More From Miguel Figliozzi et al.

Exploiting New Data Sources to Quantify Arterial Congestion and Performance Measures at a Regional Scale By Miguel Figliozzi
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Travel time and operating speed influence transit service attractiveness, operating cost and system efficiency. As part of their bus dispatch system (BDS), the Tri-County Metropolitan Transportation... More > District of Oregon (TriMet) has been archiving automatic vehicle location (AVL) and automatic passenger count (APC) data for all bus trips at the stop level since 1997. In 2014, a new and higher-resolution bus AVL data collection system was fully implemented. The new AVL system provides stop-level data as well as five-second resolution (5-SR) bus position data between stops. This research project explored potential applications of the new data for assessing transit performance and for estimating transportation system performance measures for urban streets and arterials. Results suggest that the 5-SR data provides high-resolution time and position information which can be used to determine bus travel speeds between bus stops, identify speed breakdowns, and estimate intersection signal/queuing delays.< Less
Modeling and Analyzing the Impact of Advanced Technologies on Livability and Multimodal Transportation Performance Measures in Arterial Corridors By Miguel Figliozzi
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Since pedestrians are particularly vulnerable when drivers do not yield at crosswalks, the focus of this research is to understand the factors that are associated with low yield rates or crosswalk... More > law non-compliance. In this context, the goal of this research is to study the traffic speed and vehicle trajectory factors that affect crosswalk law compliance and stopping distance from the crosswalk. The results of this research provide new insights into the relationships between traffic conditions, vehicle trajectory and compliance rates. Results indicate that vehicle origin, vehicle type, stopping at upstream traffic lights, and changes in vehicle speed and headways are key factors to predict pedestrian crosswalk law compliance and stopping behavior; changes in vehicle speed and headways have the highest explanatory power.< Less
OTREC-RR-430 By Christopher Monsere
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This research report describes our efforts to assemble and develop a multimodal archive for the Portland-Vancouver region. The preliminary nature of the archiving process means that some of the data... More > are incomplete and samples. The arterial data sources available in the Portland-Vancouver region include data for local agencies (City of Portland, Clark County, WA, TriMet and C-TRAN) covering vehicle, transit, pedestrian, and bicycle modes. We provide descriptions of each data source and a spatial and temporal classification. The report describes the process for extracting data from the agency systems and transferring these data to our multimodal database. A number of novel visualizations were created. These are summarized in this report and examples are shown. Efforts to monitor data quality and automate data quality processing are explored. Finally, the report presents efforts to combine transit and travel time data and signal timing and vehicle count data to generate some sample congestion measures.< Less
OTREC-RR-430 By Christopher Monsere
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This research report describes our efforts to assemble and develop a multimodal archive for the Portland-Vancouver region. The preliminary nature of the archiving process means that some of the data... More > are incomplete and samples. The arterial data sources available in the Portland-Vancouver region include data for local agencies (City of Portland, Clark County, WA, TriMet and C-TRAN) covering vehicle, transit, pedestrian, and bicycle modes. We provide descriptions of each data source and a spatial and temporal classification. The report describes the process for extracting data from the agency systems and transferring these data to our multimodal database. A number of novel visualizations were created. These are summarized in this report and examples are shown. Efforts to monitor data quality and automate data quality processing are explored. Finally, the report presents efforts to combine transit and travel time data and signal timing and vehicle count data to generate some sample congestion measures.< Less