详情

Develop Local Functional Classification VMT and AADT Estimation Method

项目名称：	Develop Local Functional Classification VMT and AADT Estimation Method
摘要：	Rapid growth in population over the past two decades has led to an increase in travel demand, resulting in congestion and an exponential increase in conflicts that arise because of human interaction, off- and on network characteristics, and other associated factors. To better cater the increase in demand and reduce congestion, a federally-funded, state-administered program known as Highway Safety Implementation Program (HSIP) is legislated. The goal of HSIP is to achieve a significant reduction in fatalities and serious injuries on public roads. One of the requirements of HSIP for state agencies is to report Annual Average Daily Traffic (AADT) on all paved public roads (includes functionally classified major and local roads) and develop safety performance measures. A significant amount of resources (time and money) are spent by agencies to collect AADT on these road links. However, resource constraints limit agencies from collecting AADT data for all the links, particularly local functionally classified public roads. Such limitations can be offset using robust models that help estimate AADT on functionally classified major and local roads. The objectives of the proposed research project are: 1) to review AADT and vehicle miles traveled (VMT) generation methods for functionally classified major and local roads, along with how other state departments of transportation (DOTs) are meeting the HSIP AADT requirements, 2) to identify requirements to quantify VMT on local functionally classified roads, 3) to develop sustainable and repeatable models to estimate VMT for local functionally classified roads by area type (region, Division or County), 4) to monitor requirements so as to validate and calibrate the models to improve their predictive performance, and, 5) to estimate statewide local VMT (in tabular and geospatial formats) as well as to develop and recommend growth factors for continuously estimating AADT and VMT of local functionally classified roads. The proposed scope of work involves 1) reviewing past research and current practices on AADT and VMT generation methods, 2) surveying other states on how they meet HSIP AADT requirements and identify requirements of VMT, 3) collecting adequate data based on statistical sampling techniques, 4) developing state-, area-, and link-level (route-level) models to estimate AADT and VMT, 5) validating and calibrating the models developed, 6) estimating statewide local AADT and VMT (tabular and geospatial formats) along with respective growth factors for future computations, and, 7) preparing and submitting a final report. The research team has vast experience with analysis of count data, development of AADT estimation methods, use of Geographic Information Systems (GIS) features to capture geospatial data, and generating statistical models. This expertise and experience will be an asset and ensure that North Carolina Department of Transportation's (NCDOT�s) goals and objectives to generate AADT on local functionally classified roads for use with HSIP and Highway Performance Monitoring System (HPMS) are met.
状态：	Active
资金：	165931
资助组织：	North Carolina Department of Transportation
管理组织：	North Carolina Department of Transportation
项目负责人：	Penny, Lisa E.
执行机构：	University of North Carolina - Charlotte
主要研究人员：	Pulugurtha, Srinivas S
开始时间：	20180801
预计完成日期：	20200531
实际结束时间：	0