Petersen, Scott

The Local Road Research Board (LRRB), with assistance from Sibley County and the Minnesota Department of Transportation (MnDOT), conducted a field evaluation of traffic data collection sensors. This study was initiated to explore low-cost and non-intrusive options to collect traffic data as possible alternatives to traditional methods such as tube counts, which require personnel to work close to or on the roadway rather than from a safer roadside position, as some non-intrusive sensors allow. This project reviewed new developments and alternatives to conventional road tube, inductive loop and piezo sensor data collection. This project conducted a comparison of multiple traffic data collection sensors along on a rural two-lane road with low traffic volumes (Sibley County State Aid Highway 9) in both winter and spring conditions. The project gathered information on ease of deployment, accuracy, and costs associated with each technology. The following sensors were installed and monitored as part of this study: Countingcars.com COUNTcam, Miovision Scout, JAMAR Radar Recorder, Wavetronix SmartSensor HD, Houston Radar Armadillo Tracker, Sensys VSN240F (Sensys), JAMAR Stealth Stud, Road Tubes with PicoCount 2500 classifier

The Minnesota Department of Transportation (MnDOT) collects traffic volume counts for cities and counties outside of the Twin Cities Metro Area. Volume “coverage” counts are performed on various roads including trunk highways, county roads, county state aid highways, and municipal state aid streets. The counts assist with planning, design, development, maintenance priorities and snow removal. This research implementation project considered options for cities and counties to gather traffic data; the focus of this project was to shadow three data collection processes. The three collection processes include MnDOT collecting the data (current process), the respective county collecting the data with equipment and training provided by MnDOT, and a consultant collecting the data. Sibley County volunteered to administer the county data collection process. MnDOT data collection is generally collected by District field technicians. The Sibley County data collection was conducted by County staff including an engineering intern. After the data collection process, each organization was interviewed to determine the effectiveness of the data collection method. A quantitative analysis determined how long each organization spent per count site.

This Guidebook contains information that should be useful to engineers as they consider alternative solutions to traffic safety concerns at side-street STOP controlled intersections. It is the intent of this guide to provide the engineer information to aid in the consideration, selection and deployment of LED STOP signs and ICWS at these intersections. These safety strategies should be included for consideration along with other safety improvements detailed in the TEM and Traffic Safety Fundamentals Handbook such as improving visibility of the intersection with improved signing, pavement marking, and intersection lighting; improving sight distance by providing clear sight triangles on all approaches; selecting appropriate traffic control such as ALL WAY STOP; and reduce conflict points through geometric design such as turn lanes or bypass lanes. Final Report.

In 2015 and 2016; the Minnesota Department of Transportation (MnDOT) installed network video dash- and ceiling-mounted cameras on 226 snowplows; approximately one-quarter of MnDOT's total snowplow fleet. The cameras were integrated with the onboard mobile data computer/automated vehicle location (MDC/AVL) equipment and automatically captured snapshots of road conditions during plowing. Images were sent to MnDOT's server and then imported in near-real-time to the MnDOT 511 website and MnDOT mobile app for use by the traveling public. This report details operational and technical considerations for various aspects of plow camera and 511 image integration deployment. It also includes perspectives from plow drivers; their supervisors; management in charge of deploying this project and members of the public. Project completion barriers; solutions and recommendations are included. Based on the successful deployment of this system; MnDOT recommends wider use of this equipment throughout MnDOT's snowplow fleet.

Conventional methods for detecting vehicles for permanent travel monitoring stations have relied on detecting physical attributes of vehicles without correlating these with the specific vehicles and/or motor vehicle freight operators. However, by using a license plate reader camera, information can be gathered and cross referenced to other known data related to the specific vehicle assigned to the license plate. This could provide additional tools for enforcing overweight vehicles or targeting enforcement communication with freight carriers that consistently violate weight limits. The analysis conducted during this project compared machine-read license plates to manually collected license plates. The license plates were read as vehicle travelled highway speeds in a generally uncontrolled environment. Analysis is also provided that correlates hours of direct sunlight with accuracy of the automated reader. A second analysis was conducted as an effort to improve the accuracy of the Minnesota Department of Transportation's weigh-in-motion classification scheme and bring it in line with the Department's classification scheme for automatic traffic recorder stations (sites with axle-based detection that do not collect weight information).

The Minnesota Local Road Research Board, MnDOT, and SRF performed an evaluation of a portable weigh-inmotion (WIM) system at several locations throughout Minnesota. The system was developed at the University of Minnesota-Duluth and offers roadway designers a low-cost method for obtaining vehicle load distribution data across the state's road network. To deploy the system, the weigh pads of the system were temporarily affixed sensors across the roadway lanes. As vehicles passed over the weigh pads, pressure sensors within the pads detected the weight of vehicles and the system recorded the data for later analysis. Traditional methods for travel monitoring generate traffic volume and classification data, but weigh-in-motion systems give designers a more accurate idea of current and projected traffic loading demands. SRF's testing provided implementation refinements that were incorporated into the system. During the two-year deployment process, the portable WIM system was installed under a wide array of environmental conditions to demonstrate the system's capabilities. Data generated by the system was analyzed. The Final Report details system deployment, calibration, and system accuracy.