Research in Progress
2015-2016 Projects
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Driving Simulator Based Interactive Experiments: Understanding Driver Behavior, Cognition and Technology Uptake under Information and Communication Technologies 143
Research Summary
Phase II will involve conducting the experiments and data analysis. About 500 participants will spend up to 3 hours each on the driving simulator. In addition to providing information with different characteristics (amount, one or more sources, content, etc.), a range of relevant attributes will be analyzed (such as familiarity with network, trip purpose, incident situations, etc.). Each participant will be tested under 4-5 different scenarios. In addition, bio sensors such as eye tracker and Electroencephalography (EEG) will be used to understand driver cognitive workload and visual information processing for real-time travel/traffic information provision and the underlying decision-making physiological characteristics related to understanding the benefits of the real-time information provided. The driving simulator experiments at Purdue will be supplemented through experiments at the full-sized advanced simulator at Tongji University in China, which provides 8 degrees of movement and 250 horizontal degrees of view. Further, the expertise of the study's Tongji partners in vehicle-to-vehicle (V2V) communications and vehicle-to-infrastructure (V2I) interactions will be leveraged to address safety aspects involved in the real-time information provision context. The use of the same software suite at both universities will synergistically aid in the analysis of the data.
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Guaranteed LiDAR-aided Multi-object Tracking at Road Intersections 145
RIP Database link: https://rip.trb.org/view/2015/P/1357862
Research Summary
A Traffic Scanner (TScan) is being developed with the joint pool of NEXTRANS's and INDOT/JTRP's funds to enable collecting accurate microscopic traffic data at road intersections with an innovative use of Light Detection and Ranging (LiDAR) 3D laser scanning technology. LiDAR sensing promises to overcome certain limitations of video cameras because it yields 3D point clouds that have a one-one correspondence with the environment being sensed. The current effort is focused on developing elements of the LiDAR's tracking algorithm with self-calibration and adjustment for the sensor's motion.
The results of the current project show that LiDAR calibration and tracking with clear statistical guarantees are possible. The guarantees are functions of the characteristics of the sensor itself: its resolution, and precision. We expect that our sensing system will work in a variety of environments and will produce results of a uniform quality. The proposed second phase will be focused on developing algorithms for object identification, classification, and tracking.
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A Novel Decision-Support Tool to Develop Link-Driving Schedules for MOVES 153
RIP Database: https://rip.trb.org/view/2015/P/1358299
Research SummaryEPA-MOVES is a modal-based emissions estimator that accounts for vehicle operating modes defined by factors like speed, acceleration, road grade, curvature, and so on. MOVES has the ability to include alternative types of fuel and different type of vehicles as well. Analyses at different scales including regional, state, and project level (e.g., small road network at county level) can be done with MOVES. Integration of MOVES with a microscopic traffic simulator can be outlined as an input-output process. The second-by-second vehicular activities from traffic simulation serves as input for MOVES and the emissions inventory for a transportation network can be estimated. The input from traffic simulators can be any of the following formats: (a) average speeds for the links in the network, (b) Link Driving Schedule (LDS) for each link of the network. LDS is time dependent speed profile of a link (generally done for a representative vehicle typically by sampling), and (c) Operating mode distribution of vehicles on the link. While average speed is commonly used in practice, operating mode distribution and LDS can take the advantages regarding vehicular activity data and dynamic capability of MOVES to report time dependent emissions.
In this project, we propose a novel decision-support tool to find the representative vehicle trajectories and accordingly the LDS for links on transportation networks. The technique will use the similarity measure such as the dynamic time warping distance and/or longest-common-subsequence measures in clustering that are more appropriate for curve alignment as compared with the Euclidean distances and its variants.
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Estimation of Stochastic Network Vehicular Origin-Destination Demands Using Multi-Sensor Information Fusion Approaches - Phase II 158
RIP Database link: https://rip.trb.org/view/2015/P/1358298
Research Summary
The main objective of this Phase II study is to estimate a set of stochastic network O-D demands using a multi-sensor information fusion method. Taking advantage of multi-sensor information, the information fusion model to be developed will formulate the O-D demand estimation problem as a stochastic mathematical program using the concept of fuzzy logic to track network uncertainties. The study will comprehensively explore the issues of network uncertainties and multi-sensor information on the estimation of network O-D demands. The corresponding solution algorithms will be developed and tested using a real road network in Taiwan to generate insights and policy implications for the developed model framework. Finally, sensitivity analysis on the budget constraint and network topology issues will be systematically evaluated for a cost-effective implementation in the field.
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Information and Transportation choice, Long- and Short-Term, that Link Sustainability and Livability - Phase II 159
RIP Database link: https://rip.trb.org/view/2015/P/1358297
Research Summary
Travelers' decisions regarding transportation can be conceived of along a long-term to short-term spectrum. Decisions of residential locations, vehicle ownership, and work destination are usually established over the scale of years. Over a shorter time period of perhaps months, people make decisions regarding parking purchase and non-work destinations. Despite this broad range of time frames, current strategies for the dissemination of transportation information concentrate at the short-term end of the spectrum.
To foster more sustainable transportation choice behavior, an effective information strategy should be ideally designed to work along the full time-scale range, particularly since longer-term decisions frequently constrain the shorter-term options. However, the insights on the sensitivity of choices at varying time scales to information interventions, or the impact of long-term choices on those made over the shorter terms are limited.
This project will develop practical approaches to the delivery of accessibility related information and new decision-making models in the full time-scale range that are informed by multiple disciplines including cognitive science, behavioral economics, marketing, transportation, and urban planning. It will design information interventions intended for the full range of transportation-relevant decisions and test their impacts on people moving to the Greater Lafayette area, Indiana. The research is designed to test the sensitivity of: (i) long-term decision of residential location choice to information, and (ii) the sensitivity of short-term travel characteristics to long-term residential location choice.
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Effects of Heterogeneous Information Characteristics and Sources on Evacuation Behavior 160
RIP Database link: https://rip.trb.org/view/2015/P/1358366
Research SummaryUnder disasters and emergency situations, a successful implementation of the evacuation plans depends on the provision of reliable information in a timely manner, especially so in the context of short- and no-notice evacuation. With the increasing usage of portable personal devices (e.g., smart phones) as sources of information dissemination and acquisition, there is a need to understand the role of heterogeneity of information characteristics across different dissemination sources on the travel evacuation behavior of individuals
This study proposes a systematic framework to address the potential effects of heterogeneity in information in a travel evacuation context. We will seek to understand the characteristics of information propagation from different dissemination sources and the impact of heterogeneous information on the evacuee behavior in terms of travel-related decision-making. The study will also analyze how heterogeneous decisions affect the system performance under evacuation. It will aid multiple nodal agencies associated with disaster response in developing evacuation plans, and coordinate information dissemination through multiple sources by factoring the potential for asymmetric (non-uniform) distribution of information across individuals. Thereby, the proposed study seeks to understand the role and significance of emerging social media in evacuation situations.
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Intermodal Infrastructure Investment Decisions and Linkage to Economic Competitiveness 161
RIP Database link: https://rip.trb.org/view/2015/P/1358365
Research Summary
Individual firm supply chains metrics of competitiveness include time, cost (as measured by transport cost, in transit and buffer inventory) and environmental impact. These factors impact their choice of competitive global logistics paths. In such contexts, stable transit times with larger capacities may, in cases, be more competitive than unpredictable mode choices with random delays. Several product manufacturers and retailers have committed to tracking their environmental impact (green scorecards), with sourcing preference given to suppliers who offer competitive prices while improving their environmental performance.
Thus, multimodal/intermodal facilities that consciously consider their impact on firms' choices can use their impacts on time, cost and the environment to serve as competitive alternatives for firms. In this study, we propose a firm level and an aggregate level analysis to understand the economics of emerging logistics opportunities facilitated by multimodal or intermodal terminals. By considering new multimodal or intermodal offerings as being required to compete with existing choices by firms, plans for such facilities will be more realistic because they would have anticipated market impact. Thereby, the proposed research would provide a mechanism to link intermodal infrastructure investment decisions to economic competitiveness.
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Accessibility-Based Evaluation of Transportation and Land-Use Planning: From Laboratory to Practice 140
RIP Database link: coming soon
Research Summary
Accessibility measurement has been integral to transportation and land-use scholarship since the 1950s, and since the 1970s researchers have argued that it forms the theoretically correct basis for transportation and land-use evaluation. Accessibility-measurement metrics are well-defined and can be based on data readily available to transportation planners. Yet accessibility-based evaluation has largely failed to make the leap from laboratory to practice, and has nowhere displaced traditional mobility-based evaluation. The proposed project seeks to understand barriers to the greater use of accessibility evaluation in practice; to develop qualitative, quantitative, and graphical approaches to overcoming those barriers; and to work cooperatively with practitioners on assessment of accessibility-based evaluation.
The project will be informed by lessons derived from a previous multi-year project at the University of Michigan that measured regional accessibility among the top 50 metropolitan regions of the United States, and will proceed in four interrelated stages: (i) Research political and technical barriers to the adoption of accessibility-based evaluation, (ii) Develop case studies of accessibility- and mobility-based evaluation, (iii) Develop approaches to incorporating accessibility-based evaluation, and (iv) Collaborate with practitioners and decision-makers on assessment of accessibility-based evaluation.
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New Hybrid Multi-modal Spatial Prototypes Towards Resource and Social Sustainability 163
RIP Database link: https://rip.trb.org/view/2015/P/1358863
Research Summary
This work aims to address a key research gap: There has been extensive scholarship devoted to identifying, classifying and quantifying the conditions by which existing transportation infrastructures and system operation produce uneven access to services and needs relative to socioeconomic status and its spatialization. However, there has been little design-research undertaken to examine ways in which intervention within existing transportation infrastructures might strategically alter and / or improve the conditions of uneven access. Based on interviews with thought leaders globally and in the U.S., recent Rockefeller Foundation-supported work by SMART (Zielinski, Anand) has offered preliminary observations relating to how transport needs and conditions of the underserved (low income, growing seniors population, disabled) could be, and are being, more widely addressed by emerging multi-modal systems enhanced by new service models and information technologies. To date these emerging or "disruptive" systems, regionally customized and generally implemented through public-private innovation, have been associated with the shifting needs, preferences, and cultures of the growing urban population at all income levels, including specifically the millennial demographic. However it now appears these disruptive systems-based solutions may have wider application across a broader demographic including the vulnerable and undeserved. Yet very little concerted physical design research and prototyping has been carried out to a) confirm these initial observations, b) support decision makers and practitioners and c) inform policy.
The research question that this work will aim to address is: "what may be the ways and processes by which the physical and spatial assets of transportation systems themselves might be retrofitted, coupled, or hybridized with other systems not only to address the National Transportation Goals of Livable Communities, Environmental Sustainability and Economic Competitiveness, but also to positively impact Quality of Life for all users".
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Synthesis of Best Practices for Agency-wide Freight Data and Information Management
RIP Database link: https://rip.trb.org/view/2015/P/1359038
Research Summary
While states have data and information systems for managing spatially related data to support decision making, those systems are not populated to support freight-related planning and operations decisions. For example, at least one agency has constructed roundabouts on designated truck routes and then endured the extreme dismay of trucking companies. To address coordination issues, some agencies establish new offices for freight but the comprehensive scope of business activities and issues do not fit neatly into the organizational structures of typical transportation agencies. Another approach is to enhance access to the agency-wide data and information necessary to support development of transportation infrastructure that balances the needs of both passenger and freight users.
This research will build on the investigators' expertise in asset management and relationships with the DOTs in the Mid America Freight Coalition. This project will review existing data sources, identify new data sources and create a catalog of business processes, data and information items necessary to support consistency, and quality in decision making and asset management of freight infrastructure and operations. The results will support implementation of the MAP-21 requirements for freight performance.This project deals with strategies for managing and integrating spatially related freight transportation data both intra- and inter-agency from the perspective of a state transportation agency. The scope of data is freight data, defined as data about freight for making decisions regarding the planning, design, construction, operation, and maintenance of transportation infrastructure. Some of the freight data items include truck routes, ESAL charts, truck traffic, variable speed limits, intermodal connectors, spring-thaw restrictions, bridge clearances, posted bridges, steep grades, rail crossings, port entries, foreign trade zones, longer combination vehicles rules, OS/OW routes, weight stations, and road uses agreements.
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Region V Transportation Workforce Assessment and Summit
RIP Database link: https://rip.trb.org/view/2015/P/1359175
Research Summary
Nationwide, as the Baby Boom generation moves to retirement, the transportation workforce will lose many well-trained and experienced people. Furthermore the knowledge, skills, and abilities needed in the remaining and new transportation workers will be much broader, reflecting changes in technologies, processes and the expectations of the public. At the same time these challenges are unfolding, the demographics of our region and the nation are also undergoing change. The future workforce will be made up more heavily of members of minority groups that traditionally have had much lower rates of educational attainment and of non-traditional workers seeking second careers or more flexible working environments. In April of 2012, a number of national agencies and groups came together to hold a National Transportation Workforce Summit. The product of the summit was fourteen specific recommendations for actions on the part of educators, transportation agencies and employers. Those recommendations can be found in the National Transportation Workforce Summit Reportout.
The purpose of this project is to lay the groundwork for addressing the transportation workforce challenges in the region either by taking steps toward implementing the national recommendations regionally or by identifying the challenges and developing the solutions that may be unique to this region.
This project involves two phases: Phase I is a regional assessment of the transportation workforce demand and supply. Phase II is a summit of transportation workforce stakeholders within the region.
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Measures for Environmental Sustainability Outcomes of Transportation Agencies
RIP Database link: https://rip.trb.org/view/2015/P/1359176
Research Summary
In recent years, the US Department of Transportation has identified less traditional goals for transportation performance centered on environmental sustainability. This project will assess the adoption of non-traditional measures of transportation success that the federal government has identified as a strategic goal. To what extent is the goal of environmental sustainability measured at the federal level? Has the federal government provided reporting requirements to the states in regards to environmental sustainability? How is it measured? Are there some measures that could provide models for states to follow? What are the sources of resistance to these alternative measures of transportation?
The USDOT is an anticipated user of the results from this proposed project. In recent years, the USDOT has identified less traditional measures of transportation performance centered on livable communities and environmental sustainability. To what extent are these goals measured at the state level? How are they measured? Are there some measures that could provide models for states to follow? What are the sources of resistance to these alternative measures of transportation? Answers to these questions would inform the USDOT as to the success of its efforts in shifting state transportation departments to direct attention to its more novel measures of transportation performance.
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Workforce Needs Assessment for Mid-America's Marine Highways
RIP Database link: https://rip.trb.org/view/2015/P/1373251
Research Summary
The objective of this project is to assess the workforce development needs to build and operate container on vessel, and expanded traditional service on the Marine Highways in the Upper Midwest Region. The scope includes workers to build and operate vessels and ports on the designated marine highways M35, M55 and M70. The analysis will build upon previous work to propose and assess the economic impacts of the Marine Highways. The project will determine a baseline set of occupations. For each occupation, we will determine the baseline employment levels, training requirements and resources for incumbent workers, skill requirements, and wages. The project will estimate workforce needs for three future scenarios for increased capacity usage on the marine highways of: 33%, 50% and 100%. The project will identify the need for workforce efforts to build career awareness, develop training and education programs, and industry participation. The projects incorporates workforce data, industry interviews and sector specific surveys, along with geospatial and industry trend analysis to provide a full look at workforce needs for the marine freight sector. The research findings are then presented as a strategic development agenda that supports the workforce needs and trajectory of the marine freight industry today and into the future.
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Bayesian Updating Procedure for Prediction of Corrosion-Induced Cracking in Prestressed Concrete Bridges using Visual Inspection Data
RIP Database link: https://rip.trb.org/view/2015/P/1373280
Research Summary
Bridges are key components of transportation infrastructure systems that are exposed to various uncertain environmental stressors and loading conditions. The proper functionality of these structures is critical for local and regional economic prosperity along with the assurance of public safety. Aging and deterioration are primary concerns regarding the performance bridges degrading to deficient or obsolete states. According to a recent ASCE infrastructure report (ASCE 2013b), it is estimated that every day more than 200 million trips in 102 largest metropolitan regions in the US are taken across deficient bridges. As the demands on public funds increase, it is becoming even more critical to determine and implement optimal decisions aimed at maintaining and improving public infrastructure. Bridge deck deterioration forecasts provide the necessary inputs in support of such decisions. More accurate forecasts are expected to lead to more effective decision. The ability to use bridge inspection data to update the parameters of bridge deck deterioration models on an ongoing basis following each inspection season will lead to more accurate forecasts. The enhanced accuracy of predictions of future states of bridges will lead to more effective maintenance decisions that results in increased reliability of assets, enhanced ride comfort, and less interruptions and time delays for passing traffic. Moreover, the quantification of the value of such updates with respect to the state-of-the practice will allow researchers and state agencies to better allocate the research efforts and investments vis-à-vis the various aspects of deterioration modeling and parameter estimation efforts.
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Advancing Traffic Flow Theory Using Empirical Microscopic Data
RIP Database link: https://rip.trb.org/view/2015/P/1373296
Research Summary
Most traffic flow theory is based on macroscopic data collected from conventional vehicle detectors (e.g., 30 sec average speed, flow, and occupancy). Traffic flow theory has come to a point where these low-resolution data are now limiting our insight into important phenomena such as bottleneck formation and operation. Recent theoretical work has provided a new understanding of bottleneck processes using microscopic vehicle dynamics (e.g., individual vehicle passages and trajectories). These works indicate that the conventional macroscopic data are too coarse to observe the critical dynamics of the bottleneck process. The coarse granularity of conventional data has led to several misconceptions. For example, based on macroscopic data the conventional understanding of the capacity drop phenomena finds that bottleneck throughput seemingly drops below capacity once the bottleneck becomes active. Yet the recent theoretical microscopic work finds that this so-called "capacity drop" appears to be due to an unsustainable transient increase in flow AFTER the bottleneck has become active, but before the delays are apparent in the macroscopic data. Then as activation progresses, the throughput finally drops back down to the true capacity and the conventional macroscopic studies erroneously take this instant as the onset of bottleneck activation, thus, also erroneously taking the unsustainable, supersaturated flows prior to the drop as capacity. Meanwhile, far downstream of the assumed bottleneck the throughput never exceeds the true capacity, clearly indicating that the transient surge is above capacity and is not sustainable. This proposal seeks to use high resolution traffic data collected from individual vehicle passages from loop detectors and/or instrumented probe vehicles to empirically support the microscopic theories and lead to further traffic flow theory developments based on the new insights from the high resolution data.
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A study of the Usage Potential of a Proposed Expanded Commuter Rail Station at Chicago State University
RIP Database link: https://rip.trb.org/view/2013/P/1373356
Research Summary
Chicago State University, through the Fred Blum Neighborhood Assistance Center, will perform outreach for the NEXTRANS Center to community organizations needing assistance with transportation and accessibility related GIS projects on the South Side of Chicago and southern suburbs. The specific research project CSU will work on will be a study of the potential effects of the expansion of a commuter rail station that is adjacent to campus. The station is currently underutilized. Trains only stop at the station once every one to two hours. If expanded, the station would become an express stop, with much more frequent service and would better link Chicago State to Chicago’s growing southern suburbs. The station also currently has security issues. A new station, located in closer proximity to the center of campus, with adequate security, is likely to increase public transportation usage to and from campus, and hypothetically could boost enrollment. CSU is currently working to gain funding for the station from the USDOT. The CSU NEXTRANS team would work with the CSU administrative group working on this issue to perform a GIS analysis of current and potential CSU students, to model commute times by car and public transportation currently and with the opening of the station. In addition, the CSU RA team will work to develop a survey of current students focusing on how the building of the station might affect their transportation to and from CSU, as well as whether the new station might affect the enrollment decisions of potential students in areas served by the rail line.
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Tracking bicyclists route choices, case study: The Ohio State University
RIP Database link: https://rip.trb.org/view/2015/P/1373604
Research Summary
This study will generate data on bicycling patterns to, from and on a large university campus as well as data on bicyclists’ perceptions and preferences. The results will help transportation planners make informed infrastructure investments. The methodology developed will be applicable elsewhere for other studies. Bicycles have low access costs and moderate travel speeds, they help protect the environment, reduce congestion and bring many health benefits (Clifton & Akar, 2009). Within these considerations, several researchers have explored the factors associated with bicycling choice to understand the needs of bicyclists and increase bicycle mode share. Existing literature identified socio-demographics, built environment, road conditions and land-use patterns as factors associated with bicycling choice in general (Pucher et al., 2011; Dill and Carr, 2003). Among these, presence of bicycle facilities, motor vehicle traffic characteristics, surface quality, neighboring land-uses are cited as factors affecting bicycling route choices (Broach et al. 2012). There is increasing interest among colleges and universities in ways to reduce local congestion, contributions to greenhouse gases, and provide leadership in sustainable transportation. This study brings these two emerging areas together: analyzing campus transportation patterns and identifying the factors associated with bicycle trip generation and bicycle route choices using state-of-the-art data collection techniques at a large university campus, The Ohio State University (OSU). The origins, destinations and routes of bicycle trips will be collected through a cell phone app: CycleTracks. This study includes 4 major tasks: (i) collect data on bicycle trips (origin, destination, purpose, time and route); (ii) conduct an online survey to capture bicyclists’ perceptions toward several street attributes; (iii) develop maps illustrating the collected data; (iv) develop models to understand the determinants of bicycle trip generation and route choices;
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Documenting and Determining Distributions, Trends, and Relations in Truck Times at International Border Crossing Facilities
RIP Database link: https://rip.trb.org/view/2015/P/1373610
Research Summary
In a separate project, we previously developed a geo-fence based approach to capture the times trucks incur in various activities associated with crossing an international border. We collaborated with a large freight hauler (CEVA Logistics) that regularly traverses the Ambassador Bridge (AMB) and Blue Water Bridge (BWB) international border crossing facilities to implement the approach on its trucks, to determine times for activities of interest to CEVA at the facilities (e.g., time-of-day and day-of-week patterns in overall crossing times, time spent in duty free facilities), and to use the CEVA trucks as probe vehicles to determine general truck activity times of interest to planners and operators (e.g., overall crossing times, queuing times, inspection times). Validation studies supported the results obtained. In prior NEXTRANS projects, we continued to collect data and produce summary statistics. In addition to providing “snapshot” summaries of truck activity times, the extensive dataset we have now compiled can allow unique longitudinal analysis of crossing time activities and estimation of model-based associations of times incurred in activities with other, explanatory variables. Although there were some sporadic efforts in the past to determine truck times at the busy and valuable AMB and BWB border crossing facilities, ours are the only data that have been collected on an ongoing basis and with great spatial detail. The Michigan Department of Transportation (MDOT) is now planning to implement a system to provide real-time information on wait times at the publicly owned and operated BWB facility. However, MDOT is not implementing a system at the busier, but privately owned and operated AMB facility. In addition, MDOT has not presently devoted funding to conduct off-line analysis of temporal patterns in the wait times. In this project, we would continue to collect and process data to provide updated summary statistics of crossing time activities at the AMB and BWB facilities, develop and interpret longitudinal and relational models of important activity times, complement MDOT efforts, and continue to develop stakeholders.
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Roadway Traffic Data Collection from Mobile Platforms
RIP Database link: https://rip.trb.org/view/2015/P/1373767
Research Summary
It is difficult to obtain traffic information on the large number of segments comprising geographically extensive urban roadway networks. Fixed location traffic sensors typically provide continuous coverage for a relatively small number of segments. Portable sensors (e.g., pneumatic tubes) used for temporary data collection expand the monitoring to many more segments, but the cost of deploying traffic data collection crews to cover all the segments on a frequent and regular basis and the personnel required to do so are prohibitive. Therefore, large portions of the urban network are commonly left unmonitored in terms of traffic data collection. Adding low-cost sensors (e.g., radar, LiDAR, or video sensors) to service or utility vehicles that are deployed for other purposes could be a means to collect data over urban networks on an ongoing basis at a low marginal cost.
Transit buses are attractive platforms for carrying such traffic data sensors. Transit buses traverse large portions of the urban roadway network, predominantly on higher traffic volume roadway segments, most of which are not monitored by fixed sensors. The repeated coverage of the same roadways provided by regular transit service allows large numbers of observations in multiple time-of-day periods to be accumulated. Obtaining a large number of observations is important to compensate for the short durations during which the data would be observed by the sensors in any single pass of a mobile platform.
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Methods for improving bicycle sharing system balance
RIP Database link: https://rip.trb.org/view/2015/P/1373774
Research Summary
Local transport systems provide a useful laboratory for transport studies. For example colleagues in CEEGS have worked extensively on the OSU Campus Bus System (CABS), while the Center for Urban and Regional Analysis (CURA) has an emerging interest in many aspects of innovative modes of transport including car and bike sharing. This project proposes to add a new area to this suite of ideas, one that grows from an increasing interest in novel systems for sustainable transportation. In this case the City of Columbus is home to a new bike sharing system, called CoGo. Because the system is still small (30 stations), it has not yet encountered the balance and growth issues that have hampered other larger systems. For this reason an initial study of the re-balancing of the bikes at the stations, the station size and location represent a suite of interdependent problems that are amenable to basic GIS and optimization approaches. Recent news and publicity has made it abundantly clear that large systems have enormous challenges in the area of bike rebalancing. The project proposes research that is needed to combine data from the system with optimization techniques including linear programming) to design low cost strategies that will ensure operational efficiency within the parameters that are established by the local bike share system (CoGo).
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Integrating Multiple Sources of Data for the Estimation of Transit Origin-Destination Flows
RIP Database link: https://rip.trb.org/view/2015/P/1373778
Research Summary
This study will take advantage of large datasets the NEXTRANS investigators have amassed on two transit systems: OSU’s Campus Area Bus Service (CABS) as part of OSU’s Campus Transit Lab (CTL) and the Central Ohio Transit Authority (COTA) as a result of completed and ongoing projects. On CABS, extensive APC, onboard survey, and mobile device tracking data are available. On COTA, extensive APC, onboard survey, and AFC data are available. Thus, each system has three separate sources of data the integration of which will be considered as part of this study. More reliable transit OD flow information has the potential to enhance the quality of transit planning and operations control functions that rely on such information. Moreover, the more accurate route-level estimates are expected to improve the quality of the network-level OD flow estimates, where several methods rely on route-level OD flows as inputs.
In addition to supporting practical service planning and design applications, the developed integration methods are expected to establish new foundations for researchers to build on in addressing questions related to integrating transit data from multiple sources, whether for the purpose of OD flow estimation or other uses of the data. In light of the data quality analyses and their implication on OD flow estimation, the results of this study could inform the design refinements of the next generation of transit data collection and fare collection services such that the overall quality of the data is improved, whether in the context of the primary use of the data or its secondary use, for example for OD flow estimation.
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Campus Transit Laboratory: Infrastructure for Research, Education, and Outreach
RIP Database link: https://rip.trb.org/view/2013/P/1258397
Research Summary
The Ohio State University (OSU) Campus Transit Laboratory (CTL) is a living laboratory that provides the infrastructure for integrated transit-related research investigations, educational activities, and applied studies. The CTL benefits from advanced automatic data collection and information technologies deployed on the OSU Campus Area Bus Service (CABS), accessibility of the CABS system and the OSU community to researchers, instructors, and students for data collection and in situ observations, and regular interaction between CTL investigators and CABS operators and decision makers. This NEXTRANS project would continue to: Sustain, develop, and showcase the CTL; Collect, process, and archive CTL data; Exploit the CTL for research, education, and outreach activities; and Develop collaborations with transit agencies and investigators.
This project is expected to have impacts related to transit planning and operations on each of the research, education, and outreach dimensions. Improvements in transit planning and operations should lead to a more efficient, sustainable, and environmentally responsive balance in the use of urban transportation modes. It is also hoped that publicizing a set of integrated activities centered on the use of a living lab would result in the expanded development and use of such labs in multiple transportation areas.
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Mobile air quality monitoring for local high-resolution characterization of vehicle-sourced criteria pollutants
RIP Database link: https://rip.trb.org/view/2015/P/1374045
Research Summary
This research would investigate the technical feasibility of using transit buses as platforms for carrying inexpensive sensors to obtain spatially detailed air quality data over extensive portions of urban areas. Using bus platforms with inexpensive sensors can offer a low cost means of integrating technologies and modes to obtain air quality data on an ongoing basis at presently unachievable spatial resolution. A specific hypothesis to be investigated is that using present configurations of stationary monitoring sites would not be able to provide the spatiotemporal detail required to detect localized indications of transportation-generated air pollution and indications of air pollution levels that would affect travelers in roadway corridors, whereas using the mobile transit bus platform would be able to provide this detail. The approach of taking advantage of the characteristics of one mode – namely, the regular, repeated route coverage of the transit buses – to provide information on air quality of the urban area, and especially for travelers of transit and other modes (auto, bicycle, walk) would be transferrable to all urban areas that are served by regular transit service. Since buses are deployed for other purposes (providing urban public transportation), the marginal cost of supplying the sensing platform is low. Given the developments in low cost sensors, the total cost of acquisition would be low.
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Inventory of Greenhouse Gas Emissions from On-Road Vehicles in Midwestern USA States and Integrated Approach to Achieving Environmental Sustainability in Transportation
RIP Database link: soon
Research Summary
Green House Gases (GHG) are connected to global warming and hence to climate change. Emissions from on-road vehicles significantly contribute to GHG in the atmosphere. This situation calls for environmental sustainability with the least impact on the transportation sector. Environmental sustainability of the transportation industry should start with the understanding the complexity and the evaluation of the existing status with respect to economy, social behavior and movement patterns, and geography. We propose to monitor changes in climate and environmental parameters with concomitant changes in technology enabled integration and other sustainability factors.
In the first phase, an inventory of current GHG emissions across spatial, temporal, and stakeholder levels from on-road vehicles are studied as a baseline to monitor impacts from the existing technological, policy, social, health, and economic drivers, including disparities that are controlling the transportation sector. In the second phase, alternative scenarios to the existing on-road mobile transportation system will be evaluated in order to reduce the GHG emissions. This will be looked into the aspects of the transportation mode, traffic network systems and alternative energy. -
Signal Timing Optimization for Large Scale Urban Networks under Dynamic Traffic
RIP Database link: https://rip.trb.org/view/2013/P/1374412
Research Summary
The objective of this study is to develop a new methodology for systemwide signal timing optimization to achieve the lowest level of intersection delays in a dense urban street network. The proposed systemwide signal timing optimization is carried out by adjusting green, yellow, and red splits for all signalized intersections in the network according to the traffic dynamics associated with individual intersections in AM peak, PM peak, and the rest of the day periods without changing the cycle length and signal coordination to achieve the lowest level of vehicle and pedestrian delays per cycle over a 24-hour period. Specifically, this project will propose an advanced, integrated decision support framework that contains a basic traffic flow model to handle vehicle delays only, and an enhanced model to simultaneously deal with vehicle and pedestrian delays, respectively. Both models will be integrated into the Chicago TRANSIMS toolbox that was developed to conduct regional traffic assignments on a second-by-second basis. The augmented Chicago TRANSIMS toolbox will be applied to the Chicago Central Business District (CBD) network for systemwide signal timing optimization for model validation and refinements.
2013-2014 Projects
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Segmenting, Grouping and Tracking Vehicles in LIDAR Data
RiP database: https://rip.trb.org/view/2013/P/1324050
Summary of ResearchRoadway congestion impacts almost all aspects of our lives in the US, from safety, to the environment, to the quality of life, to the cost of goods and services. A comprehensive understanding of the traffic conditions over space that give rise to congestion remains elusive. To date, these issues have been studied predominantly with macroscopic data from point detectors (e.g., loop detectors) aggregated over fixed time periods ranging from 20 sec to 15 min. Many new theories have emerged in recent years to explain several on-going anomalies in traditional traffic flow theory. At the core of these new theories is the presence of non-trivial disturbances that last far less than the fixed time aggregation periods commonly used to study traffic, and thus, these micro-disturbances have not been empirically observed. If these theories are proven empirically, they should lead to better congestion management and control.
The proposed research seeks to develop the tools to measure traffic flow at a resolution sufficiently precise to measure the micro-disturbances and prove or disprove the traffic flow theories that depend on their presence. Under support from NSF and FTA, OSU has developed an instrumented probe vehicle that includes positioning sensors (DGPS and inertial navigation) and ranging sensors (six LIDAR, one radar). The focus of the RNS is the one forward facing and one rear facing LIDAR sensors. These LIDAR collect a rich, 180° scan out to 80 m, in a plane approximately 0.5 m above the roadway, at 40 Hz. Although hundreds of hours of data have been collected, the tools to automatically reduce this vast quantity of data to useful information still need to be developed. The proposed research would undertake the task of segmenting the vehicle returns from the non-vehicle objects in the LIDAR data, grouping the vehicle returns into discrete vehicles, and tracking the resulting vehicle groups across scans. Once these tools are developed, they would be used to mine hundreds of hours of existing instrumented probe vehicle data.
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Integration of ground access to airports in measures of inter-urban accessibility
RiP database entry: https://rip.trb.org/view/2013/P/1324051
Summary of ResearchRecent research by the author has focused on the levels of accessibility on the basis of actual air passenger demand and travel patterns across particular origin and destination pairs.
http://www.geography.osu.edu/aviation/
The feedback we have received from this study strongly suggests that the additional factor of surface transport access to airports, particularly in more remote and rural regions, is very important in any measurement of accessibility and service quality. In fact, as is well known in transportation systems models, there are some complex trade-offs. The proposal is to develop a more comprehensive quality indicator of interaction between urban places. The study examines service in conjunction with the ground transport accessibility and travel time to these airports from their probable catchment area. The project would attempt to develop a more comprehensive estimate of door to door travel time from origin to destination. The air side component, via direct or multistep trips is already quite well covered, and this project would add a term for the ground location origin to the estimated destination. Such considerations are quite important to the economic development and employment retention of communities that rely on extensive travel by employees to deliver technical, sales, or other support to dispersed markets.
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Developing Operational and Policy Insights into Next Generation Vehicle Needs Based on an Integrated Understanding of the Transportation and Energy System of Systems
Research Information (pdf)
Status: Active
Summary of Research
Rapidly evolving transportation and energy technology is opening up a tremendous number of possibilities for simultaneously achieving environmental sustainability, economic development, and energy security, but the many possibilities for their interaction greatly complicate analysis to understand the best policy options and strategies for individuals and companies to take to maximize opportunities.
This project proposes to explore the effects of various vehicle design options and more detailed vehicle behavior on the integrated transportation and energy system, with particular interest in studying the effect of vehicle design options on traffic system behavior and fuel and electricity use. The study proposes augmenting the use of MPO data to incorporate the detailed behavior of drivers, new vehicle capabilities, and advanced information systems. The resulting agent based model will be suitable for investigating transportation system behavior under next generation systems and its interaction with the energy system.
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Analysis of Policies Aimed at Increasing Use of Natural Gas in the Transportation System
RiP Database
Status: Active
Summary of ResearchThe major objective of this research is to evaluate a series of natural gas for transportation policy options and to compare them with existing options for electric vehicles, biofuels, CAFE standards, etc. The policy incentives that will be considered are: 1)incentives to create natural gas fueling stations, 2)subsidies for natural gas vehicles comparable to the benefits provided to the country from their use, 3)incentives for retrofitting gasoline vehicles for conversion to CNG, and 5)incentives for fleet adoption of CNG.
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Field Data Based Data Fusion Methodologies to Estimate Dynamic Origin-Destination Demand Matrices from Multiple Sensing and Tracking Technologies
RiP Database
Status: Active
Summary of ResearchRecent advances in real-time traffic sensing, including GPS data from probe vehicles, automatic vehicle identification using RFID and Bluetooth sensors, and automatic number plate recognition, provide richer data when combined with traditional O-D estimation techniques. However, the data obtained from these different sensors do not convey similar information on the traffic conditions of the network. This project seeks to develop and test a systematic methodology to integrate the different data sources, also labeled data fusion, to address the O-D estimation problem, leveraging the availability of different types of data with disparate characteristics.
The study will involve collecting data from ITS test-bed corridors in Chennai (Madras), India. The data collected will also serve as a benchmark data archive for O-D estimation techniques and will augment ongoing research to develop dynamic O-D demand matrices based on partial observability of the field network.
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Estimation of Time-Dependent Intersection Turning Proportions for Adaptive Traffic Signal Controls -or- Estimation of Time-Dependent Intersection Turning Proportions for Adaptive Traffic Signal Control under Limited Link Traffic Counts from Heterogeneous Sensors
RiP Database
Status: Active
Summary of ResearchThis research seeks to estimate time-dependent intersection turning proportions using partial link traffic counts and observed turning proportions provided by heterogeneous sensor technologies.
It will help transportation/highway management agencies determine a desirable sensor deployment plan in terms of how to prioritize the critical links for different sensor characteristics under an annual budget constraint. It will also illustrate that interdependencies arise between information and infrastructure in relation to the vehicles, and that they lead to complexities that require solutions as technology is increasingly leveraged in conjunction with the limited budgets. In terms of broader significance, several methodological approaches involving network-level solutions developed to leverage ITS technologies have been previously limited in terms of real-world deployment due to the unavailability of such O-D matrices. Hence, the proposed research has key practical implications for transportation agencies.
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Information and Transportation Choices, Long- and Short-Term, that Link Sustainability and Livability
RiP Database
Status: Active
Summary of ResearchThe research is designed to test:
a. The sensitivity of the long-term decision of residential location choice to information;
b. The sensitivity of short-term travel behavior to long-term residential location choice.
Rare among policy investigations, information-related questions can be researched through true experimental designs. This project proposes to assign movers in the two cities randomly to control and experimental groups. Experimental groups in Ann Arbor, MI and Lafayette, IN will be exposed to an information-delivery strategy designed to address transportation-relevant decision-making over a range of time scales. Control and experimental groups will be surveyed for transportation-related outcomes, and intergroup differences will be analyzed with standard statistical models to determine treatment effects.
This project proposes to study how travelers' long- and short-term transportation-related decisions are affected by information interventions, providing potentially new perspectives to fostering sustainable transportation choices and bridging methodological gaps in holistically approaching the notion of livability.
Current strategies for the dissemination of transportation information concentrate at the short-term end of the spectrum. Not enough is known about the sensitivity of choices at varying time scales to information interventions or about the downstream impact of longer-term choices on those made over the shorter term. This project will develop new decision-making models informed by multiple disciplines, including cognitive science, behavioral economics, marketing, transportation, and urban planning. The project will design information interventions intended for the full range of transportation-relevant decisions and test their impacts on people moving to Ann Arbor, Michigan, and West Lafayette, Indiana, as well as consumers in the market for a vehicle.
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Truck Activity and Wait Times at International Border Crossings
RiP Database
Status: Active
Summary of ResearchDetermining the times trucks incur at international border crossings is of interest to the private freight industry and to the border crossing facility operators and planners. Private carriers and shippers can benefit from having objective travel time measures for trip planning, scheduling, and routing. Facilities operators and planners can detect when conditions warrant changes in operations or infrastructure. Private and public stakeholders at two of the busiest international truck crossings in North America, both of which are situated in Region 5, do not have access to such travel time data.
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Impact of passenger transportation modes, travel choices, and urban geography on CO2 emissions
RiP Database
Status: Active
Summary of ResearchThe primary objectives of continuing the investigation of the effects of various factors on passenger transportation CO2 emissions are to: (a) further expand the dataset to effectively improve the reliability and wider applicability of the relationships of interest, (b) address the transit utilization limitation and additional travel and regulation characteristics, and (c) broaden the scenario analyses based on the improved models to capture joint factor effects and to demonstrate their use as a policy-making support tool.
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LIDAR Based Vehicle Classification
RiP Database
Status: Active
Summary of ResearchVehicle classification data are used in many transportation applications, including: planning, pavement design, environmental impact studies, traffic control, and traffic safety. Every state in the US maintains a network of vehicle classification stations to explicitly sort vehicles into several classes based on observable features, e.g., length, number of axles, axle spacing, etc. Various technologies are used for this automated classification, the three most common approaches are: weigh in motion (WIM); axle-based classification from a combination of loop detectors, piezoelectric sensors or pneumatic sensors; and length-based classification from dual loop detectors. All of these sensor technologies suffer from the difficulty of deploying and maintaining in/on pavement sensors. There has recently been an increasing interest in developing non-intrusive sensors to classify vehicles, e.g., there are several non-intrusive sensors now on the market that offer vehicle classification and most of these sensors rely on microwave radar (e.g., RTMS, SmartSensor, etc.).
The research will deploy LIDAR based system using high vantage points (10-30 m) at one or more multi-lane facilities to monitor traffic and overcome the current limitation due occlusions. In addition to algorithm development, the research will include extensive, labor-intensive ground truth data extraction, both for development and validation of the algorithms. The budget and scope of the work is for the task of developing the LIDAR based system.
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Transit Origin-Destination Flow Estimation Considering Temporal Variations based on APC Data
RiP Database
Status: Active
Summary of ResearchThis project builds upon the progress made by the NEXTRANS investigators in using APC data from transit buses to estimate route-level OD flows considering a variety of new dimensions and identified limitations. Specifically, these efforts relate to the temporal representation of OD flows.
Route-level bus passenger OD flow estimation methods recently developed by the NEXTRANS investigators are presently being used to provide insights on empirical flow patterns for a few transit agencies. The research here is targeted to improve upon these applications for sustained, long-term use. As was done in moving the recently developed approaches toward empirical implementation, methodological formulations must be developed, evaluated, and refined before being put into use. The advanced methods eventually developed would form the basis for long-term benefits to transit agencies and MPOs.
The methods being developed are based on exploiting spatially and temporally extensive boarding and alighting data that are now available from APC technologies in use on many transit properties. As with previously developed methods, the new methods will be inspired by an understanding of bus passenger behavior that is consistent with data and in situ observations collected on OSU’s living Campus Transit Lab and refined according to these data and observations.
The developed methods will lead to a richer representation of OD flow patterns and more accurate estimates of such patterns. In both cases, improved service planning and operations, where OD flow patterns are used as inputs, are expected. Planning applications include, for example, extending, splitting or combining, and designing new routes, and operations applications include short-turning, expressing, and holding. Improved service and operations will eventually result in a more competitive transit mode, with subsequent effects on reduced congestion, improved sustainable use of energy resources, and mitigated environmental impacts stemming from passenger travel
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Using Naturalistic Driving Performance Data to Develop an Empirically Defined Model of Distracted Driving
RiP Database
Status: Active
Summary of ResearchApproximately 33,000 fatalities and over 2.2 million nonfatal injuries result from motor vehicle crashes each year in the United States, with a total cost that exceeded $US230 billion in 2009 alone (NHTSA, 2010a). In 2009, 16% of fatal crashes and 20% of non-fatal injury crashes included reports of distracted driving (NHTSA, 2010b). Findings from the 100-Car Naturalistic Driving Study suggested that 22% of all crashes and near-crashes were related to secondary-task distraction (Klauer, 2006). The measurement of driver distraction is a challenge. Driver self-assessment of distraction is inaccurate, observational studies can only detect observable distractions, and naturalistic driving studies are costly. The prevention of distraction-related crashes requires a better understanding of the nature of driver distraction. This, in turn, requires a means to accurately assess the occurrence and degree of driver distraction in large samples. The goal of this project is to identify kinematic indicators of distracted driving for devising a model that would allow distracted driving to be measured using technological approaches. The result will be a new definition of distracted driving that is based on measureable kinematic variables. This ability would facilitate an epidemiologic approach to studying driver distraction, as well as contribute to potential warning systems that redirect distracted drivers’ attention back to the task of driving.
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Standardized Metrics for Accessibility: Establishing a Federal Policy-Relevant Knowledge Base
RiP Database
Status: Active
Summary of ResearchTransportation planning and policy has traditionally been evaluated with metrics of mobility, such as highway level-of-service or time lost to delay. Standardized metrics of mobility are abundantly available to planners and engineers through such widely used resources as the Highway Capacity Manual and the Manual on Uniform Traffic Control Devices. Standardized data about mobility facilitate consistent evaluations of transportation outcomes across both time and place. The purpose of transportation, however, is not movement but access, and ubiquitous reliance on mobility-based evaluation has tended to favor—via both transportation and land-use planning--low-density, auto oriented development patterns. A shift to accessibility-based metrics can help alter this trend, and can better align planning practice with transportation’s fundamental purpose. Yet no standardized metrics are currently available to assist decision makers about progress on accessibility. This project seeks to understand how a standardized set of data generated by regional agencies might be collected in a repository to facilitate consistent and dependable accessibility-based analysis among places and through time. Tasks include assessing the current state of standardized transportation data, documenting the range of current practice with regard to the needed inputs to accessibility analysis, and developing a framework for standardizing the inputs to accessibility metrics. The objective is to provide assistance to federal agencies in modify their procedures for data collection and publication and for Metropolitan Planning Organizations and local governments to gain the capacity to compare their outcomes over time to other peers.
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Mapping New Mobility Business, Innovation, and Employment Opportunities in Michigan: Developing a Data-Driven Graphic Platform for Assessing and Advancing Laboratory Development and Entrepreneurship Opportunities in Urban Regions
RiP Database
Status: Active
Summary of ResearchThis work will develop a data-driven mapping platform for assessing local and regional economic development, employment, entrepreneurship, and industry cluster development opportunities related to New Mobility, starting with southeast Michigan as the initial prototype area. The mapping activity will assemble through a GIS-based toolset, a dynamic visualization and geospatialization platform to illuminate existing material and economic flows between related sector agents, as well as to identify network gaps via methodologies related to value-chain mapping.
In general, this suite of network visualization tools relates specifically to New Mobility industry and enterprise, fills an important analysis gap and will result in more informed decision making and innovation by governments, large business, entrepreneurs and other innovators. The work addresses the specific interests of project partners by integrating diverse sets of data and interrelations that operate within ‘blind spots’ of individual sector participants. The tools proposed for development aim to result in more informed decision-making and risk assessment in emerging sectors, while identifying the priority strategic actions Michigan policy and business leadership can advance that support the growth of the new mobility industry sector in Michigan. The proposed tools will be developed with the intent that process and product can be scaled and translated to other sites and globally.
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Use of Comparative Efficiency Analysis to Optimize Transportation Infrastructure
RiP Database
Status: Active
Summary of ResearchThe main purpose of this research is to present an analysis of an alternative strategy for optimizing transportation infrastructure maintenance decision-making. The approach being proposed is based on performance-based resource analysis, which balances competing objectives and perspectives of multiple stakeholder groups while considering the amount of resources available, as described in NCHRP Report 666. Performance-based analysis focuses on the concept of spending efficiencies and performance-based resource allocation. It also encourages the use of performance targets and the ways to develop and maintain them over time. Performance targets have to become a part of the business process that directly links organizational goals and objectives to available resources and results. In performance-based resource analysis, targets are critical when evaluating the effectiveness of investment decisions.
The primary benefit of this research is that it empowers maintenance administrators in state transportation agencies with a new and innovative integrated solution to make decisions and set policies related to transportation infrastructure maintenance. The result of this research provides an alternative way to look at how efficient maintenance spending has been, and gives maintenance administrators a chance to figure out the most efficient way to allocate and distribute maintenance funds.
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Driving Simulator Laboratory: Traveler Behavior Modeling and Interactive Experiments to Address Mobility and Safety Needs
RiP Database
Status: Active
Summary of ResearchThe Purdue Driving Simulator Laboratory (DSL) will be a quasi-living laboratory for mobility and safety research, interactive learning, and outreach. The DSL will develop behavioral and operational models and assess impacts to address current and emerging needs of the USDOT, state and local DOTs, and private sector firms in the information and locational services domains.
It seeks to address fundamental questions related to the costs-benefits of infrastructure investment in advanced traveler information based management systems, the explicit quantification of the psychological impacts of information provision, traveler behavior to develop effective operational road-space management strategies, evacuee behavior under large-scale disasters, and the holistic understanding of real-time information provision and dissemination mechanisms from the mobility and safety perspectives.
The ability to quantify physical and psychological benefits of real-time information has several dimensions of significant impact for practitioners and researchers. The proposed experiments will enable development of realistic behavior models and understanding of the benefits and safety implications associated with information provision and road space management strategies
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Accessibility-Based Evaluation of Transportation and Land-Use Planning: From Laboratory to Practice
RiP Database
Status: Active
Summary of ResearchThe project will be informed by lessons derived from a previous multi-year project at the University of Michigan that measured regional accessibility among the top 50 metropolitan regions of the United States, and will proceed in four interrelated stages:
A. Research political and technical barriers to the adoption of accessibility-based evaluation.
B. Develop case studies of accessibility- and mobility-based evaluation.
C. Develop approaches to incorporating accessibility-based evaluation.
D. Collaborate with practitioners and decision-makers on assessment of accessibility-based evaluation.
The utility of approaches described above will be assessed through interviews and focus groups with practitioners.
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Campus Transit Laboratory: Infrastructure for Research, Education, and Outreach
RiP Database
Status: Active
Summary of ResearchThe Ohio State University (OSU) Campus Transit Laboratory (CTL) is a living laboratory that provides the infrastructure for integrated transit-related research investigations, educational activities, and applied studies. The CTL benefits from advanced automatic data collection and information technologies deployed on the OSU Campus Area Bus Service (CABS), accessibility of the CABS system and the OSU community to researchers, instructors, and students for data collection and in situ observations, and regular interaction between CTL investigators and CABS operators and decision makers. This NEXTRANS project would continue to: -Sustain, develop, and showcase the CTL -Collect, process, and archive CTL data -Exploit the CTL for research, education, and outreach activities -Develop collaborations with transit agencies and investigators.
Current Events
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Research
Education
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University Partners
- Purdue University
- The Ohio State University
- Central State University
- Chicago State University
- Illinois Institute of Technology
- Trine University
- University of Michigan
- University of Wisconsin-Madison
