Log Movement in the Superior Region – Rate and Capacity Based Analysis of Modal Shares – Alger County

SPONSOR:  ALGER COUNTY

PI:  Pasi Lautala

Project Period:  01.01.18-12.31.19

Task 1: Log and non-log product movement data collection

This study will use actual log movement data (both by truck and by train) by the participating forest products companies, as well as train routes and schedules from CN (and potentially E&LS) as a backbone for the spatial simulation model of the region. The main activities of the task 1 include log and non-log movement data collection. For the non-log movements, the main emphasis is in collecting data on origin-destination (O-D) pairs, both from the forest products companies and from the results of NRTC study.

Task 2: Development of GIS network and yard/siding/mill constraints

We are expecting the GIS (Geographical Information System) maps of truck/rail movements to be the first main outputs from our study. These electronic maps developed based on the log movement data will show not only the actual locations and capacities of yards and sidings, but the transportation infrastructure of study area.

Task 3: Log /non-log movement data reduction/cleaning (as necessary) and conversion to a common format

In this task, we will clean up and convert the log movements to a common format. We will identify the log volumes through each O-D pair, including volumes through rail sidings/yards. Data collected in the previous tasks will be collated and organized with the development of commodity flows. Commodity flows will provide the movements of goods (log) in the study area and will be the basic dataset for average daily/monthly O-D matrix of log movements.

Task 4: Development of operational constraints (rail) and operational model

The studies on the freight mode choice, especially the competition between truck and rail are becoming critical to improve the efficiency of freight transportation system. In this task, we will investigate observed/unobserved factors influencing freight mode choice, including truck and rail. The average daily/monthly O-D matrix of log movements in the previous task will utilize to develop log freight mode choice model.

Task 5: Development of “non-log” product movement graphics, data tables and maps

In the same way as in Task 2 and 3 for a log product, this task identifies the “non-log” volume through each O-D pair and develops movement tables based on data collected in previous Task 1. The task includes generating volume matrices and GIS maps on the movements to identify opportunities.

Task 6: 1st simulation runs and development of results

In this task, we will develop the first simulation model that seeks to optimize log transportation considering the operational constraints of rail. This model will analyze log movements (from several companies/mills) by rail and truck, and look at where and how opportunities may be created to improve the business case for CN or a short line operator to provide cost effective service. One potential example is identifying locations where larger shipment sizes can be concentrated at once. Figure 1 presents the framework of the spatial model, using all processes from Tasks 1 to 5 as its main components.

Task 7: Industry/sponsor review of results

Progress report will be provided to get industry/sponsor reviews of the optimization and non-log movement results. This report will include the results of five tasks in the phase 1 (from Task 1 to Task 5) as well as the results derived from the first operational simulation model of task 6.

Task 8: 2nd simulation runs and analysis of additional logistics considerations.

We will run the second simulation and analyze on the car demand, effects on log trucks, opportunities for reduced peaking and consolidated rail yards. The comments/opinions from the first review will be reflected in the second simulation runs.

Task 9: Industry sponsor/review of results and final report

Pasi Lautala
Pasi Lautala
Kuilin Zhang
Kuilin Zhang

 

Log Movement in the Superior Region – Rate and Capacity Based Analysis of Modal Shares – MDOT

SPONSOR:  MICHIGAN DEPARTMENT OF TRANSPORTATION

PI:  Pasi Lautala

Project Period:  01.01.18-12.31.19

Dr. Pasi Lautala will provide coordination of the project and data collection from industry stakeholders.

Dr. Kuilin Zhang will lead the operational constraint and model development for log transportation model. He will also lead the analytical tasks related to the model, supported by the graduate research assistants.

Pasi Lautala
Pasi Lautala
Kuilin Zhang
Kuilin Zhang

Implementation of Online Training Modules to Rail Learning System

SPONSOR: FEDERAL RAILROAD ADMINISTRATION (FRA)

PI:  Pasi Lautala

The proposed activities will enable the FRA’s Office of Safety and Office of R&D to utilize the RLS as a platform for internal FRA training offered to both new and current employees. Offering training online will increase flexibility in obtaining the necessary skills required to effectively perform essential job functions, and save on travel expenses currently incurred for this type of training.  In addition, the proposal increases the amount of openly available education modules by incorporating the Railroading 101 modules developed by the FRA, as well as newly recorded versions of the 2016 Railway Engineering Education Symposium (REES) modules. The proposal will also provide technical support in using the modules and continuing monitoring and support of the system throughout the project duration. Continue reading “Implementation of Online Training Modules to Rail Learning System”

Log Movement in the Superior Region – Rate and Capacity Based Analysis of Modal Shares

SPONSOR:  MICHIGAN DEPARTMENT OF AGRICULTURE AND RURAL DEVELOPMENT (MDARD)

PI:  Pasi Lautala

Since the purchase of the Wisconsin Central Rail system by Canadian National (CN) operations on the small branch lines throughout the Upper Peninsula of Michigan and Northern Wisconsin have seen reduced business. Starting in 2012, the Northwoods Rail Transit Commission (NRTC), formed by the economic development in the 13 counties of Northern Wisconsin as well as membership of nine of the UP’s 15 counties, has been leading an effort to not only put a spotlight on the decline, but seek solutions in collaboration with the CN. However, the effort has only been successful at keeping a spotlight on the issue.

One of the industries that have been particularly hard hit is the forest products industry. Moving logs by rail from aggregation points to the mills has been a very cost effective and safer method of moving raw material. Unfortunately, most of these movements start or end on branch lines and move below average distances to reach the mills. This doesn’t match well with the current business model for large railroads that is based on moving large blocks of cars (generally anywhere from 20-100) for fairly long distances (500+ miles). As a result, the prices CN considers profitable have been pushing logs off their rails and onto trucks.

Recent discussions by the Michigan Forest Products Council (MFPC), an industry group that includes representatives of the largest mills in the UP and Northern Wisconsin focused on the need to develop a strategy to either convince CN that a business case existed for them to get back into moving logs in the region or make a case for allowing a short line operator to take over service on the branch lines. The NRTC, who participated in the MFPC discussions, has also endorsed this strategy. Two specific steps to advance the strategy are an effort funded by the Wisconsin Department of Transportation to update a previous rail study and a proposal by Michigan Technological University (MTU) to conduct a detailed analysis of the log movements to determine how a better business case can built by improving the operational movements related to where, when and how logs enter the rail system.

MTU’s study will use actual train movement data from CN and log movements data provided by the members of the Michigan Forest Products Council including a number of mills in Wisconsin, to create a spatial simulation model of the region. This model will analyze log movements (from several companies/mills) by rail and truck and look at where and how opportunities may be created to improve the business case for CN or a short line operator to provide cost effective service. One potential example is identifying locations where larger shipment sizes can be concentrated at once.

Pasi Lautala
Pasi Lautala

Evaluating the Use of Operational Management Techniques for Capacity Improvements on Shared-Use Rail Corridors

SPONSOR:  NATIONAL CENTER FOR FREIGHT AND INFRASTRUCTURE RESEARCH AND EDUCATION

PI:  Pasi Lautala

The majority of intercity passenger and commuter rail services in the United States (U.S.) operate on the shared-use corridors with freight rail services. These types of operations tend to be challenging for efficient capacity utilization and reliability due to the high heterogeneity of trains (diversity of trains operations). In addition, the projected growth in demand for rail transportation is likely to exacerbate the situation, making efficient use of capacity a necessity for freight and passenger traffic alike. There are two main approaches to improve the capacity levels, either by applying new capital investment or by improving operational characteristics and parameters of the rail services (such as improving the trains timetables). To date, U.S. has concentrated more on the first approach while the second approach is commonly used in European practices. It would be beneficial to evaluate the main challenges and advantages of using operational management techniques to improve the capacity utilization along shared use corridors in the U.S.

This study will investigate the use of operations management techniques on selected shared use corridors (Kalamazoo – Dearborn section of the Michigan HSR corridor and Baltimore-Washington section of the Northeast Corridor). The study will be conducted by applying the European simulation packages (Railsys and/or Opentrack) as well as Rail Traffic Controller (RTC), a common simulation package in the U.S., to evaluate different traffic scenarios and operational variables at selected locations. The use of multiple simulation tools will also allow application of a hybrid approach on the operational scenarios that will be developed in collaboration with DOTs and Amtrak.

Pasi Lautala
Pasi Lautala

National University Rail Center Tier 1

SPONSOR:  MICHIGAN DEPARTMENT OF TRANSPORTATION

PI:  Pasi Lautala

The primary objective of the NU Rail Center is to improve and expand rail education, research, workforce development, and technology transfer in the US. Michigan Tech, in collaboration with its academic, industry and state partners, will work to identify important rail knowledge areas for inclusion in these activities. Under the center, the Michigan Tech team is expanding its multidisciplinary research activities from the previous NU Rail award in various areas, such as rural freight rail and multimodal transportation improvements, human factors and rail safety, infrastructure evaluation and assessment, high performance materials for railroad infrastructure preservation and renewal, and improved materials for the rail industry. Michigan Tech’s Rail Transportation Program (RTP) director also serves as the Associate Director of Education for the consortium. Educational activities are a high priority with focus on expansion of undergraduate level funded projects and internships among other activities. On technology transfer, the main objective is to continue the development of Michigan Rail Conference.

Pasi Lautala
Pasi Lautala

Study of Greenhouse Gas Savings Associated with Congestion Reduction Using Multi-Modal Optimization of Timber Shipments in the North Central United States

Sponsor: US Department of Transportation

PI: Pasi Lautala

This study examined industry led models for the optimization of timber shipments in the North Central United States (norther third of Wisconsin, Minnesota, and the Upper Peninsula of Michigan). The research team analyzed optimization models of the delivery of logs to the wood products industry in the region. The research team investigated a multi-modal (rail/truck), surface transportation solution set and performed a sensitivity analysis based on changing energy costs. The team evaluated the potential effects on air emissions before and after the virtual routing optimization. The team also explored options for establishing a rail served super yard in the region to reduce consolidate logs with the object of reducing empty truck miles and increasing rail ton-miles.

A copy of this report can be found on the University of Wisconsin – Superior website.

Pasi Lautala
Pasi Lautala

National University Rail (NURail) Center

Sponsor: University of Illinois Urbana Champaign

PI: Pasi Lautala

In 2012, the seven university consortium, including Michigan Tech, was awarded the first National University Rail Transportation Center (NURail) by the USDOT Research and Innovative Technology Administration (RITA). The University of lllinois at Urbana-Champaign (UIUC) leads the consortium.

The primary objective of the NURail Center is to improve and expand rail education, research, workforce development, and technology transfer in the U.S.

Pasi Lautala
Pasi Lautala
Timothy Havens
Timothy Havens
Paul G. Sanders
Paul G. Sanders
Myounghoon Jeon
Myounghoon Jeon

Beyond Traffic Innovation Center (BTIC)

SPONSOR:  US DEPARTMENT OF TRANSPORTATION (USDOT)

PI:  Pasi Lautala

The close partnerships between diverse entities on MTU’s campus allow Michigan Tech to serve the transportation field across many areas. Innovations and research conducted under entities such as the Michigan Tech Research Institute, Advanced Power Systems Research Center, and numerous laboratories can be integrated into our academic programs by departments, but also disseminated to practitioners and public stakeholders through our Center for Technology and Training (CTT), Tribal Technical Assistance Program (TTAP) and Center for Science and Environmental Outreach (CSEO).

Michigan Tech has a strong and versatile academic program in transportation. Our Department of Civil and Environmental Engineering offers BS, MS, and PhD concentrations in transportation. In addition, we house one of the few Rail Transportation Programs in the nation and perhaps the only Minor in Rail Transportation available today. There also are certificate programs in Hybrid Electric Drive Vehicle Engineering, Advanced Electric Power Engineering and a graduate certificate in Automotive Systems, plus numerous opportunities for undergraduate and graduate level transportation research in various disciplines. These include our innovative Enterprise Programs for undergraduate research in areas, such as alternative energy, hybrid electric vehicles and wireless communications.

In addition to our academic programs, we offer professional training and outreach in transportation topics through a variety of centers. CTT is a transportation training and outreach center focusing on practitioner training, technical assistance, and best practices that enhance business and technical practices for state and local agencies. Their training typically reaches 5,000 participants annually with over 24,000 contact hours. TTAP offers similar services to American Indian governments and communities in the 31 states bordering and east of the Mississippi River (Federal Lands Eastern Region), reaching 1,100 annual participants and 4,200 contact hours. Finally, the Michigan Tech Mobile Lab is a fully outfitted mobile laboratory that partners with government, industry, and nonprofit organizations to deliver HEV (hybrid-electric vehicle) education, outreach, and research across the nation.

Michigan Tech has been instrumental in organizing regional and national conferences and workshops, such as the annual Michigan Rail Conference founded by Michigan Tech in collaboration with the Michigan Department of Transportation (MDOT) and the National Tribal Transportation Conference. Michigan Tech also collaborated in a workshop funded by FHWA with participants from state DOTs like Caltrans, city government, European representatives, and industry to “Address Infrastructure Life Cycle Inventory Data Needs: Supporting Sustainable Decision-Making for Civil Infrastructure Using EPDs.” Dr. John Harvey from the University of California Pavement Research Consortium (UCPRC) was a close collaborator on the effort. In 2016, we also initiated the Exploring Next Generation IN-vehicle INterfaces Consortium (ENGIN) and related speaker series.

Michigan Tech educates and encourages K-12 students to advance in the transportation field through several youth events and summer programs. These include the National Summer Transportation Institute (NSTI), Rail and Intermodal Summer Youth Program (SYP), Women in Automotive Engineering, and Human Factors Engineering programs. We also host the annual Clean Snowmobile Challenge at Michigan Tech’s Keweenaw Research Center.

Michigan Tech is engaged in national and regional decision making through participation in and leadership of committees. Some examples include the Chairmanship of the TRB AR040 Freight Rail Committee and involvement in AASHTO Subcommittee on Materials and FHWA Sustainable Pavements Technical Working Group. Michigan Tech is also represented in the seven-member State of Michigan Commission for Supply Chain and Logistics Collaboration, and our faculty/staff has obtained national and regional awards, such as the Wootan Award received by Timothy Colling and the 2015 WisDOT Tribal Excellence Award from the Wisconsin Department of Transportation received by John Velat.

While not located in one of the 11 megaregions identified in the Beyond Traffic 2045, our location in rural Michigan makes us ideal in addressing trends and challenges faced by rural transportation, and we have worked closely with Michigan Department of Transportation and local governments in these issues. However, Michigan Tech’s leadership is not restricted to rural aspects. Many of our activities have broader impacts, such as the RoadSoft asset management software developed at Michigan Tech and used in the Michigan and several others states by rural and urban counties alike.

Michigan Tech is directly involved in addressing several trends/challenges identified in the Beyond Traffic document. We have conducted numerous studies related to the challenges faced in freight transportation in our region, conducted Life-Cycle Analysis (LCA) to evaluate environmental impacts of different transportation materials and related solutions, are actively involved in emissions research for various engines, are one of the leaders in advancing open source 3D printing, have on-going projects related to V2V and automated vehicle research, and have had various projects related to alternative energies for transportation, especially in the biomass supply chains for biofuel development. Michigan Tech researchers and educators accomplish this innovative work through collaborative thinking and working across departments and disciplines, which allows us to tackle large-scale projects that require a diverse skill set.

 

Pasi Lautala
Pasi Lautala

Driver Behavior at Highway-Rail Grade Crossing Using NDS and Driving Simulation

SPONSOR:  FEDERAL RAILROAD ADMINISTRATION (FRA)

PI:  Pasi Lautala 

Project Period:  09.09.16-09.18.17

According to the USDOT Federal Railroad Administration, highway-rail grade crossing and trespasser fatalities still account for 96 percent of all rail-related deaths.  A review of accident causes reveals that one of the main accident factors is human driving behavior.

One of the potential approaches to improve drivers’ behavior at crossings is to systematically examine their actions and use the outcomes to develop alternative methods or approaches to decrease the probability of missing or ignoring warnings.  The Naturalistic Driving Study (NDS) approach, using in-vehicle video and other sensors to directly observe drivers during normal driving activities, is a technique that shows promise toward improved understanding of driver actions in the crossings.

This two-year project is divided into two phases with an overall objective to investigate driver behavior at highway-rail grade crossings using two distinct, but complimentary techniques.  Phase I will use data collected under the Strategic Highway Research Program (SHRP) Naturalistic Driving Study to look at how normal drivers react at crossings in every day driving situations.  Phase II will use the understanding developed in the first phase to create scenarios that resemble environments similar to those found in the NDS for use in our driver simulator environment.  The research will look for two basic results.  First, we will develop and use the organized NDS crossing database to examine behavioral trends at the crossings. Second, we will compare driver behavior in the simulator with that found in the NDS data to determine the level of correlation between the two environments.   Our hypothesis is that a strong correlation would allow us to outline how to use the simulator environment in the future to predict driver response to a variety of crossing parameters.

Pasi Lautala
Pasi Lautala
Myounghoon Jeon
Myounghoon Jeon
Dave Nelson
Dave Nelson