Highway Maintenance Concept Vehicle, June 2002

This report documents Phase IV of the Highway Maintenance Concept Vehicle (HMCV) project, a pooled fund study sponsored by the Departments of Transportation of Iowa, Pennsylvania, and Wisconsin. This report provides the background, including a brief history of the earlier phases of the project, a systems overview, and descriptions of the research conducted in Phase IV. Finally, the report provides conclusions and recommendations for future research. Background The goal of the Highway Maintenance Concept Vehicle Pooled Fund Study is to provide travelers with the level of service defined by policy during the winter season at the least cost to taxpayers. This goal is to be accomplished by using information regarding actual road conditions to facilitate and adjust snow and ice control activities. The approach used in this study was to bring technology applications from other industries to the highway maintenance vehicle. This approach is evolutionary in that as emerging technologies and applications are found to be acceptable to the pooled fund states and as they appear that to have potential for supporting the study goals they become candidates for our research. The objective of Phase IV is to: Conduct limited deployment of selected technologies from Phase III by equipping a vehicle with proven advanced technologies and creating a mobile test laboratory for collecting road weather data. The research quickly pointed out that investments in winter storm maintenance assets must be based on benefit/cost analysis and related to improving level of service. For example, Iowa has estimated the average cost of fighting a winter storm to be about $60,000 to $70,000 per hour typically. The maintenance concept vehicle will have advanced technology equipment capable of applying precisely the correct amount of material, accurately tailored to the existing and predicted pavement conditions. Hence, a state using advanced technology could expect to have a noticeable impact on the average time taken to establish the winter driving service level. If the concept vehicle and data produced by the vehicle are used to support decision-making leading to reducing material usage and the average time by one hour, a reasonable benefit/cost will result. Data from the friction meter can be used to monitor and adjust snow and ice control activities and inform travelers of pavement surface conditions. Therefore, final selection of successfully performing technologies will be based on the foundation statements and criteria developed by the study team.

Spatial Scale of Clustering of Motor Vehicle Crash Types and Appropriate Countermeasures, 2009

This project analyzes the characteristics and spatial distributions of motor vehicle crash types in order to evaluate the degree and scale of their spatial clustering. Crashes occur as the result of a variety of vehicle, roadway, and human factors and thus vary in their clustering behavior. Clustering can occur at a variety of scales, from the intersection level, to the corridor level, to the area level. Conversely, other crash types are less linked to geographic factors and are more spatially “random.” The degree and scale of clustering have implications for the use of strategies to promote transportation safety. In this project, Iowa's crash database, geographic information systems, and recent advances in spatial statistics methodologies and software tools were used to analyze the degree and spatial scale of clustering for several crash types within the counties of the Iowa Northland Regional Council of Governments. A statistical measure called the K function was used to analyze the clustering behavior of crashes. Several methodological issues, related to the application of this spatial statistical technique in the context of motor vehicle crashes on a road network, were identified and addressed. These methods facilitated the identification of crash clusters at appropriate scales of analysis for each crash type. This clustering information is useful for improving transportation safety through focused countermeasures directly linked to crash causes and the spatial extent of identified problem locations, as well as through the identification of less location-based crash types better suited to non-spatial countermeasures. The results of the K function analysis point to the usefulness of the procedure in identifying the degree and scale at which crashes cluster, or do not cluster, relative to each other. Moreover, for many individual crash types, different patterns and processes and potentially different countermeasures appeared at different scales of analysis. This finding highlights the importance of scale considerations in problem identification and countermeasure formulation.

Highway Maintenance Concept Vehicle Final Report: Phase Three, 2001

This report documents Phase III of a four-phase project. The goals of the project are to study the feasibility of using advanced technology from other industries to improve he efficiency and safety of winter highway maintenance vehicle operations, and to provide travelers with the level of service defined by policy during the winter season at the least cost to the taxpayers. The results of the first phase of the research were documented in the Concept Highway Maintenance Vehicle Final Report: Phase One dated April 1997, which describes the desirable functions of a concept maintenance vehicle and evaluates its feasibility. Phase I concluded by establishing the technologies that would be assembled and tested on the prototype vehicles in Phase II. The primary goals of phase II were to install the selected technologies on the prototype winter maintenance vehicles and to conduct proof of concept in advance of field evaluations planned for Phase III. This Phase III final report documents the work completed since the end of Phase II. During this time period, the Phase III work plan was completed and the redesigned friction meter was field tested. A vendor meeting was held to discuss future private sector participation and the new design for the Iowa vehicle. In addition, weather and roadway condition data were collected from the roadway weather information systems at selected sites in Iowa and Minnesota, for comparison to the vehicles' onboard temperature sensors. Furthermore, the team received new technology, such as the mobile Frensor unit, for bench testing and later installation.