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• 1. [Article] Evaluation of Advanced Traffic Control Systems

  Researchers from Portland State University develop performance measures and algorithms for evaluation of state-of-the-art traffic signal control technologies..

  Citation × Citation Citation Abstract Copy Title: Evaluation of Advanced Traffic Control Systems Author: Figliozzi, Miguel Year: 2014 Researchers from Portland State University develop performance measures and algorithms for evaluation of state-of-the-art traffic signal control technologies.. Title: Evaluation of Advanced Traffic Control Systems Author: Figliozzi, Miguel Year: 2014 Researchers from Portland State University develop performance measures and algorithms for evaluation of state-of-the-art traffic signal control technologies.. Close

• 2. [Article] Utilizing Egocentric Video and Sensors to Conduct Naturalistic Bicycling Studies

  Existing data collection methods are mostly designed for videos captured by stationary cameras and are not designed to follow cyclists along a route or to integrate other sensor data. The goals of this ...

  Citation × Citation Citation Abstract Copy Title: Utilizing Egocentric Video and Sensors to Conduct Naturalistic Bicycling Studies Author: Liu, Feng, Figliozzi, Miguel Year: 2016 Existing data collection methods are mostly designed for videos captured by stationary cameras and are not designed to follow cyclists along a route or to integrate other sensor data. The goals of this research are: a) to develop a platform to collect naturalistic video bicycling data, b) to develop a methodology to integrate video data with other sensors that measure cyclists’ position and comfort levels, and c) to apply the platform and data collection methodology to a real-world route. This research effort has successfully integrated video and sensor data to describe cyclists’ comfort levels along a route. It was found that stress levels while riding during peak hours averaged 1.75 times higher than while riding at offpeak hours on the same routes and facilities. Separated bicycle infrastructure, such as multiuse paths, during peak and off-peak hours showed the lowest stress levels. Signalized intersections were hotspots for cyclists’ stress. All these results are statistically significant. The results indicate that integrating video and sensor data allows for a more detailed understanding of cyclists’ perceptions along a route. Rather than having an average measure for the whole route or path, it is possible to precisely identify the places and/or situations that trigger a change in experience or stress. By measuring how different facility types and riding conditions affect the distribution of stress levels among users, transportation engineers and planners may in the future incorporate video and detailed sensor data to evaluate the real-world performance of different types of facilities Title: Utilizing Egocentric Video and Sensors to Conduct Naturalistic Bicycling Studies Author: Liu, Feng, Figliozzi, Miguel Year: 2016 Existing data collection methods are mostly designed for videos captured by stationary cameras and are not designed to follow cyclists along a route or to integrate other sensor data. The goals of this research are: a) to develop a platform to collect naturalistic video bicycling data, b) to develop a methodology to integrate video data with other sensors that measure cyclists’ position and comfort levels, and c) to apply the platform and data collection methodology to a real-world route. This research effort has successfully integrated video and sensor data to describe cyclists’ comfort levels along a route. It was found that stress levels while riding during peak hours averaged 1.75 times higher than while riding at offpeak hours on the same routes and facilities. Separated bicycle infrastructure, such as multiuse paths, during peak and off-peak hours showed the lowest stress levels. Signalized intersections were hotspots for cyclists’ stress. All these results are statistically significant. The results indicate that integrating video and sensor data allows for a more detailed understanding of cyclists’ perceptions along a route. Rather than having an average measure for the whole route or path, it is possible to precisely identify the places and/or situations that trigger a change in experience or stress. By measuring how different facility types and riding conditions affect the distribution of stress levels among users, transportation engineers and planners may in the future incorporate video and detailed sensor data to evaluate the real-world performance of different types of facilities Close

• 3. [Article] A Model for Better Crosswalk Safety

  NITC researchers from Portland State University developed models to find what factors affected vehicles’ compliance with pedestrian safety laws. The results suggest that treatments discouraging accelerating ...

  Citation × Citation Citation Abstract Copy Title: A Model for Better Crosswalk Safety Author: Figliozzi, Miguel Year: 2017 NITC researchers from Portland State University developed models to find what factors affected vehicles’ compliance with pedestrian safety laws. The results suggest that treatments discouraging accelerating toward a crosswalk could help increase pedestrian safety. Title: A Model for Better Crosswalk Safety Author: Figliozzi, Miguel Year: 2017 NITC researchers from Portland State University developed models to find what factors affected vehicles’ compliance with pedestrian safety laws. The results suggest that treatments discouraging accelerating toward a crosswalk could help increase pedestrian safety. Close

• 4. [Article] Crowdsourcing Cycling Safety and Route Data with the “ORcycle” Smartphone App

  ORcycle is a new smartphone application (for both Android and iOS) developed by Transportation, Technology, and People (TTP) lab researchers at Portland State University as part of an Oregon Department ...

  Citation × Citation Citation Abstract Copy Title: Crowdsourcing Cycling Safety and Route Data with the “ORcycle” Smartphone App Author: Figliozzi, Miguel Year: 2015 ORcycle is a new smartphone application (for both Android and iOS) developed by Transportation, Technology, and People (TTP) lab researchers at Portland State University as part of an Oregon Department of Transportation (ODOT) research project. ORcycle collects user, route, infrastructure, crash, and safety data. ORcycle was successfully launched in early November 2014 and presents many improvements over existing or similar apps. Initial data findings and insights will be presented. Lessons learned as well as opportunities and challenges associated with smartphone data collection methods will be discussed. More information about the app can be found here: http://www.pdx.edu/transportation-lab/orcycle. Title: Crowdsourcing Cycling Safety and Route Data with the “ORcycle” Smartphone App Author: Figliozzi, Miguel Year: 2015 ORcycle is a new smartphone application (for both Android and iOS) developed by Transportation, Technology, and People (TTP) lab researchers at Portland State University as part of an Oregon Department of Transportation (ODOT) research project. ORcycle collects user, route, infrastructure, crash, and safety data. ORcycle was successfully launched in early November 2014 and presents many improvements over existing or similar apps. Initial data findings and insights will be presented. Lessons learned as well as opportunities and challenges associated with smartphone data collection methods will be discussed. More information about the app can be found here: http://www.pdx.edu/transportation-lab/orcycle. Close

• 5. [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

• 6. [Article] Methodology to Characterize Ideal Short-Term Counting Conditions and Improve AADT Estimation Accuracy Using a Regression-Based Correcting Function

  Transportation agencies’ motor vehicle count programs tend to be well established and robust with clear guidelines to collect short-term count data, to analyze data, develop annual average daily traffic ...

  Citation × Citation Citation Abstract Copy Title: Methodology to Characterize Ideal Short-Term Counting Conditions and Improve AADT Estimation Accuracy Using a Regression-Based Correcting Function Author: Figliozzi, Miguel, Johnson, Pam, Monsere, Christopher M., Nordback, Krista Year: 2014 Transportation agencies’ motor vehicle count programs tend to be well established and robust with clear guidelines to collect short-term count data, to analyze data, develop annual average daily traffic (AADT) adjustment factors, and to estimate AADT volumes. In contrast, bicycle and pedestrian traffic monitoring is an area of work for most transportation agencies. In most agencies, there are a low numbers of counting sites and limited agency experience to manage a city-wide or state-wide system of collecting, processing, and using nonmotorized data. Short duration counts are used to estimate longer duration volumes such as AADT. Because bicycle or pedestrian short-term counts vary dramatically over time and significantly more than motorized vehicle counts, the direct application of motorized vehicle AADT estimation methods may be inadequate. The goal of this paper is to present a methodology that will enhance, if needed, existing AADT estimation methods widely employed for motorized vehicle counts. The proposed methodology is based on the analysis of AADT estimation errors using regression models to estimate a correcting function that accounts for weather and activity factors. The methodology can be applied to any type of traffic with high volume variability but in this research is applied to a permanent bicycle counting station in Portland, Oregon. The results indicate that the proposed methodology is simple and useful for finding ideal short-term counting conditions and improving AADT estimation accuracy. Title: Methodology to Characterize Ideal Short-Term Counting Conditions and Improve AADT Estimation Accuracy Using a Regression-Based Correcting Function Author: Figliozzi, Miguel, Johnson, Pam, Monsere, Christopher M., Nordback, Krista Year: 2014 Transportation agencies’ motor vehicle count programs tend to be well established and robust with clear guidelines to collect short-term count data, to analyze data, develop annual average daily traffic (AADT) adjustment factors, and to estimate AADT volumes. In contrast, bicycle and pedestrian traffic monitoring is an area of work for most transportation agencies. In most agencies, there are a low numbers of counting sites and limited agency experience to manage a city-wide or state-wide system of collecting, processing, and using nonmotorized data. Short duration counts are used to estimate longer duration volumes such as AADT. Because bicycle or pedestrian short-term counts vary dramatically over time and significantly more than motorized vehicle counts, the direct application of motorized vehicle AADT estimation methods may be inadequate. The goal of this paper is to present a methodology that will enhance, if needed, existing AADT estimation methods widely employed for motorized vehicle counts. The proposed methodology is based on the analysis of AADT estimation errors using regression models to estimate a correcting function that accounts for weather and activity factors. The methodology can be applied to any type of traffic with high volume variability but in this research is applied to a permanent bicycle counting station in Portland, Oregon. The results indicate that the proposed methodology is simple and useful for finding ideal short-term counting conditions and improving AADT estimation accuracy. Close

• 7. [Article] Identficaton and Characterization of Pollutant Hot Spots Integratng Probe Vehicle, Traffic and Land Use Data

  Identification and Characterization of PM2.5 and VOC Hot Spots on Arterial Corridor by Integrating Probe Vehicle, Traffic, and Land Use Data: The purpose of this study is to explore the use of integrated ...

  Citation × Citation Citation Abstract Copy Title: Identficaton and Characterization of Pollutant Hot Spots Integratng Probe Vehicle, Traffic and Land Use Data Author: Bell, Katherine Eleanor, Figliozzi, Miguel Year: 2014 Identification and Characterization of PM2.5 and VOC Hot Spots on Arterial Corridor by Integrating Probe Vehicle, Traffic, and Land Use Data: The purpose of this study is to explore the use of integrated probe vehicle, traffic and land use data to identify and characterize fine particulate matter (PM2.5) and volatile organic compound (VOC) hot spot locations on urban arterial corridors. An emission hot spot is defined as a fixed location along a corridor in which the mean pollutant concentrations are consistently above the 85th percentile of pollutant concentrations when considering all other locations along the corridor during the same time period. In order to collect data for this study, an electric vehicle was equipped with instruments designed to measure PM2.5 and VOC concentrations. Second-by-second measurements were performed for each pollutant from both the right and left sides of the vehicle. Detailed meteorological, traffic and land use data is also available for this research. The results of a statistical analysis are used to better understand which data sources are most valuable in estimating PM2.5 and VOC hot spot locations consistent with empirical data, as well as which variables have the greatest impact on emissions and pollutant levels at a microscale level. This research highlights the importance of considering both consistency and peak emission levels when identifying hot spot locations. An objective of this research is to develop a method to identify urban arterial hot spot locations that provides a balance of efficiency (in terms of capital expenses, time, resources, expertise requirements, etc.) and accuracy. Title: Identficaton and Characterization of Pollutant Hot Spots Integratng Probe Vehicle, Traffic and Land Use Data Author: Bell, Katherine Eleanor, Figliozzi, Miguel Year: 2014 Identification and Characterization of PM2.5 and VOC Hot Spots on Arterial Corridor by Integrating Probe Vehicle, Traffic, and Land Use Data: The purpose of this study is to explore the use of integrated probe vehicle, traffic and land use data to identify and characterize fine particulate matter (PM2.5) and volatile organic compound (VOC) hot spot locations on urban arterial corridors. An emission hot spot is defined as a fixed location along a corridor in which the mean pollutant concentrations are consistently above the 85th percentile of pollutant concentrations when considering all other locations along the corridor during the same time period. In order to collect data for this study, an electric vehicle was equipped with instruments designed to measure PM2.5 and VOC concentrations. Second-by-second measurements were performed for each pollutant from both the right and left sides of the vehicle. Detailed meteorological, traffic and land use data is also available for this research. The results of a statistical analysis are used to better understand which data sources are most valuable in estimating PM2.5 and VOC hot spot locations consistent with empirical data, as well as which variables have the greatest impact on emissions and pollutant levels at a microscale level. This research highlights the importance of considering both consistency and peak emission levels when identifying hot spot locations. An objective of this research is to develop a method to identify urban arterial hot spot locations that provides a balance of efficiency (in terms of capital expenses, time, resources, expertise requirements, etc.) and accuracy. Close

• 8. [Article] Safety Effectiveness of Pedestrian Crossing Enhancements

  Over the last decade, the Oregon DOT and other agencies have systematically implemented many pedestrian crossing enhancements (PCEs) across the state. This study explored the safety performance of these ...

  Citation × Citation Citation Abstract Copy Title: Safety Effectiveness of Pedestrian Crossing Enhancements Author: Monsere, Christopher M., Figliozzi, Miguel, Kothuri, Sirisha, Razmpa, Ali, Hazel, Daniel R. Year: 2016 Over the last decade, the Oregon DOT and other agencies have systematically implemented many pedestrian crossing enhancements (PCEs) across the state. This study explored the safety performance of these enhanced crossing in Oregon. Detailed data were collected on 191 crossings. Supplemental data items included crossing location information, route characteristics, surrounding land use and crossing enhancement descriptions. Pedestrian volume at the crossing locations was a highly desirable but unavailable data element. To characterize pedestrian activity, a method was developed to estimate ranges for pedestrian crosswalk activity levels based on the land use classification at the census block level and the presence of pedestrian traffic generators such as bus stops, schools, shopping centers and hospitals within a 0.25-mile radius. Each crosswalk was categorized into one of six levels of activity – very low, low, medium-low, medium, medium-high and high. Crash data for the 2007-2014 period were assembled for the safety analysis. After filtering, 62 pedestrian crashes and 746 rear-end crashes were retained for further analysis. The crash data were merged and analyzed. Crash patterns and risk ratios were explored. The most important trend observed was a shift (reduction) in the pedestrian crash severity after the installation of the crosswalk treatments. This shift was from fatal and injury A crash type to lower severity crashes of injury B and injury C. For pedestrian crashes, increases in the risk ratio were observed for increases in the number of lanes, the posted speed, and estimated pedestrian activity level. Similar trends were observed for rear-end crashes. Due to data limitations, subsequent safety analysis focused on installations of RRFB crossing enhancements. A CMF for RRFB installations was estimated. The CMFS for pedestrian crashes are 0.64 +/- 0.26 using a simple before-after analysis; for rear-end crashes: 0.93 +/- 0.22 using an empirical Bayes analysis approach. Title: Safety Effectiveness of Pedestrian Crossing Enhancements Author: Monsere, Christopher M., Figliozzi, Miguel, Kothuri, Sirisha, Razmpa, Ali, Hazel, Daniel R. Year: 2016 Over the last decade, the Oregon DOT and other agencies have systematically implemented many pedestrian crossing enhancements (PCEs) across the state. This study explored the safety performance of these enhanced crossing in Oregon. Detailed data were collected on 191 crossings. Supplemental data items included crossing location information, route characteristics, surrounding land use and crossing enhancement descriptions. Pedestrian volume at the crossing locations was a highly desirable but unavailable data element. To characterize pedestrian activity, a method was developed to estimate ranges for pedestrian crosswalk activity levels based on the land use classification at the census block level and the presence of pedestrian traffic generators such as bus stops, schools, shopping centers and hospitals within a 0.25-mile radius. Each crosswalk was categorized into one of six levels of activity – very low, low, medium-low, medium, medium-high and high. Crash data for the 2007-2014 period were assembled for the safety analysis. After filtering, 62 pedestrian crashes and 746 rear-end crashes were retained for further analysis. The crash data were merged and analyzed. Crash patterns and risk ratios were explored. The most important trend observed was a shift (reduction) in the pedestrian crash severity after the installation of the crosswalk treatments. This shift was from fatal and injury A crash type to lower severity crashes of injury B and injury C. For pedestrian crashes, increases in the risk ratio were observed for increases in the number of lanes, the posted speed, and estimated pedestrian activity level. Similar trends were observed for rear-end crashes. Due to data limitations, subsequent safety analysis focused on installations of RRFB crossing enhancements. A CMF for RRFB installations was estimated. The CMFS for pedestrian crashes are 0.64 +/- 0.26 using a simple before-after analysis; for rear-end crashes: 0.93 +/- 0.22 using an empirical Bayes analysis approach. Close