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• 1. [Article] Utilizing High-Resolution Archived Transit Data to Study Before-and-After Travel-Speed and Travel-Time Conditions

  Travel times, operating speeds, and service reliability influence costs and service attractiveness. This research outlines an approach to quantify how these metrics change after a modification of roadway ...

  Citation × Citation Citation Abstract Copy Title: Utilizing High-Resolution Archived Transit Data to Study Before-and-After Travel-Speed and Travel-Time Conditions Author: Glick, Travis B Year: 2017 Travel times, operating speeds, and service reliability influence costs and service attractiveness. This research outlines an approach to quantify how these metrics change after a modification of roadway design or transit routes using archived transit data. The Tri-County Metropolitan Transportation District of Oregon (TriMet), Portland’s public transportation provider, archives automatic vehicle location (AVL) data for all buses as part of their bus dispatch system (BDS). This research combines three types of AVL data (stop event, stop disturbance, and high-resolution) to create a detailed account of transit behavior; this probe data gives insights into the behavior of transit as well as general traffic. The methodology also includes an updated approach for confidence intervals estimates that more accurately represent of range of speed and travel time percentile estimates. This methodology is applied to three test cases using a month of AVL data collected before and after the implementation of each roadway change. The results of the test cases highlight the broad applicability for this approach to before-and-after studies. Title: Utilizing High-Resolution Archived Transit Data to Study Before-and-After Travel-Speed and Travel-Time Conditions Author: Glick, Travis B Year: 2017 Travel times, operating speeds, and service reliability influence costs and service attractiveness. This research outlines an approach to quantify how these metrics change after a modification of roadway design or transit routes using archived transit data. The Tri-County Metropolitan Transportation District of Oregon (TriMet), Portland’s public transportation provider, archives automatic vehicle location (AVL) data for all buses as part of their bus dispatch system (BDS). This research combines three types of AVL data (stop event, stop disturbance, and high-resolution) to create a detailed account of transit behavior; this probe data gives insights into the behavior of transit as well as general traffic. The methodology also includes an updated approach for confidence intervals estimates that more accurately represent of range of speed and travel time percentile estimates. This methodology is applied to three test cases using a month of AVL data collected before and after the implementation of each roadway change. The results of the test cases highlight the broad applicability for this approach to before-and-after studies. Close

• 2. [Article] Estimating Reliability Indices and Confidence Intervals for Transit and Traffic at the Corridor Level

  As congestion worsens, the importance of rigorous methodologies to estimate travel-time reliability increases. Exploiting fine-granularity transit GPS data, this research proposes a novel method to estimate ...

  Citation × Citation Citation Abstract Copy Title: Estimating Reliability Indices and Confidence Intervals for Transit and Traffic at the Corridor Level Author: Glick, Travis B Year: 2017 As congestion worsens, the importance of rigorous methodologies to estimate travel-time reliability increases. Exploiting fine-granularity transit GPS data, this research proposes a novel method to estimate travel-time percentiles and confidence intervals. Novel transit reliability measures based on travel-time percentiles are proposed to identify and rank low-performance hotspots; the proposed reliability measures can be utilized to distinguish peak-hour low performance from whole-day low performance. As a case study, the methodology is applied to a bus transit corridor in Portland, Oregon. Time-space speed profiles, heatmaps, and visualizations are employed to highlight sections and intersections with high travel-time variability and transit low performance. Segment and intersection travel-time reliability are contrasted against analytical delay formulas at intersections with positive results. If bus stop delays are removed, this methodology can also be applied to estimate regular traffic travel-time variability. Title: Estimating Reliability Indices and Confidence Intervals for Transit and Traffic at the Corridor Level Author: Glick, Travis B Year: 2017 As congestion worsens, the importance of rigorous methodologies to estimate travel-time reliability increases. Exploiting fine-granularity transit GPS data, this research proposes a novel method to estimate travel-time percentiles and confidence intervals. Novel transit reliability measures based on travel-time percentiles are proposed to identify and rank low-performance hotspots; the proposed reliability measures can be utilized to distinguish peak-hour low performance from whole-day low performance. As a case study, the methodology is applied to a bus transit corridor in Portland, Oregon. Time-space speed profiles, heatmaps, and visualizations are employed to highlight sections and intersections with high travel-time variability and transit low performance. Segment and intersection travel-time reliability are contrasted against analytical delay formulas at intersections with positive results. If bus stop delays are removed, this methodology can also be applied to estimate regular traffic travel-time variability. Close

• 3. [Article] Exploiting New Data Sources to Quantify Arterial Congestion and Performance Measures at a Regional Scale

  Transit travel time, operating speed and reliability all influence service attractiveness, operating cost and system efficiency. These metrics have a long-term impact on system effectiveness through a ...

  Citation × Citation Citation Abstract Copy Title: Exploiting New Data Sources to Quantify Arterial Congestion and Performance Measures at a Regional Scale Author: Figliozzi, Miguel, Bertini, Robert L., Glick, Travis B, Stoll, Nicholas B, Feng, Wei, Sidhu, Bobjot S., Pande, Anurag Year: 2017 Transit travel time, operating speed and reliability all influence service attractiveness, operating cost and system efficiency. These metrics have a long-term impact on system effectiveness through a change in ridership. As part of its bus dispatch system (BDS), the Tri-County Metropolitan Transportation 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. This new AVL system provides stop-level data as well as five-second resolution (5-SR) bus position data between stops. Rather than relying on interpolation tools to estimate bus trajectories (including stops and delays) between stops, the higher-resolution data shows more precise bus positions along each trip. Bus travel speeds and intersection signal/queuing delays may be determined using this newer information of several variables on transit travel time. 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 stops, identify speed breakdowns, and estimate intersection signal/queuing delays. Additionally, high-resolution achieved bus data can be used to visualize sources of congestion and delay on urban arterials. A new inter-stop trip time model was developed using the five-second resolution data. This newly developed model resulted in statistically significant and improved results over previous models. The models for overall travel time indicated that dwell time and average speed between stops were the major factors influencing transit travel time. Hence, it was concluded that estimation of average speed between stops is a critical component of the transit trip time models. Using this 5-SR data in the trip time model led to more precise and statistically valid trip time models. The research provides conclusions that can be used by transit agencies to improve operations through improvements such as transit signal priority. More importantly, for transit agencies looking for ways to archive data the research provides recommendations on formatting the data that can be most useful for future analysis. Title: Exploiting New Data Sources to Quantify Arterial Congestion and Performance Measures at a Regional Scale Author: Figliozzi, Miguel, Bertini, Robert L., Glick, Travis B, Stoll, Nicholas B, Feng, Wei, Sidhu, Bobjot S., Pande, Anurag Year: 2017 Transit travel time, operating speed and reliability all influence service attractiveness, operating cost and system efficiency. These metrics have a long-term impact on system effectiveness through a change in ridership. As part of its bus dispatch system (BDS), the Tri-County Metropolitan Transportation 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. This new AVL system provides stop-level data as well as five-second resolution (5-SR) bus position data between stops. Rather than relying on interpolation tools to estimate bus trajectories (including stops and delays) between stops, the higher-resolution data shows more precise bus positions along each trip. Bus travel speeds and intersection signal/queuing delays may be determined using this newer information of several variables on transit travel time. 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 stops, identify speed breakdowns, and estimate intersection signal/queuing delays. Additionally, high-resolution achieved bus data can be used to visualize sources of congestion and delay on urban arterials. A new inter-stop trip time model was developed using the five-second resolution data. This newly developed model resulted in statistically significant and improved results over previous models. The models for overall travel time indicated that dwell time and average speed between stops were the major factors influencing transit travel time. Hence, it was concluded that estimation of average speed between stops is a critical component of the transit trip time models. Using this 5-SR data in the trip time model led to more precise and statistically valid trip time models. The research provides conclusions that can be used by transit agencies to improve operations through improvements such as transit signal priority. More importantly, for transit agencies looking for ways to archive data the research provides recommendations on formatting the data that can be most useful for future analysis. Close