Influences on Bicyclists and Motor Vehicles Operating Speed within a Corridor
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abstract
This proposed project will investigate the influences on motor vehicle and bicyclist operations within a corridor. The variables that will be considered include roadway characteristics, such as number of lanes and driveway density, along with the vehicle mix present (either number of bicyclists and motor vehicles or percent for each unit type). The objective of this project is to identify the variables affecting vehicle operating speed, especially the number of bicyclists. This project is proposed to build upon the database being created in a companion Safe-D project (Data Mining to Improve Planning for Pedestrian and Bicyclist Safety). That project is building a database that will include number of bicyclists for several roads within the City of San Diego, CA. This research project will add information on operating speeds for motor vehicles for select corridors. As part of the research, the team will determine if operating speeds can be obtained from a data provider (e.g., Inrix) or if the level of detail needed will require obtaining the data from speed measuring equipment installed in select locations. This research will then investigate the relationship between motor vehicle operating speed with roadway conditions, including the number of bicyclists present. Due to the dynamic nature of operational speed, an appropriate analysis requires control for a wide range of conditions � in addition to the geometry of the facility � such as traffic volume and density of the flow. This research project will investigate these relationships using a variety of metrics including average travel speed, the 85th percentile speed, and the variance of speeds when operations are uncongested. The analysis may require sub-setting the data, depending on the range of conditions represented. The range of possible analyses approaches will also depend on the amount of speed data obtained and its level of aggregation. The research team will give consideration to potential cyclical trends in the speed data, as well as any time series characteristics present in these types of datasets, in order to properly account for those trends and characteristics. The goal is to be able to clearly identify and describe variables that influence operating speed for motor vehicles especially the number of bicyclists present on the segment. Collaboration with San Diego State University is anticipated in the form of a summer intern and site visit in Year 2.
