Methodology Update for Estimating Volume to Service Flow Ratio

Volume/service flow ratio (VSF) is calculated by the Highway Performance Monitoring System (HPMS) software as an indicator of peak hour congestion. It is an essential input to the Kentucky Transportation Cabinet’s (KYTC) key planning applications, such as highway adequacy rating. After the Federal Highway Administration (FHWA) reassessed the HPMS, the standalone HPMS software was no longer supported. This conclusion was based on the 2000 Highway Capacity Manual (HCM2000). As a result, the peak capacity and VSF estimates based on the submittal file are no longer available to KYTC. The calculation of VSF ratios requires AADT, K factor, directional factor, and peak capacity as inputs. Previously, peak capacity was calculated by the HPMS software. The calculation method had limitations; it did not take into consideration certain information that may affect the VSF, such as the availability of a truck-climbing lane. Researchers in this study developed a Microsoft Access-based tool for KYTC that estimated peak capacity and VSF. They adapted the approach to ensure compliance with HCM2010. The tool required pre-processing the HIS extract to eliminate empty cells by either excluding segments with missing data or by imputing the values of the missing item(s). Often, a short segment was misclassified as a multilane highway or an urban two-lane or three-lane facility. Analyses indicated that VSF can provide a modest amount of information on a segment’s level of traffic congestion. However, it does not reflect variations in travel time (or speed), which may greatly contribute to user experience on the highway. A post-processing step may also be needed to mitigate the impact of short segments in the input data. The future of VSF as the sole measure of congestion performance should be evaluated

Quantifying the Impact of Weather Events on Travel Time and Reliability

It is of practical significance to understand the specific impact of weather events on the operating condition of the surface transportation system so that proactive and reactive strategies can be quickly implemented by transportation agencies to minimize the negativity resulted from adverse weather events. Many studies have been conducted on quantifying such effects yet suffer from limitations such as subjectively defining a time window under uncongested conditions and not being able to account for the severe impact from weather events which result in travel time unreliability. To overcome those shortcomings in existing literature, an integrated data mining framework based on decision tree and quantile regression techniques is developed in this study. The results demonstrate that the approach is effective in characterizing time periods with different traffic characteristics and quantifying the impact of rain and snow events on both congestion and reliability aspects of the transportation system. It is observed that snow events impose more significant impact on travel times than that from rain events. In addition, the impact from weather events is even more severe on travel time reliability than average delay. The impact magnitude is directly related to the level of recurrent congestion under study. Other insights with regard to the capability of quantile regression and future improvement on the methodological design are also offered

Collection and Analysis of 2013-2014 Travel Time Data

This report documents the findings of Planning Study 27, Collection and Analysis of 2013-2014 Travel Time Data, which is a continuation of Planning Study 24, Analysis of Historical Travel Time Data. The main scope is to analyze newly acquired link-referenced speed data on Kentucky roads from 2013 and 2014. Results of the analysis demonstrate the value of probe data in measuring and tracking the performance of roadways across several years. In addition, such data can help KYTC and MPOs identify bottlenecks in the network, prioritize improvement strategies, and assess the effectiveness of projects. As data collection techniques advance, the coverage and quality of probe data will continue to improve. It is advisable for KYTC to maintain a steady stream of such data to assist with data-driven decision making for a variety of applications

A Calibration Method for Wide Field Multicolor Photometric System

The purpose of this paper is to present a method to self-calibrate the spectral energy distribution (SED) of objects in a survey based on the fitting of an SED library to the observed multi-color photometry. We adopt for illustrative purposes the Vilnius (Strizyz and Sviderskiene 1972) and Gunn & Stryker (1983) SED libraries. The self-calibration technique can improve the quality of observations which are not taken under perfectly photometric conditions. The more passbands used for the photometry, the better the results. This technique has been applied to the BATC 15-passband CCD survey.Comment: LateX file, 1 PS file, submitted to PASP number 99-025 The English has been improved and some mistakes have been correcte