Flaggers protect workers by providing temporary traffic control and maintaining traffic flow through a work zone. They are often the first line of defense to stop distracted, inattentive, or aggressive motorists from intruding into the work area. This project aims to develop an automated intrusion detection system to alert drivers who are unsafely approaching or entering a flagger-controlled work zone. A human factors user needs assessment found maintenance workers preferred a modified traffic signal to feature the alert system due to flagger risks of being in the roadway and drivers failing to stop and remain stopped when presented with the STOP side of the flagger sign. A modified traffic signal that could be operated using a handheld remote was developed. The low-cost embedded electronics on the traffic signal enabled it to track trajectories of nearby vehicles, detect potential intrusions, and trigger audio-visual warnings to alert the intruding driver. Usability testing in a simulated driving test found poor expectancies and stopping rates of the traffic signal-based alarm system compared to a traditional flagger but did demonstrate evidence that drivers may be less likely to stop and remain stopped with the flagger STOP sign than the red ball indicator of the traffic signal. Furthermore, some drivers corrected their initial stopping error after triggering the auditory alarm of the traffic signal. A follow up test found improved performance with the alert system incorporated into an audiovisual enhanced STOP/SLOW flagger paddle. Testing of the developed sensor system found the system capable of simultaneous multi-vehicle tracking (including estimation of vehicle position, velocity, and heading) with a range of up to 60 meters and angular azimuth range of 120 degrees and correctly detecting all test intruding vehicles.
This project involved the development of a fault diagnostic system for Safetruck, an intelligent vehicle prototype. The fault diagnostic system continuously monitors the health of vehicle sensors, detects a failure when it happens, and identifies the source of the failure. The fault diagnostic system monitors several key components: the Global Positioning System, lateral accelerometer, and yaw-rate gyroscope, which constitute the set of lateral dynamic sensors, as well as the forward-looking radar that measures distance relative velocity, and azimuth angle to other vehicles and objects on the highway. To design the project's lateral fault diagnostic system, researchers exploited the model-based dynamic relationships that exist between the three lateral sensors. They verified the system's performance through extensive experiments on the Safetruck. This project also explored a number of new approaches to creating a reliable fault detection system for radar. Monitoring the radar's health poses a special challenge because the radar measures the distance to another independent vehicle on the highway. In the absence of inter-vehicle communications, the fault diagnostic system has no way of knowing the other vehicle's motion, which means that model-based approaches cannot be used. Experimental results indicate that an inexpensive redundant sensor combined with a specially designed nonlinear filter would provide the most reliable method for radar health monitoring.
This project concentrates on the development of real- time tire-road friction coefficient estimation systems for snowplows that can reliably estimate different road surface friction levels and quickly detect abrupt changes in friction coefficient. Two types of systems are developed - a vehicle-based system and a wheel-based system. The vehiclebased friction measurement system utilizes vehicle motion measurements from differential GPS and other on-board vehicle sensors. The wheel-based friction measurement system utilizes a redundant wheel that is mounted at a small angle to the longitudinal axis of the vehicle. Complete technical details on the vehicle-based friction measurement system are presented in this report. Compared to previously published results in literature, the advantage of the vehicle-based system developed here is that it is applicable during both vehicle acceleration and braking and works reliably for a wide range of slip ratios, including high slip conditions. The system can be utilized on front/rear-wheel drive as well as all- wheel drive vehicles. Extensive results are presented from experimental results conducted on various surfaces with a winter maintenance vehicle called the "SAFEPLOW." The experimental results show that the system performs reliably and quickly in estimating friction coefficient on different road surfaces during various vehicle maneuvers.
The overarching goal of this project was to instrument the new MnDOT Navistar truck used at MN Road. A rugged data acquisition, data recording and wireless transmission system was established for collection of various sensor signals from the truck. The truck was instrumented with a suite of 20 accelerometers, with these accelerometers being located both on the five axles of the truck and on the tractor and trailer bodies. In addition, the truck was instrumented with a differential GPS system and an inertial measurement unit in the tractor cab. A cRIO-based data acquisition system, a rugged laptop and Labview software together serve as a flexible platform for data acquisition. A wireless communication system has been established to communicate trigger signals to roadside cabinets when the truck is at desired GPS locations on the road. Data recording by in-pavement sensors is triggered by this system. Software has also been set up for automatic downloading of data from the truck to a server on the network at MN Road. The experimental performance of the developed system has been verified by multiple tests conducted by the research team. The above instrumentation of the truck will enable data collection on truck vibrations, enable analysis of correlations between truck vibrations and variations in signals of weigh-inmotion sensors, and enable recording of truck movements and pavement loads at MnROAD.
A friction measurement system was developed for Polk County and installed on two snowplows in the county's winter road-maintenance fleet. The major components of the developed system were a special instrumented wheel, a pneumatic pressure-controlled cylinder, force-measurement load cell and accelerometers, a data collection microprocessor and a data processing micro-processor. The road friction coefficient was estimated in real-time and was stored on a secure digital card along with the current GPS-sensed location of the truck. The friction coefficient information was also displayed in real-time using LED lights for the operator. Although the basic design of the friction wheel system had been used for several previous years of intermitant testing without showing significant wear, the almost identical installations on the Polk County trucks suffered bearing failures after the first few days of continuous use. The failed bearings were replaced with larger bearings in a more robust mount. Apparently, the system again failed in a few days, but the research team did not learn of this failure until the end of the project. The low budget for the project and the significant travel required to go to Crookston posed major challenges in getting a friction measurement to work effectively for Polk County.
This project focused on the enhancement and evaluation of a battery-less wireless weigh-in-motion (WIM) sensor for improved enforcement of road weight restrictions. The WIM sensor is based on a previously developed vibration energy harvesting system, in which energy is harvested from the vibrations induced by each passing vehicle to power the sensor. The sensor was re-designed in this project so as to reduce its height, allow it to be installed and grouted in an asphalt pavement, and to protect the piezo stacks and other components from heavy shock loads. Two types of software interfaces were developed in the project: a) An interface from which the signals could be read on the MnDOT intranet b) An interface through a wireless handheld display Tests were conducted at MnRoad with a number of test vehicles, including a semi tractor-trailer at a number of speeds from 10 to 50 mph. The sensor had a monotonically increasing response with vehicle weight. There was significant variability in sensor response from one test to another, especially at the higher vehicle speeds. This variability could be attributed to truck suspension vibrations, since accelerometer measurements on the truck showed significant vibrations, especially at higher vehicle speeds. MnDOT decided that the final size of the sensor was too big and could pose a hazard to the traveling public if it got dislodged from the road. Hence the task on evaluation of the sensor at a real-world traffic location was abandoned and the budget for the project correspondingly reduced.
The first part of this project conducted a detailed evaluation of the ability of a new friction measurement system to provide an accurate measure of road conditions. A system that records friction coefficient as a function of road location was developed using the same vehicle location measurement system as the current MDSS project. Studies conducted show that the friction measurement system provides a significantly more reliable measure of road surface conditions than does visual inspection. The second part of this project focused on a detailed evaluation of the performance of a closed-loop system that utilizes friction measurement for automatic applicator control. Experimental studies have shown that a friction measurement based zero velocity sander can adequately apply salt/chemicals to all slippery spots on a road at speeds up to 25 mph. The final part of this project focused on enhancement of the developed automatic applicator control system with utilization of real-time data from a geographical information system that provides information on upcoming geometric road alignment and known problematic segments of roadway. The developed friction measurement, data recording and applicator control system is compact, modular and can be used on both snowplows and pick-up trucks.
This project focuses on experimental tests of the performance characteristics of autonomous vehicles (AVs) on highways and local roads in Minnesota. The project provides detailed data characterizing AV performance, which in turn can be used to inform the transportation community on implications for infrastructure maintenance, winter road maintenance, work zone guidelines, safety, and traffic capacity. The experimental work presented here makes use of a new autonomous vehicle purchased by the Center for Transportation Studies at the University of Minnesota. The key aspects of the autonomous functions of the vehicle studied in this project include winter performance and implications for road maintenance, characterization of the driving performance of the AV and its likely influence on safety, traffic flow and fuel economy, and the ability of the AV to handle work zones and the implications on changes needed to the guidelines for work zones. The project documents the major challenges and obstacles ahead in the way of true autonomy on Minnesota roads, but also outlines further areas for research with which it will be possible to facilitate the improvement of the capabilities of autonomous vehicles in Minnesota in the future.
Real-time measurement of tire-road friction coefficient is extremely valuable for winter road maintenance operations and can be used to optimize the kind and quantity of the deicing and anti-icing chemicals applied to the roadway. In this project, a wheel based tire-road friction coefficient measurement system is first developed for snowplows. Unlike a traditional Norse meter, this system is based on measurement of lateral tire forces, has minimal moving parts and does not use any actuators. Hence, it is reliable and inexpensive. A key challenge is quickly detecting changes in estimated tire-road friction coefficient while rejecting the high levels of noise in measured force signals. Novel filtering and signal processing algorithms are developed to address this challenge including a biased quadratic mean filter and an accelerometer based vibration removal filter. Detailed experimental results are presented on the performance of the friction estimation system on different types of road surfaces. Experimental results show that the biased quadratic mean filter works very effectively to eliminate the influence of noise and quickly estimate changes in friction coefficient. Further, the use of accelerometers and an intelligent algorithm enables elimination of the influence of driver steering maneuvers, thus providing a robust friction measurement system. In the second part of the project, the developed friction measurement system is used for automated control of the chemical applicator on the snowplow. An electronic interface is established with the Force America applicator to enable real-time control. A feedback control system that utilizes the developed friction measurement sensor and a pavement temperature sensor is developed and implemented on the snowplow.