Browsing by Subject "Data collection"

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Bicycle and Pedestrian Data Collection Manual
(Minnesota Department of Transportation, 2017-01) Minge, Erik; Falero, Courtney; Lindsey, Greg; Petesch, Michael; Vorvick, Thor
The Minnesota Department of Transportation (MnDOT) launched the Minnesota Bicycle and Pedestrian Counting Initiative in 2011, a statewide, collaborative effort to encourage and support non-motorized traffic monitoring. One of the objectives of the Initiative was to provide guidance related to monitoring bicycle and pedestrian traffic. This manual is an introductory guide nonmotorized traffic monitoring. The manual describes general traffic monitoring principles; bicycle and pedestrian data collection sensors; how to perform counts; data management and analysis; and the next steps for bicycle and pedestrian traffic monitoring in Minnesota. The manual also includes several case studies that illustrate how bicycle and pedestrian traffic data can be used to support transportation planning and engineering.
Bridge Health Monitoring and Inspections – A Survey of Methods
(Minnesota Department of Transportation, 2009-09) Gastineau, Andrew; Johnson, Tyler; Schultz, Arturo
Since the collapse of the I-35W bridge in August 2007, bridge health monitoring has become an area of intense interest. This report defines terminology related to bridge health monitoring and provides a general glossary of available monitoring systems. The glossary is meant to help readers make an informed decision by understanding how different systems function and their strengths and weakness. The authors developed a questionnaire to send to commercial companies offering monitoring systems. Of the 72 questionnaires that were sent to commercial companies, 38 companies responded and are included in this report. From information provided with these questionnaires, available commercial systems are briefly summarized. Criteria for system evaluation were developed to help the bridge owner narrow down company choices for bridge application. After the owner answers a set of questions pertaining to a particular bridge, a program developed in Microsoft EXCEL helps the bridge owner decide the best system for a particular situation. An example is provided for program clarity. Once company choice is narrowed down, additional criteria were developed to aid in final product choice.
Call me maybe? It's not crazy! Data collection offices are a good partner in data management
(2015) Sell, Andrew; Hofelich Mohr, Alicia
For data management professionals, attention is largely focused on the beginning and ends of the research process, as many researchers are worried about meeting federal requirements for data management plans (DMPs) and are looking for ways to share and archive their data. As a University office specializing in survey and experimental data collection, we have seen how the "middle" steps of data collection and analysis can be influenced by, and be an influence on, these upstream and downstream data management processes. In this Pecha Kucha, we will present relevant data management lessons we have learned from designing, developing, and hosting data collection tools. Challenges of anonymity and paying participants, quirks of statistical files produced by data collection tools, and transparency in the research process are among some of the issues we will discuss. As many of these challenges directly impact later sharing and curation of the data collected, we emphasize that data collection offices can be important partners in data management efforts.
Development of a Mobile App for Reporting Work Zone Intrusions
(Minnesota Department of Transportation, 2024-01) Davis, Brian; Morris, Nichole L.; Craig, Curtis; Schumacher, John; Khoday, Annaika
Work zone intrusions represent a significant safety risk to workers. To help better understand these situations, the Minnesota Department of Transportation partnered with the University of Minnesota to create a method to document intrusion events. This information provides a deeper understanding of the circumstances under which these events occur and enables data-driven decision making when considering ways to reduce or mitigate work zone intrusions. This work focuses on the development of a mobile smartphone app that allows workers to report intrusions from the field immediately after they occur, allowing for timely and accurate intrusion reporting. The work zone intrusion mobile app is developed using an iterative, user-centered design process that solicits feedback from work zone personnel, supervisors, and work zone safety stakeholders at every step in the process. The app uploads completed report data to the existing eSAFE system, allowing for a single repository of collected intrusion report data. To support deployment of the system, training workshops and supporting training and communications materials are created for distribution among users. Throughout the development and deployment of the app, user feedback shows that the app is easy to use and well liked.
Freeway Network Traffic Detection and Monitoring Incidents
(Minnesota Department of Transportation, 2007-10) Joshi, Ajay J.; Atev, Stefan; Fehr, Duc; Drenner, Andrew; Bodor, Robert; Masoud, Osama; Papanikolopoulos, Nikolaos P.
We propose methods to distinguish between moving cast shadows and moving foreground objects in video sequences. Shadow detection is an important part of any surveillance system as it makes object shape recovery possible, as well as improves accuracy of other statistics collection systems. As most such systems assume video frames without shadows, shadows must be dealt with beforehand. We propose a multi-level shadow identification scheme that is generally applicable without restrictions on the number of light sources, illumination conditions, surface orientations, and object sizes. In the first level, we use a background segmentation technique to identify foreground regions that include moving shadows. In the second step, pixel-based decisions are made by comparing the current frame with the background model to distinguish between shadows and actual foreground. In the third step, this result is improved using blob-level reasoning that works on geometric constraints of identified shadow and foreground blobs. Results on various sequences under different illumination conditions show the success of the proposed approach. Second, we propose methods for physical placement of cameras in a site so as to make the most of the number of cameras available.
I-94 Connected Vehicles Testbed Operations and Maintenance
(Center for Transportation Studies, University of Minnesota, 2019-06) Duhn, Melissa; Parikh, Gordon; Hourdos, John
In March 2017, the Connected Vehicle Testbed along I-94 went live. The original project was sponsored by the Roadway Safety Institute and built on the Minnesota Traffic Observatory's (MTO) existing field lab, also utilizing certain Minnesota Department of Transportation (MnDOT) infrastructure. The testbed originally consisted of seven stations, rooftop and roadside, capable of transmitting radar and video data collected from the roadway back to a database at the MTO for analysis, emulating what a future connected vehicle (CV) roadway will look like. This project funded maintenance and upgrades to the system, as well as movement of some stations due to construction on I-94. In addition, better visualization tools for reading the database were developed. The CV testbed is state-of-the-art, fully functional, and uniquely situated to attract freeway safety-oriented vehicle to infrastructure (V2I) and vehicle to vehicle (V2V) safety application development, implementation, and evaluation projects going forward.
Implementation of a V2I Highway Safety System and Connected Vehicle Testbed
(Center for Transportation Studies, University of Minnesota, 2019-04) Hourdos, John; Parikh, Gordon; Dirks, Peter; Lehrke, Derek
To better prepare for the Connected Vehicle (CV) roadway, RSI has established a CV testbed along a highly crashed section of I-94, building on the Minnesota Traffic Observatory’s existing field lab infrastructure. This real- world testbed was designed to implement and evaluate the next generation of vehicle-based freeway safety applications. The priority of this project was to establish the backbone of the sensor communication network and data collection system along the testbed length.
Improvement of Driving Simulator Eye Tracking Software
(Center for Transportation Studies, University of Minnesota, 2019-06) Davis, Brian; Morris, Nichole L.; Achtemeier, Jacob D.; Easterlund, Peter
This work focuses on improving the eye tracking analysis tools used with the HumanFIRST driving simulator. Eye tracking is an important tool for simulation-based studies. It allows researchers to understand where participants are focusing their visual attention while driving. The eye tracking system provides a nearly continuous record of the direction in which the driver is looking with respect to real-world coordinates. However, this by itself does not give any information about the objects at which the driver is looking. To determine when a driver is fixated on a given element in the simulated world (e.g., a vehicle or sign), additional processing is necessary. Current methods to process this data are time and resource intensive, requiring a researcher to manually review the eye tracking data. This motivates an automated solution that can automatically and programmatically combine eye tracking and simulator data to determine at which object(s) (either in the real world or the simulated world) the driver is looking. This was accomplished by developing and implementing software capable of providing useful eye tracking data to researchers without requiring time and resource intensive human intervention and hand coding of data. The data generated by the analysis software was designed to provide a set of summary statistics and metrics that will be useful across different simulation studies. Additionally, visualization software was created to allow researchers to view key simulator and eye tracking data for context or insight or to identify and characterize anomalies in the analysis software. Overall, the software implemented will increase the efficiency with which eye tracking data can be used alongside simulator data.
Manitou Stream Monitoring Project Field Methods
(University of Minnesota Duluth, 2004-04) Brady, Valerie; Johnson, Lucinda B; Reed, Jane
This stream monitoring protocol primarily describes collection of data about basic geomorphological and physical habitat parameters of stream reaches.
Non-linear spacing policy and network analysis for shared-road platooning
(Center for Transportation Studies, University of Minnesota, 2019-08) Levin, Michael; Rajamani, Rajesh; Jeon, Woongsun; Chen, Rongsheng; Kang, Di
Connected vehicle technology creates new opportunities for obtaining knowledge about the surrounding traffic and using that knowledge to optimize individual vehicle behaviors. This project creates an interdisciplinary group to study vehicle connectivity, and this report discusses three activities of this group. First, we study the problem of traffic state (flows and densities) using position reports from connected vehicles. Even if the market penetration of connected vehicles is limited, speed information can be inverted through the flow-density relationship to estimate space-and time-specific flows and densities. Propagation, according to the kinematic wave theory, is combined with measurements through Kalman filtering. Second, the team studies the problem of cyber-attack communications. Malicious actors could hack the communications to incorrectly report position, speed, or accelerations to induce a collision. By comparing the communications with radar data, the project team develops an analytical method for vehicles using cooperative adaptive cruise control to detect erroneous or malicious data and respond accordingly (by not relying on connectivity for safe following distances). Third, the team considers new spacing policies for cooperative adaptive cruise control and how they would affect city traffic. Due to the computational complexity of microsimulation, the team elects to convert the new spacing policy into a flow-density relationship. A link transmission model is constructed by creating a piecewise linear approximation. Results from dynamic traffic assignment on a city network shows that improvements in capacity reduces delays on freeways, but surprisingly route choice increased congestion for the overall city.
Pedestrian and Bicycle Crash Risk and Equity: Implications for Street Improvement Projects
(2019-06) Lindsey, Greg; Tao, Tao; Wang, Jueyu; Cao, Jason
Transportation managers need information about crash risk and equity to prioritize investments in street networks. This case study uses data from Minneapolis, Minnesota, to illustrate how estimates of pedestrian and bicycle crash risk and assessments of inequities in the distribution of that risk can inform prioritization of street improvement projects. Crash numbers and frequencies for pedestrian and bicycle crashes at intersections and mid-blocks in Minneapolis are determined for the 2005-2017 period. New models of pedestrian and bicycle crash risk at both intersections and mid-blocks that control for exposure are introduced and used to predict crashes at all intersections and mid-blocks in the city. Statistical tests are used to assess the equity of distribution of estimated crash risk between areas of concentrated poverty with majority-minority populations and other areas in the city. Crash indexes based on predicted crashes are used to illustrate how increased emphases can be placed on pedestrian and bicycle safety in street improvement rankings. Results show that pedestrian and bicycle crash risk is correlated with exposure, that different factors affect crash risk at intersections and mid-blocks, and that these factors differ for pedestrian and bicycle crashes. Results also show that mean crash risk is higher in neighborhoods with lower incomes and majority-minority populations. For street improvement projects in the city, different rankings result when segments are ranked according to modeled pedestrian and bicycle crash risk in addition to total crash rates based on historical numbers of crashes at particular locations. Results generally affirm efforts by the Minneapolis Department of Public Works to increase emphases on pedestrian and bicycle safety and equity in its prioritization of street improvements.
Research Implementation of the SMART SIGNAL System on Trunk Highway (TH) 13
(Minnesota Department of Transportation, 2013-02) Liu, Henry X.; Zheng, Jianfeng; Hu, Heng; Sun, Jie
In our previous research, the SMART-SIGNAL (Systematic Monitoring of Arterial Road Traffic and Signals) system that can collect event-based traffic data and generate comprehensive performance measures has been successfully developed by the University of Minnesota. In this research, a new set of interfaces are developed for SMART-SIGNAL system including new prototypes of data collection unit (DCU) and refined web-based user interface. To collect high resolution event-based traffic data including both vehicle detector actuation event and signal phase change event, two types of DCUs are designed, the TS-1 DCU and TS-2 DCU for corresponding traffic signal cabinet. TS-1 DCU connects with TS-1 cabinet using pin to pin interface, and the TS-2 DCU interfaces directly with SDLC bus within TS-2 cabinet. The DCUs uses high performance microcontroller modules, and are compact and easy to install. Both DCUs are designed to be vender independent add-on module for traffic cabinet, and can be used as flexible solution to enhance data collection by agencies. The refined web-based user interface features various performance measures to public users, such as Level of Service (LOS), queue length, travel time and intersection delays. The new set of interfaces have been deployed with the SMART-SIGNAL system at 13 intersections along Trunk Highway (TH) 13 in Burnsville, MN.
Smartphone-Based Travel Experience Sampling and Behavior Intervention among Young Adults
(Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota, 2012-05) Fan, Yingling; Chen, Qian; Liao, Chen-Fu; Douma, Frank
This research project aims to develop a data collection application that enables real-time tracking and reporting of the health-related impacts of travel behavior. Using computing, communication, and sensing capabilities of smartphones, an Android phone application—named UbiActive—was developed to collect real-time travel-related physical activity and psychological well-being data from phone users. The application was tested on multiple Android phones, among which Nexus S and HTC Magic were found to produce comparable physical activity outputs with the commercially available accelerometer. The application was further tested in a three-week field study for its viability for real-time data collection and behavior intervention against unhealthy travel behavior. Twenty-three young adults were recruited and randomized into intervention and control groups. Both groups were asked to install UbiActive on their phone and wear their phone on their right hip during all waking hours for three consecutive weeks. The intervention group was provided information on impacts of their travel behavior on physical activity and psychological well-being. No information was provided to the control group. After the field study, all participants were asked to complete a web-based exit survey that was comprised of questions about their general participation experience and specific concerns about the study design, application, compliance requirements, and privacy issues. Findings from the field study show that UbiActive has high potential in collecting travel-related physical activity and psychological experience data, but limited effectiveness in behavior intervention. Findings from the exit survey provide useful insights into potential improvement areas of the study and the UbiActive application.
Transitway Data Management Project
(Center for Transportation Studies, 2010-01) Borah, Jason C.; Craig, William J.
The purpose of this project is make data available for studying the impact of transitways in the Twin Cities Metropolitan Area. We are doing this in two ways: 1) documenting the databases used by University of Minnesota researchers funded by the TIRP – Transitways Impact Research Program and 2) developing a directory of public and private data sources that could be used by future TIRP researchers. This report documents work done to accomplish those goals. Preliminary work has been done using the Minnesota Metadata Guidelines to document two completed TIRP projects. Ten new data sources have been added to MetroGIS’s DataFinder catalog, along with two new data categories. These sources and categories are documented in the report.
Work Zone Intrusion Report Interface Design
(Minnesota Department of Transportation, 2018-02) Craig, Curtis M.; Morris, Nichole L.; Libby, David A.; Davis, Brian
While necessary for roadways, work zones present a safety risk to crew. Half of road workers deaths between 2005 and 2010 were due to collisions with motorists intruding on the work zone. Therefore, addressing intrusions is an important step for ensuring a safe work environment for crewmembers. However, a recent research synthesis at the Minnesota Department of Transportation found that few states had an explicit method for systematically collecting work zone intrusion data. The purpose of this work zone intrusion interface design project was to design an efficient, comprehensive, and user-friendly reporting system for intrusions in work zones. A user-centric, iterative design process was employed to design an adaptable web-based and paper report to account for simple documentation of intrusions not deemed a threat to worker safety and a detailed report for more thorough documentation of serious intrusion events. Final recommendations include organizational changes and support to encourage workers to complete the form and provide valuable data to the state.

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