Tag Archives: highway

New Tools to Optimize Truck Station Locations

The Minnesota Department of Transportation (MnDOT) has 137 truck stations across the state. These stations house and allow maintenance of MnDOT highway equipment as well as provide office and work space for highway maintenance staff. Within 20 years, 80 of these stations will need to be replaced as they reach the end of their effective life spans. Researchers developed a geographic information system based modeling tool to determine the most effective locations for truck stations in the state. Using data from many sources, a new research study has determined that MnDOT could rebuild 123 stations, relocate 24 on land available to MnDOT and combine two. MnDOT would save millions of dollars using the location optimization alternatives over the 50-year life cycle of a typical truck station.

What Was the Need?

MnDOT operates 137 truck stations, 18 headquarter sites for maintenance operations and over 50 areas for materials delivery. Truck stations are used to house and maintain large highway equipment, and to provide office and work space for highway maintenance staff. Some stations also store materials. 

The average life span of a truck station is 50 years. Within the next 20 years, 80 of MnDOT’s truck stations will need to be replaced. With costly capital replacement imminent, MnDOT has considered measures to optimize truck station locations within its eight state districts, including possibilities of reducing the size of some, increasing others, or combining the facilities of some state and local agencies into new partnerships. Determining the best effective locations for new truck stations could reduce costs for both state and local partners.

MnDOT needed a means of selecting and collecting the most appropriate data for an investigation into optimizing truck station locations. The agency also needed tools such as a computer model to analyze the data. These resources would allow MnDOT to determine the most time- and cost-effective locations for future truck stations. 

What Was Our Goal?

The initial objective of this research project was to collect data about truck service areas, including the quantity of highway equipment and materials capacity, and the materials storage capacity of facilities. This information combined with service route data would allow MnDOT to optimize truck station locations by determining whether facilities should be closed, resized, combined or relocated, and whether other materials storage locations would be necessary. An economic benefit–cost analysis would compare alternatives. 

A map of Minnesota indicates the location of each of MnDOT’s 137 truck stations with a blue square and of major highway routes connecting the stations, also shown in blue.
This project will determine the future of more than half of MnDOT’s 137 truck stations in the next two decades.

What Did We Do?

To determine how other departments of transportation (DOTs) and related agencies have addressed choosing the best locations for facilities, researchers conducted a literature review that included reports from six state DOTs and Australia, Transportation Research Board publications and other research papers. In addition, they consulted the standards developed by MnDOT’s Truck Station Standards Committee. 

Researchers also conducted surveys and interviews of both MnDOT and outside agency stakeholders. 

With many data sets collected for each truck station site, researchers used a geographic information system (GIS) platform to solve a location-allocation problem and a multivehicle routing problem for the truck stations. The problems incorporated such factors as amount of equipment, equipment capacity, storage capacity, material demand for road segments and other information. Estimated costs of operation for each location alternative were compared to present costs of each truck station. 

“Using real-world data, we built GIS models of maintenance operations to determine optimal truck station locations. With expected life spans of around 50 years, truck stations that are optimally located will reduce operating costs and save money for MnDOT and Minnesota taxpayers.” —William Holik, Assistant Research Engineer, Texas Transportation Institute

MnDOT’s Maple Grove Truck Station and Maintenance Center is a new 108,000-square-foot facility.
MnDOT’s truck stations range in size from Class 1 buildings of at least 25,000 square feet to smaller
Class 3 facilities with four or fewer overhead doors.
MnDOT’s Maple Grove Truck Station and Maintenance Center is a new 108,000-square-foot facility. MnDOT’s truck stations range in size from Class 1 buildings of at least 25,000 square feet to smaller Class 3 facilities with four or fewer overhead doors.

What Did We Learn?

The literature review showed that optimizations of facility locations may require a second level of sites, such as strategically placed materials storage depots. Some research also showed that both transportation and facility costs must be considered and that after a certain point, consolidation of stations could cost more as vehicles and staff were required to drive farther to reach them. 

Reports of state DOT location optimization efforts were instructive. Iowa DOT noted the need to consider the slow highway speeds of snowplows. This was a critical element for researchers to include in their optimization models as it determines route travel times. Vermont Agency of Transportation highlighted the use of satellite materials depots. Generally, state DOT efforts were confined to small regional issues, unlike MnDOT’s statewide scope.

In interviews with MnDOT and local agency stakeholders, researchers learned about partnerships that already existed between MnDOT and city and county agencies. These partnerships primarily included the sharing of truck stations and sometimes of materials. These partnerships were included in the optimization development.

Researchers optimized the truck station location using a GIS optimization model and separate cost analyses. They developed alternatives for each truck station individually. Each alternative was then analyzed to determine costs and savings over a 50-year life cycle. 

Finally, researchers determined which alternatives could be most effectively executed and their optimum order. They also developed an implementation plan for station relocation and replacement. This modeling was an iterative process: Each optimal location replaced the existing location and became the baseline against which the next station alternative was compared. The result was a comprehensive set of location possibilities for each MnDOT district with multiple alternatives for every truck station, including benefit–cost analyses. Researchers’ optimization solutions determined that 123 truck stations could be rebuilt on-site, 24 could be relocated on land available to MnDOT, and two could be combined. 

“We successfully analyzed all of our truck station and loading locations, determined which were good candidates for potential relocation or consolidation, and developed a data-driven plan of action to save millions of dollars.” —Christopher Moates, Planning Director, MnDOT Building Services

What’s Next?

MnDOT now has the information it needs to effectively implement cost-saving changes in future truck station planning and construction. The agency could use the researchers’ initial recommendations or further employ the GIS modeling tool to examine variations on the results of the project. 

This post pertains to Report 2019-10, “Optimizing Truck Station Locations for Maintenance Operations,” published February 2019. For more information, visit MnDOT’s Office of Research & Innovation project page.

Bus–Highway Connections Make Transit More Competitive With Driving

Researchers developed a method for associating travel times and travel costs with transit mobility. In an evaluation of bus–highway system interactions, investigators found that park-and-ride lots and managed lanes put suburban and walk-up urban transit options on equal footing. Bus–highway system interactions improve access to job locations and have improved transit access to job sites by about 20 percent compared to automobile access. When wage-related costs are included, the benefit of automobile use over transit use diminishes significantly.

What Was the Need?

Bus service in the Twin Cities relies on MnDOT-built park-and-ride (PNR) lots and managed lanes—lanes for buses on streets and highways, including high-occupancy lanes—to help transit users travel from the suburbs and urban locations to job, retail, service and entertainment sites. 

One measure of how a transit system of PNR lots and bus service works for users is job accessibility—the number of jobs that can be reached by a mode of transportation within a certain travel time period.

The type of lanes a bus uses impacts travel times via bus, and the differences in these travel times in turn impact the transit user’s ability to reach locations using walk-up transit service. The transit alternative to walk-up service is drive-to-transit service via PNR lots. The Twin Cities transit system intersects with over 100 PNR lots where transit users park their vehicles and take express and limited-stop services to business districts and job locations. 

Understanding the impact of managed lanes and PNR lots on transit effectiveness in terms of job access requires diving into transit and travel data; developing ways to measure accessibility for walk-up, drive-to-transit and automobile-only travel modes; and adjusting methods so the cost of travel and the time of travel can be reasonably compared between modes. 

A MnPASS lane on Interstate 394 at the General Mills Boulevard exit. The express lane is closest to the highway median, indicated by a white diamond-shaped marker on the pavement and separated from three other traffic lanes by a solid white line. A highway sign above the lane indicates the fees for lane use.
MnPASS lanes are managed lanes that offer buses quicker access to downtown.

What Was Our Goal?

MnDOT sought to evaluate how the bus and highway systems interact in terms of job accessibility. The research would consider how managed lanes and PNR lots affect job accessibility for walk-up and drive-to-transit users, compare these findings to automobile-only usage, and profile how well the transit system of the Twin Cities serves users in terms of cost to use and travel time. 

What Did We Do?

In the first stage of work, the research team focused on the managed lane network to determine how it contributes to walk-up transit accessibility. Investigators developed a computer program to modify transit schedule data to reflect how buses operate in different managed lane configurations and calculate walk-up access to jobs systemwide. 

In the second stage, the team developed a method for calculating accessibility via PNR use, and PNR accessibility in terms comparable to access via walk-up transit and automobile use. 

In the third stage, researchers developed a mixed-mode accessibility profile of the system. 

“The researchers did more than just measure mobility; they quantified access to employment in terms of travel time and travel cost, as well. Results put park-and-rides and suburban transit on equal footing with walk-up transit in urban environments.”

—Jim Henricksen, Traffic Forecaster, MnDOT Metro Traffic Forecasting and Analysis 

The research team incorporated a monetary dimension to travel time accessibility measures, associating costs of automobile use, parking fees, transit fare and travel time with travel modes in a value of time unit to compare accessibility between automotive and transit usage. 

What Did We Learn?

Study results showed that PNR lots and managed lanes offer greater access to job sites. The longer the trip to a job site, the more competitive transit becomes with driving for commuting to work. Bus–highway interactions via managed lanes and PNR lots improve transit job accessibility relative to automobile use by 3.8 percent in a 30-minute commute and by 19.1 percent in a 60-minute commute. For the 60-minute scenarios, transit accessibility from the suburbs to the central business district improves by 319,322 jobs for the average worker. 

For managed lanes, the greatest benefit is for suburban regions near express routes. On the I-94 corridor, where the greatest improvement by transit to accessibility is felt, every mile of MnPASS lanes offers an increase of 98 jobs accessible to average riders. 

With express bus service, travel times from PNR lots to destinations decrease by an average of 10.7 minutes for the system. Compared to walk-up transit travel, drive-to-transit from suburban areas offers accessibility values roughly three times greater than travel by walk-up transit, in part because time spent driving in suburbs gets users to more transit facilities than the same time spent walking.  

“We developed tools and methodologies, and applied them metrowide to bring new insights to the role of highway operations and planning on access to jobs through transit.”

—Andrew Owen, Director, Accessibility Observatory, University of Minnesota

Researchers found pockets in the Twin Cities where transit and PNR are more competitive with automotive travel per dollar of travel. These areas highlight urban locations where the transit network is the most robust and suburban areas where automobile travel times are long compared to express transit. When researchers applied wage value to time spent traveling, the benefit of driving rather than using PNR lots and transit dropped 89.6 percent. The relative value of transit may increase further if measures account for productivity on transit. 

What’s Next?

This research helps MnDOT plan future PNR and managed lane facilities to maximize benefit to transit services. Value of time models and comparisons offer a way to measure the relative value of transit to automobile use in accessing jobs. 

Future analysis may include long-term fixed costs associated with vehicle ownership and show further improvement in the comparative value of transit services to automobile use. Methods from this study may also be applied to other mixed-mode transit options, like biking, scooters or ride-sharing to transit access points.

This Technical Summary pertains to Report 2019-17, “Accessibility and Behavior Impacts of Bus-Highway System Interactions,” published April 2019. Visit the MnDOT research project page for more information.