详情

原文传递 Animal-Vehicle Collision Data Collection.

题名：	Animal-Vehicle Collision Data Collection.
关键词：	highway safety,vehicle animal collisions,mitigation/surveys, data collection, united states, canada, wildlife, natural resources management, transportation departments/
摘要：	Animal-vehicle collisions (AVCs) affect human safety, property, and wildlife, and the number of AVCs has substantially increased across much of North America over the last several decades. Systematically collected AVC data help estimate the magnitude of the problem and help record potential changes in AVCs over time. Such data also allow for the identification and prioritization of locations that may require mitigation. In addition, systematically collected AVC data allow for the evaluation of the effectiveness of mitigation measures in reducing the number of AVCs. In the United States and Canada, AVC at are typically collected by transportation agencies, law enforcement agencies, and/or natural resource management agencies. These activities result in two types of data: data from accident reports (AVC data) and data based on animal carcass counts (AC data). However, not all transportation agencies, law enforcement agencies, and/or natural resource management agencies record these types of data. Furthermore, the agencies that do record such data often use different methods, resulting in difficulties with data integration and interpretation, and ultimately with the usefulness of the data. This synthesis examines the extent to which AVC and AC data are collected, analyzed,and used across the United States and Canada. The data were obtained through a survey of departments of transportation (DOTs) and departments of natural resource management(DNRs) for each state or province. For DOTs and DNRs combined, the response rate was 89%(56 of 63 states and provinces).Most DOTs and DNRs collect or manage AVC or AC data, or both. Most AVC data are actually collected by law enforcement agencies, whereas AC data are typically collected by the DOTs and DNRs themselves. The two agency types have a some what different motivation for collecting the data. DOTs primarily collect data to improve human safety (AVC and AC data), for accounting reasons (AC data), and, to a lesser extent, for wildlife conservation reasons (AC data). DNRs are motivated by a mixture of human safety and wildlife conservation concerns (AVC data) or primarily by wildlife conservation concerns (AC data). Both AVC and AC data typically have reporting thresholds. In addition, the search and reporting effort of the programs varies tremendously between states and provinces and is not always consistent within a state or province. Furthermore, there is an emphasis on large wild and domesticated animals (deer size and larger), especially in AC data collection programs.These factors typically lead to a substantial under estimation of collisions with animals, both for AVC and AC data. DOTs typically train their employees in collecting information on date and location of the AVC or AC, but they do not necessarily train their employees in the identification of the species or any other animal-related parameters. DNRs rarely provide training to their personnel, but if they do it is often concerned with animal-related parameters such as species identification, sex, age, and sometimes necropsy. Based on these results, additional training for DOT personnel may have to place more emphasis on animal-related parameters, especially species identification, whereas training for DNR personnel may have to be initiated altogether. / NOTE: Final rept. for 27 Sep 01-26 Dec 04. / Supplementary Notes: Prepared in cooperation with Texas Transportation Inst., College Station. Sponsored by John A. Volpe National Transportation Systems Center, Cambridge, MA. and Federal Highway Administration, McLean, VA. / Availability Note: Order this product from NTIS by: phone at 1-800-553-NTIS (U.S. customers); (703)605-6000 (other countries); fax at (703)605-6900; and email at orders@ntis.gov. NTIS is located at 5285 Port Royal Road, Springfield, VA, 22161, USA.
报告类型：	科技报告