Combining Performance, Demand, Incident, and Roadway Characteristics Data for Freight Bottleneck Identification
Corresponding Author: Sebastian Guerrero, WSP
Presented By: Sebastian Guerrero, WSP
Abstract
Developing a ground-level understanding of the operational bottlenecks faced by the trucking sector is a key part of freight planning. This has become easier in recent years with the proliferation of different disaggregated freight data sets, however questions remain about how best to interpret and combine them to prioritize public sector investments. To address this, a comprehensive framework was developed for the Oregon DOT that: (1) translates different data sources (NPMRDS, HERS-ST, Incident Records, and Travel Demand Model) into a single spatial-analytical platform; (2) defined 12 tangible indicators measuring elements such as delay, unreliability and estimating delay costs; and (3) established a hierarchy of thresholds to identify bottlenecks. This approach is innovative in that it combines a variety of data sources to develop indicators that make sense to stakeholders, such as delay and unreliability. It also uses secondary indicators such as the severity of grades and frequency of crashes to corroborate and explain the results observed from speed and reliability data. Subsequent workshops with freight and trucking representatives validated preliminary results of the analysis.