from implementing the optimal alternatives over a 50-year period is $23;362;000. The implementation plan recommends the order for truck station replacement for each district based on age; condition; and implementation priority.

This study uses accessibility as a performance measure to evaluate a matrix of future land use and network scenarios for planning purposes. Previous research has established the coevolution of transportation and land use, demonstrated the dependence of accessibility on both, and made the case for the use of accessibility measures as a planning tool. This study builds off of these findings by demonstrating the use of accessibility-based performance measures on the Twin Cities metropolitan area. This choice of performance measure also allows for transit and highway networks to be compared side-by-side. A zone-to-zone travel time matrix was computed using Stochastic User Equilibrium (SUE) assignment with travel time feedback to trip distribution. A database of schedules was used on the transit networks to assign transit routes. This travel time data was joined with the land use data from each scenario to obtain the employment, population, and labor accessibility from each traffic analysis zone (TAZ) within specified time ranges. Tables of person-weighed accessibility were computed for 20 minutes with zone population as the weight for employment accessibility and zone employment as the weight for population and labor accessibility. The person-weighted accessibility results were then used to evaluate the planning scenarios. The results show that centralized population and employment produce the highest accessibility across all networks.