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According to statistics from the Federal Highway Administration (FHWA), each year approximately 17% of all work zone fatalities are pedestrians. People who are visually impaired often encounter physical and information barriers that limit their accessibility and mobility. A survey was conducted among 10 visually impaired participants as a starting point to understand their challenges and what types of information are helpful in providing bypass or routing instructions to them around work zones. The survey results were incorporated into development of guiding documents in determining information elements that are essential and useful for providing routing instructions to the visually impaired around work zones. Building on our previous efforts to provide geometry and signal timing to the visually impaired at signalized intersections, a smartphone-based navigation system was developed and integrated with navigational audible information to alert pedestrians at decision points prior to their arrival at a work zone. The recommended message elements from survey results were implemented in a smartphone app that uses GPS and Bluetooth technologies to determine a user's location. When a work zone is detected, the smartphone will vibrate to alert users and the app will then announce a corresponding audible message to users. The visually impaired users can perform a single tap on the smartphone to repeat the messages, if needed. Functionality testing and system validation of the smartphone app were performed by attaching four Bluetooth beacons to light posts near a construction site in St. Paul, MN. Additional research is needed to conduct experiments with visually impaired users and evaluate system reliability and usefulness.

This report builds on past efforts to analyze freight mobility and reliability by developing an analysis methodology using GPS data to study freight performance of heavy commercial trucks along 38 key freight corridors in the Twin Cities metropolitan area.

Weigh-In-Motion (WIM) system tends to go out of calibration from time to time, as a result generate biased and inaccurate measurements. Several external factors such as vehicle speed, weather, pavement conditions, etc. can be attributed to such anomaly. To overcome this problem, a statistical quality control technique is warranted that would provide the WIM operator with some guidelines whenever the system tends to go out of calibration. A mixture modeling technique using Expectation Maximization (EM) algorithm was implemented to divide the Gross Vehicle Weight (GVW) measurements of vehicle class 9 into three components, (unloaded, partially loaded, and fully loaded). Cumulative Sum (CUSUM) statistical process technique was used to identify any abrupt change in mean level of GVW measurements. Special attention was given to the presence of auto-correlation in the data by fitting an auto-regressive time series model and then performing CUSUM analysis on the fitted residuals. A data analysis software tool was developed to perform EM Fitting and CUSUM analyses. The EM analysis takes monthly WIM raw data and estimates the mean and deviations of GVW of class 9 fully loaded trucks. Results of the EM analyses are stored in a file directory for CUSUM analysis. Output from the CUSUM analysis will indicate whether there is any sensor drift during the analysis period. Results from the analysis suggest that the proposed methodology is able to estimate a shift in the WIM sensor accurately and also indicate the time point when the WIM system went out-of-calibration. A data analysis software tool, WIM Data Analyst, was developed using the Microsoft Visual Studio software development package based on the Microsoft Windows® .NET framework. An open source software tool called R.NET was integrated into the Microsoft .NET framework to interface with the R software which is another open source software package for statistical computing and analysis.

In order to reduce risky behavior around workzones, this project examines the effectiveness of using in-vehicle messages to heighten drivers' awareness of safety-critical and pertinent workzone information. This investigation centers around an inexpensive technology based on Bluetooth low-energy (BLE) tags that can be deployed in or ahead of the workzone. A smartphone app was developed to trigger nondistracting, auditory-visual messages in a smartphone mounted in a vehicle within range of the BLE workzone tags. Messages associated with BLE tags around the workzone can be updated remotely in real time and as such may provide significantly improved situational awareness about dynamic conditions at workzones such as: awareness of workers on site, changing traffic conditions, or hazards in the environment. Experiment results indicate that while travelling at 70 mph (113 km/h), the smartphone app is able to successfully detect a long-range BLE tag placed over 410 feet (125 meters) away on a traffic barrel on a roadway shoulder. Additional experiments are being conducted to validate the system performance under different roadway geometry, traffic, and weather conditions.

Report #9 in the series: Access to Destinations Study. Conventional transportation planning is often focused on improving movement (or mobility) - most often by the automobile. To the extent that accessibility, a well-known concept in the transportation planning field since the 1950s, has been measured or used in transportation planning, such measures have also been auto-based. Broadening the scope of accessibility to include a wide array of destinations and non-auto modes such as walking, cycling, and transit has been previously proposed as a much needed aim among planning initiatives. A central issue is that to date, however, there have been few examples of measures draw from. When it comes to bicycling, walking, and transit measures of accessibility are an endeavor long on rhetoric but short on execution. This report discusses such hurdles, presents alternatives for overcoming them, and demonstrates how accessibility for walking, cycling, and transit - and for different types of destinations - can be reliably measured. We focus on explaining specific features of non-motorized transportation that complicate the development of accessibility measures, and offer solutions that conform to conventional transportation planning practice. In this research project, non-motorized measures of accessibility were developed for the entire seven counties of the Twin Cities (Minnesota, USA) metropolitan area. For purposes of this exposition in this report, we discuss the details of creating such measures using a sample application from Minneapolis, Minnesota, USA to demonstrate proof of concept for the endeavor.

An ongoing research project examines guidance systems, which can take over control of a vehicle if the driver becomes incapacitated. Part of this project includes an evaluation of a Differential Global Positioning System (DGPS) for vehicle-based lane sensing. This report documents the results of tests of the 5 Hz NovAtel RT20 DGPS receiver. A series of 32 static tests found the overall mean and standard deviation for the offset errors within specifications. In a series of dynamic tests, in which the vehicle was driven around the track at speeds of 20-35 miles per hour, after removing the effect of the GPS receiver's latency, the DGPS determined position exhibited a mean offset error of -17.3 cm (-6.82 in) and a mean standard deviation of 25.5 cm (10.1 in) in the direction of vehicle motion. In the direction perpendicular to vehicle motion, the mean offset was 4.57 cm (1.8 in) with a mean standard deviation of 39.6 cm (15.6 in). With no overhead obstructions in these tests, continuous satellite lock was possible. Tests at higher speeds based on a more accurate methodology are planned for the future.

This presentation pertains to report 2015-18, Implementation of Traffic Data Quality Verification for WIM Sites.

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.

An inductive loop signature technology was previously developed by a US Department of Transportation (DOT) Small Business Innovation Research (SBIR) program to classify vehicles along a section of the roadway using existing inductive loop detectors installed under the pavement. It was tested and demonstrated in California that the loop signature system could obtain more accurate; reliable and comprehensive traffic performance measures for transportation agencies. Results from the studies in California indicated that inductive loop signature technology was able to re-identify and classify vehicles along a section of roadway and provide reliable performance measures for assessing progress; at the local; State; or national level. This study aimed to take advantage of the outcomes from the loop signature development to validate the performance with ground truth vehicle classification data in the Twin Cities Metropolitan Area (TCMA). Based on the results from individual vehicle class verification; class 2 vehicles had the highest match rate of 90%. Possible causes of classification accuracy for other vehicle classes may include types of loops; sensitivity of inductive loops that generates a shadow loop signal on neighboring lanes; and classification library that was built based on California data. To further understand the causes of loop signature performance and improve the classification accuracy; the author suggests performing additional data verification at a permanent Automatic Traffic Recorder (ATR) site. There is also an opportunity to investigate the classification algorithm and develop an enhanced pattern recognition methodology based on the raw loop signature profile of various types of vehicles in Minnesota.

Transportation agencies in the U.S. use devices such as loop detectors, automatic traffic recorders (ATR), or weigh-in- motion (WIM) sensors to monitor the performance of traffic network for planning, forecasting, and traffic operations. With a limited number of ATR and WIM sensors deployed throughout the state roadways, temporary double tubes are often deployed to get axle-based vehicle classification counts. An inductive loop signature technology previously developed by a Small Business Innovation Research (SBIR) program sponsored by the US Department of Transportation is used to classify vehicles using existing loops. This technology has the potential to save time and money while providing the state, counties or cities more data especially in the metro area where loop detectors have already been installed. This research leveraged the outcomes from previous development to validate the classification accuracy with video data. A loop signature system was initially installed at a traffic station in Jordan, MN, to evaluate its performance. The system was later moved to another location on US-52 near Coates, MN, to validate its classification accuracy with more heavy- vehicle traffic. Individual vehicle records were manually verified and validated with ground-truth video data using both the 13 and 7-bin classification schemes from the Federal Highway Administration (FHWA) and the Highway Performance Monitoring System (HPMS). The combined results from both test sites indicated that the loop signature technology had an overall classification accuracy of 93% and 96% using the FHWA and HPMS schemes, respectively. The classification performance can be further improved by including additional vehicle signatures from the state to the classification library.