DRAFT Vision Statement — Operations and Congestion (to include travel demand modeling)
Lead: Billy Bachman
Over the next ten years, transportation system performance will be monitored at unprecedented spatial and temporal resolutions. Detailed, action-oriented operations information will be available to policy makers, planners, and system managers.
ABJ60 Operation and Congestion Mission
The ABJ6O Operations and Congestion group will research and promote the use of spatial data / information science for distilling these new data into useful information and enlightened understanding for decision-making. The group will research the measuring, monitoring, evaluating, forecasting, and reporting of spatial data / information for transportation system operations.
Topics of Interest to the Committee
1. As massive amounts of operational data are observed, collected, and stored (GPS, ITS, Mobile phones, aerial/satellite imagery, etc.), there is a need to ensure proper data reduction to spatial and temporal scales.
2. There is a need to design and implement transportation network data models to support the specific needs of operations and congestion analysis. Included in these designs must be methods for integrating to other network representations typically used in planning and cartography
3. Operational data has systemic and device-specific errors/anomalies that must be recognized and cleaned through imputation. Many techniques for imputation require spatial and temporal analyses. The spatial and temporal aspects of data imputation must be understood.
4. While operational data provides a wealth of information about the dynamics of vehicles and systems, an even deeper understanding can be achieved through the integration with other spatial and temporal datasets (ie., weather, land use, special events, construction). Spatial data mining of operational data to extract/estimate activity patterns is of substantial interest to the committee.
5. The magnitude and temporal nature of operational data presents significant problems for data visualization. Techniques and guidelines for the spatial and temporal visualization and presentation of operational data need to be researched.
6. Transportation data for characterizing operations and planning has historically relied on average numbers (travel time, speed, AADT, etc.). Other statistical measures that characterize distributions and errors can provide much better information about operational performance. The committee should research and promote advances in statistical understanding and communication.
7. Data collection sampling strategies are generally designed to support a single business function. The resulting data, however, provides value needs beyond a single purpose. Guidance for collecting operations data should be generated to ensure that increased value is achieved.
8. Many innovative operational data collection techniques involve the observation and recording of activities and travel patterns of individual people or vehicles. Privacy protection is of great concern and spatial masking techniques should be developed and standardized to prevent the transfer of private information.
9. Operational data has the potential to improve the understanding of existing travel patterns and therefore improve the profession’s ability to forecast travel in the future. Research should be conducted to assist models in trip distribution techniques and to assist the understanding of model variability.
Members of the Operations and Congestion Focus Group:
Group Lead: Billy Bachman