Search

Search Results

• 1. [Article] Multimodal Data at Signalized Intersections: Strategies for Archiving Existing and New Data Streams to Support Operations and Planning & Fusion and Integration of Arterial Performance Data

  There is a growing interest in arterial system management due to the increasing amount of travel on arterials and a growing emphasis on multimodal transportation. The benefits of archiving arterial-related ...

  Citation × Citation Citation Abstract Copy Title: Multimodal Data at Signalized Intersections: Strategies for Archiving Existing and New Data Streams to Support Operations and Planning & Fusion and Integration of Arterial Performance Data Author: Tufte, Kristin A., Monsere, Christopher M., Kothuri, Sirisha Murthy, Olson, Carl Scott Year: 2013 There is a growing interest in arterial system management due to the increasing amount of travel on arterials and a growing emphasis on multimodal transportation. The benefits of archiving arterial-related data are numerous. This research report describes our efforts to assemble and develop a multimodal archive for the Portland-Vancouver region. There is coverage of data sources from all modes in the metropolitan region; however, the preliminary nature of the archiving process means that some of the data are incomplete and samples. The arterial data sources available in the Portland-Vancouver region and that are covered in this report include data for various local agencies (City of Portland, Clark County, WA, TriMet and C-TRAN) covering vehicle, transit, pedestrian, and bicycle modes. We provide detailed descriptions of each data source and a spatial and temporal classification. The report describes the conceptual framework for an archive and the data collection and archival process, including the process for extracting the data from the agency systems and transferring these data to our multimodal database. Data can be made more useful though the use of improved visualization techniques. Thus as part of the project, a number of novel, online visualizations were created and implemented. These graphs and displays are summarized in this report and example visualizations are shown. As with any automated sensor system, data quality and completeness is an important issue and the challenge of automating data quality is large. Preliminary efforts to validate and 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. Title: Multimodal Data at Signalized Intersections: Strategies for Archiving Existing and New Data Streams to Support Operations and Planning & Fusion and Integration of Arterial Performance Data Author: Tufte, Kristin A., Monsere, Christopher M., Kothuri, Sirisha Murthy, Olson, Carl Scott Year: 2013 There is a growing interest in arterial system management due to the increasing amount of travel on arterials and a growing emphasis on multimodal transportation. The benefits of archiving arterial-related data are numerous. This research report describes our efforts to assemble and develop a multimodal archive for the Portland-Vancouver region. There is coverage of data sources from all modes in the metropolitan region; however, the preliminary nature of the archiving process means that some of the data are incomplete and samples. The arterial data sources available in the Portland-Vancouver region and that are covered in this report include data for various local agencies (City of Portland, Clark County, WA, TriMet and C-TRAN) covering vehicle, transit, pedestrian, and bicycle modes. We provide detailed descriptions of each data source and a spatial and temporal classification. The report describes the conceptual framework for an archive and the data collection and archival process, including the process for extracting the data from the agency systems and transferring these data to our multimodal database. Data can be made more useful though the use of improved visualization techniques. Thus as part of the project, a number of novel, online visualizations were created and implemented. These graphs and displays are summarized in this report and example visualizations are shown. As with any automated sensor system, data quality and completeness is an important issue and the challenge of automating data quality is large. Preliminary efforts to validate and 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. Close

• 2. [Article] Tracking Trucks to Improve Performance

  Freight transportation is an important part of Oregon’s economy, and the Oregon Department of Transportation, or ODOT, continually observes the highway system to make sure it is running as smoothly as ...

  Citation × Citation Citation Abstract Copy Title: Tracking Trucks to Improve Performance Author: Cetin, Mecit, Monsere, Christopher M. Year: 2013 Freight transportation is an important part of Oregon’s economy, and the Oregon Department of Transportation, or ODOT, continually observes the highway system to make sure it is running as smoothly as possible. By monitoring the progress of individual trucks, ODOT can obtain performance metrics such as travel time, travel delays, and origin-destination flows. This information can help identify slow passages or bottlenecks in the highway system. Typical ways of obtaining these metrics, however, may involve purchasing expensive equipment, and may also raise privacy concerns if each truck is required to carry a tracking unit. To avoid these difficulties, Portland State University researcher Chris Monsere explored a simpler way to get freight performance measures using a probabilistic approach. Title: Tracking Trucks to Improve Performance Author: Cetin, Mecit, Monsere, Christopher M. Year: 2013 Freight transportation is an important part of Oregon’s economy, and the Oregon Department of Transportation, or ODOT, continually observes the highway system to make sure it is running as smoothly as possible. By monitoring the progress of individual trucks, ODOT can obtain performance metrics such as travel time, travel delays, and origin-destination flows. This information can help identify slow passages or bottlenecks in the highway system. Typical ways of obtaining these metrics, however, may involve purchasing expensive equipment, and may also raise privacy concerns if each truck is required to carry a tracking unit. To avoid these difficulties, Portland State University researcher Chris Monsere explored a simpler way to get freight performance measures using a probabilistic approach. Close

• 3. [Article] Evaluation of Transportation Microenvironments Through Assessment of Cyclysts' Exposure to Traffic-Related Particulate Matter

  It is well established that vehicles powered by carbon-based fuels (e.g. gasoline, diesel) have a negative impact on air quality, especially in urban centers. Traditionally, air quality conformity studies ...

  Citation × Citation Citation Abstract Copy Title: Evaluation of Transportation Microenvironments Through Assessment of Cyclysts' Exposure to Traffic-Related Particulate Matter Author: George, Linda A., Figliozzi, Miguel A., Monsere, Christopher M., Kendrick, Christine M., Bigazzi, Alexander Y, Moore, Adam Year: 2011 It is well established that vehicles powered by carbon-based fuels (e.g. gasoline, diesel) have a negative impact on air quality, especially in urban centers. Traditionally, air quality conformity studies analyze the macroenvironmental impact of transportation corridors, as they relate to regional air quality management concerns. Urban residents spend a considerable amount of outdoor time in transportation microenvironments as pedestrians, bicycle commuters, people waiting to use public transport, residents and workers situated along roadways, and commuters within vehicles. An emerging area of research has shown that human health impacts within transport microenvironments can be considerable, but have not been well-characterized. As urban public policies increasingly encourage the use of multi-mode commuting in dense urban centers, decisionmakers need reliable modeling tools to predict and mitigate the health consequences of vehicle-related emissions in transportation microenvironments. This project proposes unique integration of real-time multi-modal personal exposure monitoring with real-time detailed traffic monitoring in order to develop a computer model that links traffic characteristics, emissions, built environment configuration, mode of travel and health impacts. Existing emission and dispersion models do not take direct account of the dynamic nature of traffic and how emissions impact the health of the diversity of urban dwellers, bus commuters, pedestrians, and bicycle riders. Typical approaches use highly aggregated vehicle data and computed link speeds to assign an emission factor to the traffic, an assumed proportion of which is trucks. In addition, existing methods to assess environmental impacts tend to focus on the production source of the pollutant not the impacts, which require information on population activities and its proximity to vehicle flows. Personal exposure studies document significant air quality impacts within the transportation microenvironment but do not integrate dynamic traffic and emission analysis. Previous research argues for a comprehensive approach. From the perspective of mitigating transportation impacts, it is significant to understand: a) exposure to the pollution, which in turn requires assessment of where people are in relation to the source of the pollutant, and b) the relation between pollution and vehicle flows. This research will target highly polluted high exposure hotspots in Portland, e.g. high traffic flows running through a major trip destination area for shopping, entertainment, education, or health care highly dependent on mode of travel, traffic levels and type, and built environment characteristics. Our approach is to conduct field studies to measure personal exposure to particulate matter as a function of transportation mode through pre-determined routes in the city. Exposure levels, position, time and rate of travel will be recorded. Simultaneously we will collect detailed traffic data that will provide type/number of vehicle, speed of travel and start/stop behavior. GIS analysis of the urban form and land use characteristics will establish built environment parameters. These data will be integrated into a built environment-travel mode-exposure model. The major scientific innovations offered by this project are: 1) integration of detailed and real-time exposure/emissions with a real-time traffic measurement approach, and 2) development of an integrated emissions and transportation model that combines traffic characteristics, emissions, built environment configuration, mode of travel and predicted health impacts. The outcomes of the research will be of importance to the general public, urban communities, departments of transportation charged with managing urban traffic, and public health authorities. Title: Evaluation of Transportation Microenvironments Through Assessment of Cyclysts' Exposure to Traffic-Related Particulate Matter Author: George, Linda A., Figliozzi, Miguel A., Monsere, Christopher M., Kendrick, Christine M., Bigazzi, Alexander Y, Moore, Adam Year: 2011 It is well established that vehicles powered by carbon-based fuels (e.g. gasoline, diesel) have a negative impact on air quality, especially in urban centers. Traditionally, air quality conformity studies analyze the macroenvironmental impact of transportation corridors, as they relate to regional air quality management concerns. Urban residents spend a considerable amount of outdoor time in transportation microenvironments as pedestrians, bicycle commuters, people waiting to use public transport, residents and workers situated along roadways, and commuters within vehicles. An emerging area of research has shown that human health impacts within transport microenvironments can be considerable, but have not been well-characterized. As urban public policies increasingly encourage the use of multi-mode commuting in dense urban centers, decisionmakers need reliable modeling tools to predict and mitigate the health consequences of vehicle-related emissions in transportation microenvironments. This project proposes unique integration of real-time multi-modal personal exposure monitoring with real-time detailed traffic monitoring in order to develop a computer model that links traffic characteristics, emissions, built environment configuration, mode of travel and health impacts. Existing emission and dispersion models do not take direct account of the dynamic nature of traffic and how emissions impact the health of the diversity of urban dwellers, bus commuters, pedestrians, and bicycle riders. Typical approaches use highly aggregated vehicle data and computed link speeds to assign an emission factor to the traffic, an assumed proportion of which is trucks. In addition, existing methods to assess environmental impacts tend to focus on the production source of the pollutant not the impacts, which require information on population activities and its proximity to vehicle flows. Personal exposure studies document significant air quality impacts within the transportation microenvironment but do not integrate dynamic traffic and emission analysis. Previous research argues for a comprehensive approach. From the perspective of mitigating transportation impacts, it is significant to understand: a) exposure to the pollution, which in turn requires assessment of where people are in relation to the source of the pollutant, and b) the relation between pollution and vehicle flows. This research will target highly polluted high exposure hotspots in Portland, e.g. high traffic flows running through a major trip destination area for shopping, entertainment, education, or health care highly dependent on mode of travel, traffic levels and type, and built environment characteristics. Our approach is to conduct field studies to measure personal exposure to particulate matter as a function of transportation mode through pre-determined routes in the city. Exposure levels, position, time and rate of travel will be recorded. Simultaneously we will collect detailed traffic data that will provide type/number of vehicle, speed of travel and start/stop behavior. GIS analysis of the urban form and land use characteristics will establish built environment parameters. These data will be integrated into a built environment-travel mode-exposure model. The major scientific innovations offered by this project are: 1) integration of detailed and real-time exposure/emissions with a real-time traffic measurement approach, and 2) development of an integrated emissions and transportation model that combines traffic characteristics, emissions, built environment configuration, mode of travel and predicted health impacts. The outcomes of the research will be of importance to the general public, urban communities, departments of transportation charged with managing urban traffic, and public health authorities. Close