http://hdl.handle.net/2027.42/13914 http://deepblue.lib.umich.edu/retrieve/94910 http://hdl.handle.net/2027.42/13914 Search the Channel search http://deepblue.lib.umich.edu/simple-search http://hdl.handle.net/2027.42/64436 Title: Market models for predicting PHEV adoption and diffusion<br/><br/>Authors: Senter, R. Jr.; McManus, W.<br/><br/>Abstract: This is the final report on market models for predicting Plug-In Hybrid Electric Vehicles (PHEV) adoption. The work was one of the tasks carried out by the University ofMichigan on the technical challenges of PHEVs and impacts to the U.S. power system. We first examine benchmark market models with fixed saturation levels. On balance, we conclude that their weaknesses dominate their strengths. We then examine two alternative approaches to predicting PHEV adoption and diffusion using models without a fixed saturation level: Centrone et al. (2007) and the consideration-purchase model (suggested by Struben and Sterman (2008)). The consideration-purchase model makes the market behavior of consumers the focus of attention, and it is our preferred market model. http://hdl.handle.net/2027.42/64345 Title: Evaluation of 2008 Vermont crash data reported to the MCMIS crash file<br/><br/>Authors: Blower, Daniel; Matteson, Anne<br/><br/>Abstract: This report is part of a series evaluating the data reported to the Motor Carrier Management Information System (MCMIS) Crash File undertaken by the Center for National Truck and Bus Statistics at the University of Michigan Transportation Research Institute. The earlier studies showed that reporting to the MCMIS Crash File was incomplete. This report examines the factors that are associated with reporting rates for the state of Vermont.MCMIS Crash File records were matched to the Vermont crash file to determine the nature and extent of underreporting. It was necessary to focus just on crashes involving a fatality, A-injury or B-injury, because of problems identifying MCMIS reportable crashes in the Vermont crash file. It appears that Vermont reported 64.9 percent of these crash involvements in 2008.Reporting rates were found to be related to crash severity, the configuration of the vehicle, and the type of enforcement agency that covered the crash. Over 71 percent of fatal crash involvements were reported, 54.5 percent of A-injury involvements, and 67.1 percent of B-injury involvements. More than 66 percent of reportable involvements of truck involvements were reported, but the reporting rate was 50.0 percent for buses.Missing data rates are low for most variables. Corresponding data elements in the MCMIS and Vermont crash files were reasonably consistent, though all cases reported as truck with trailer in the MCMIS file were recorded as tractor-semitrailers in the Vermont crash file. http://hdl.handle.net/2027.42/64283 Title: Safety benefits of stability control systems for tractor- semitrailers<br/><br/>Authors: Woodrooffe, J; Blower, D.; Gordon, T.; Green, P. E.; Liu, B.; Sweatman, P.<br/><br/>Abstract: This study was conducted by the University of Michigan Transportation Research Institute(UMTRI) under a Cooperative Agreement between NHTSA and Meritor WABCO to examinethe performance of electronic stability control (ESC) systems, and roll stability control (RSC) systems for heavy-truck tractor-semitrailers. The study is based on the analysis of independent crash datasets using engineering and statistical techniques to estimate the probable safety benefits of stability control technologies for 5-axle tractor-semitrailer vehicles. Theconventional approach for assessing the safety benefits of vehicle technologies is to analyze crash datasets containing data on the safety performance of vehicles equipped with the technology of interest. Because the deployment of the stability technologies for large trucks is in its infancy, national crash databases do not yet have a sufficient amount of factual data that can be directly linked to the performance of the technology. Therefore a novel method of examining the potential benefits of these systems was used. Crash scenarios that could likelybenefit from the technologies were selected from national crash databases and the probable effectiveness of each technology was estimated. The analysis in this study did not have the advantage of examining representative crash datasets that contain identifiable data from vehicles equipped with the technology. Therefore, the analysis was based on probable outcome estimates derived from hardware-in-the-loop simulation, field test experience, expert panel assessment, and fleet crash data and these methods were used to estimate the safety benefits from the national crash data population. http://hdl.handle.net/2027.42/64281 Title: Relationships between lighting and animal-vehicle collisions<br/><br/>Authors: Sullivan, J. M.<br/><br/>Abstract: In 1990, there were 106 traffic fatalities in the United States in crashes for which a collision with an animal was the first harmful event; by 2007 this level had risen to 223—a 110% increase. Analyses ofannual trends suggest that this increase cannot be fully explained by increases in vehicle miles travelled, nor by changes in the general fatal and nonfatal crash rates. Animal-vehicle collisions (AVCs) representa small but increasing share of the overall crash picture.Daily and seasonal AVC crash trends were examined and appear to follow the activity patterns of the U.S. deer population. This involves peaks in the hourly crash levels around dawn and dusk, and a seasonal peak during October and November. AVC crash distributions are presented by state.The odds of an AVC in darkness were modeled as a function of posted speed limit in a series of logistic regressions. Higher posted speeds were associated with proportionally greater crash risk in darkness.The effect is observed for fatal collisions compiled from the Fatality Analysis Reporting System (FARS), and for injury and property-damage-only (PDO) crashes compiled from Michigan crash datasets. One implication of the effect is that countermeasures designed to extend a driver’s preview time for animals, such as headlighting and night-vision systems may help reduce the risk of AVCs.