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Snowplow operators are often tasked with clearing snow from roadways under challenging conditions. One such situation is low visibility due to falling or blowing snow that makes it difficult to navigate, stay centered in the lane, and identify upcoming hazards. To support snowplow operators working in these conditions, University of Minnesota researchers developed a snowplow driver-assist system that provides the operator with visual and auditory information that is suitable for low-visibility situations. A lane-guidance system uses high-accuracy Global Navigation Satellite System (GNSS) and maps of the roadway to provide information to drivers about their lateral positions. A forward-obstacle-detection system uses forward-facing radar to detect potential hazards in the roadway. The design of the system, and in particular its interface, is guided by extensive user testing to ensure the system is easy to understand, easy to use, and well liked among its users. The system was deployed in two phases over the 2020-2021 and 2021-2022 winter seasons. In total, nine systems were deployed on snowplows across Minnesota, four in the first winter season and an additional five in the second. Participating truck stations represented all eight MnDOT districts as well as Dakota County. Over the course of the deployment, additional user feedback was collected to identify system strengths and areas for improvement. The system was found to be a cost-effective addition to snowplows that increase driver safety, reduce plow downtime, and increase driver efficacy for plowing operations, thus providing support to operators working in demanding, low-visibility conditions.

Our objective is the development and evaluation of a low-cost, vehicle-mounted sensor suite capable of generating map data with lane and road boundary information accurate to the 10 cm (4 in) level. Such a map could be used for a number of different applications including GNSS/GPS based lane departure avoidance systems, smart phone based dynamic curve speed warning systems, basemap improvements, among others. The sensor suite used consists of a high accuracy GNSS receiver, a side-facing video camera, and a computer. Including cabling and mounting hardware, the equipment costs were roughly $30,000. Here, the side-facing camera is used to record video of the ground adjacent to the passenger side of the vehicle. The video is processed using a computer vision algorithm that locates the fog line within the video frame. Using vehicle position data (provided by GNSS) and previously collected video calibration data, the fog line is located in real-world coordinates. The system was tested on two roads (primarily two-lane, undivided highway) for which high accuracy (<10 cm) maps were available. This offset between the reference data and the computed fog line position was generally better than 7.5 cm (3 in). The results of this work demonstrate that it is feasible to use a camera to detect the position of a road's fog lines, or more broadly any other lane markings, which when integrated into a larger mobile data collection system, can provide accurate lane and road boundary information about road geometry.

The use of LIDAR is becoming more common among state, county, and local agencies. It presents a means for collecting a great deal of information about the geometry of a road, its surrounding area, and depending on the sensors used, real-time 3D information about vehicle, cyclist, and pedestrian movements. The main focus of this project was to develop and conduct two workshops in Minnesota for public DOT and GIS professionals to provide information on the state of the art in mobile LIDAR scanning. Topics included the basics of LIDAR operation, an overview of currently available hardware, as well as current and future applications of the technology. Additionally, the workshops featured a live demonstration of a Velodyne HDL-64E 3D LIDAR scanner. A sample application was developed to both demonstrate and better understand the capabilities of a real-time 3D LIDAR scanner. This work focused on developing a system capable of automatically collecting vehicle trajectories through intersections using 3D LIDAR data. This application showed that LIDAR might be a suitable tool for collecting traffic data and provided valuable information about the strengths and limitations of such a system. This project was designed to provide transportation and GIS professionals with accurate, current, and applicable information about LIDAR systems. To accomplish this, existing LIDAR knowledge was combined with market survey research as well as with new information gathered through the process of creating a sample application. This knowledge was aggregated and used to create a workshop that was informative and well received by participants.

An increasing number of Accessible Pedestrian Signals (APS) have been installed at new or upgraded intersections to assist people with vision impairment to navigate streets. For un-signalized intersections and intersections without APS; people with vision impairment have to rely on their own orientation and mobility skills to gather necessary information to navigate to their destinations. Previously; a smartphone-based accessible pedestrian system was developed to support wayfinding and navigation for people with vision impairment at both signalized and un-signalized intersections. A digital map was also created to support the wayfinding app. This system allows a visually impaired pedestrian to receive signal timing and intersection geometry information from a smartphone app for wayfinding assistance. A beacon using Bluetooth Low Energy (BLE) technology helps to identify a pedestrian's location when he or she travels in a GPS-unfriendly environment. A network of Bluetooth beacons ensures that correct traffic information is provided to the visually impaired at the right location. This project leverages the previous work by installing the system at a number of intersections in downtown Stillwater; Minnesota; where MnDOT operates the signalized intersections. In this study; researchers interface with the traffic controllers to broadcast traffic signal phasing and timing (SPaT) information through a secured and private wireless network for visually impaired users. The aim is to test the smartphone-based accessible system and evaluate the effectiveness and usefulness of the system in supporting wayfinding and navigation while the visually impaired travel through signalized and un-signalized intersections.

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.

This flyer was created as part of Report 2023-04, "Development of a Mobile App for Reporting Work Zone Intrusions," published January 2024.

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.

This report discusses the results of a study to quantify the performance of low-cost; centimeter-level accurate Global Navigation Satellite Systems (GNSS) receivers that have appeared on the market in the last few years. Centimeter-level accuracy is achieved using a complex algorithm known as real-time kinematic (RTK) processing. It involves processing correction data from a ground network of GNSS receivers in addition to the signals transmitted by the GNSS satellites. This makes RTK-capable receivers costly (in excess of $10;000) and bulky; making them unsuitable for cost- and size-sensitive transportation applications (e.g.; driver assist systems in vehicles). If inexpensive GNSS receivers capable of generating a position solution with centimeter accuracy were widely available; they would push the GNSS revolution in ground transportation even further as an enabler of safety enhancements such as ubiquitous lane-departure warning systems and enhanced stability-control systems. Recently manufacturers have been advertising the availability of low-cost (< $1;000) RTK-capable receivers. The work described in this report provides an independent performance assessment of these receivers relative to high-end (and costly) receivers in realistic settings encountered in transportation applications.

Lane-departure crashes at horizontal curves represent a significant portion of fatal crashes on rural Minnesota roads. Because of this; solutions are needed to aid drivers in identifying upcoming curves and inform them of a safe speed at which they should navigate the curve. One method for achieving this that avoids costly infrastructure-based methods is to use in-vehicle technology to display dynamic curve-speed warnings to the driver. Such a system would consist of a device located in the vehicle capable of providing a visual and auditory warning to the driver when approaching a potentially hazardous curve at an unsafe speed. This project seeks to determine the feasibility of in-vehicle dynamic curve-speed warnings as deployed on a smartphone app. The system was designed to maximize safety and efficacy to ensure that system warnings are appropriate; timely; and non-distracting to the driver. The developed system was designed and implemented based on the results of a literature survey and a usability study. The developed system was evaluated by 24 Minnesota drivers in a controlled pilot study at the Minnesota Highway Safety and Research Center in St. Cloud; Minnesota. The results of the pilot study showed that; overall; the pilot study participants liked the system and found it useful. Analysis of quantitative driver behavior metrics showed that when receiving appropriately placed warnings; drivers navigated horizontal curves 8-10% slower than when not using the system. These findings show that such a curve-speed warning system would be useful; effective; and safe for Minnesota drivers.