Browsing by Subject "Ran off road crashes"

Now showing 1 - 4 of 4
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    Development of a Sensor Platform for Roadway Mapping: Part A - Road Centerline and Asset Management
    (Center for Transportation Studies, University of Minnesota, 2014-06) Davis, Brian; Donath, Max
    Collecting information about the roadway infrastructure is a task that DOTs at all governmental levels need to accomplish. One way to increase the operational efficiency of these efforts is to use a relatively inexpensive mobile data collection platform that acquires information that is general enough to serve multiple purposes. The design and evaluation of one such platform that costs roughly $40,000 is described. It primarily consists of a differential GPS receiver providing vehicle location, and a LIDAR scanner that generates geometric profiles of the area between the vehicle and just beyond the road’s edge. The vehicle collects data along the road by driving it in both directions. The system post-processes the data to automate feature extraction. For roads with simple geometry such as two-lane, undivided highways, the road’s centerline can be calculated by finding the midline between the vehicle’s paths from each direction of travel. Algorithms process the LIDAR scans to automatically detect the presence of curbs and guardrails, which is then combined with location information to yield the position of these features in world coordinates. The centerline calculation was determined to be accurate to within 6 cm in areas where its use was applicable. Curbs and guardrails were generally detected with an accuracy of better than 10 cm. The results demonstrate that it is feasible to use a relatively inexpensive mobile data collection system to acquire road centerline and roadside features such as curbs and guardrails.
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    Development of a Sensor Platform for Roadway Mapping: Part B – Mapping the Road Fog Lines
    (Minnesota Department of Transportation, 2015-04) Davis, Brian; Donath, Max
    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.
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    Human Factors of Vehicle-Based Lane Departure Warning Systems
    (Minnesota Department of Transportation, 2015-06) Edwards, Christopher; Cooper, Jennifer; Ton, Alice
    Run-off-road (ROR) crashes are a concern for two-lane rural and urban roadways throughout Minnesota due to the frequency by which they contribute to fatal crashes (Minnesota Crash Facts, 2013). Mitigating the severity of the ROR events is an on-going research goal in order to help reduce the number of ROR crashes. Examining countermeasures that may reduce ROR crashes is important to determine the most efficient and effective method of warning. Behavioral responses were examined through the use of an in-vehicle haptic-based lane departure warning system (LDWS) using a driving simulator. The study incorporated systematic variation to both the reliability of the warning and sequence of treatment conditions. An additional analysis examined the presence of behavioral adaptation after repeated exposure to the system. Severity of a ROR event was measured as the total time out of lane (TTL) and maximum lane deviation (MLD). Covariates (e.g. road shape) were examined to determine the influence they may have on the severity of a ROR. The results reveal overall LDWS efficacy. TTL was significantly longer when no system was active compared to when it was active. LDWS led to shorter duration of ROR events. Greater velocity was found to be highly predictive of longer TTL. MLD was also greater for baseline drives compared to treatment drives. No behavioral adaptation or system overreliance was detected, suggesting long term benefits of the LDWS. Drivers who actively engaged in a distraction task were at far greater risk of traveling greater and more dangerous distances out of lane.
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    In-Vehicle Dynamic Curve-Speed Warnings at High-Risk Rural Curves
    (Minnesota Department of Transportation, 2018-03) Davis, Brian; Morris, Nichole L.; Achtemeier, Jacob D.; Patzer, Brady
    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.