01764065

Component

https://annualmeeting.myt...nlineProgram/Details/15461

Travel time reliability is known as the temporal variability of travel time and influences many aspects of the traveler’s decisions, especially in roadway transport. This study aims to take a step in this direction by providing a tool to analyze the effect of transportation network improvements on travel time reliability. The primary issue that the authors address in this study is to find out how the reduction in the number of lanes, crashes, and traffic volume influence travel time reliability on interstate highways in Virginia. This study uses the data extracted from the INRIX for the interstate highways in the state of Virginia. The authors have examined different supervised data mining and Machine Learning (ML) algorithms to find the most promising tool and incorporated the results into an analysis toolbox. The results have shown to be satisfactory for modeling moderate travel time variations.

This paper was sponsored by TRB committee AED20 Standing Committee on Urban Transportation Data and Information Systems.

TRBAM-21-00150

English

17p

2021

Transportation Research Board 100th Annual Meeting

Digital/other

Figures; Maps; References; Tables

Data mining; Interstate highways; Machine learning; Mathematical models; Reliability; Sensitivity analysis; Travel time

INRIX

Virginia

Highways; Planning and Forecasting

Transportation Research Board Annual Meeting 2021 Paper #TRBAM-21-00150

TRIS, TRB, ATRI

Dec 23 2020 11:18AM