351 McCormick Dr.
P.O. Box 400742
Charlottesville, VA 22904-4742
1424 S Main St.
Blacksburg, VA 24061
Ralph Buehler (VT) Email: email@example.com
Andrew Mondschein (UVa) Email: firstname.lastname@example.org
Funding Source(s) and Amounts Provided (by each agency or organization)
Virginia Tech $67,939 (Match)
UVa $5,670 (Match)
Total Project Costs
Agency ID or Contract Number
We propose a bicycle and pedestrian count campaign that will be systematically designed to describe non-motorized traffic patterns for the entire transportation network in Blacksburg, VA. Our approach involves a two stage process: 1) sitting a long-term reference network of automated counters and performing short-duration counts (~1 week) to estimate AADT on ~10% of the street segments in Blacksburg and 2) developing regression models based on land use and characteristics of the street network to estimate AADT at locations where counts were not collected. Previous research has found that methods developed for scaling short-duration counts of motor vehicles to long-term averages can be adjusted to provide reliable estimates of AADT for bicycles and pedestrians (Hankey et al. 2014, Nordback et al., 2013, Nosal et a. 2014); a limitation of these studies is that they focused on limited networks (i.e. off-street trails) or specific transportation corridors. Our proposed work would be the first to implement this method for an entire transportation network for bicycles and pedestrians. Identifying spatial and temporal trends of bicycle and pedestrian traffic is crucial for evaluating exposure to hazard and assessing the impact of investment in future infrastructure. We have designed our count campaign to fit seamlessly into existing best practices for motor vehicles; for example, we will calculate analogous performance measures (e.e. AADT) and structure our counts (i.e.a combination of short-duration and references sites) in ways that could easily integrate into existing state and federal DOT databases. The proposed study would serve as a proof-of-concept for our approach in a rural, University town. We envision later expanding our approach to places where land use and traffic patterns may differ; for example, locations where other members of our research team are located (Charlottesville and Alexandria, VA); communities that have demonstrated interest (e.g. Roanoke, VA; see Letters of Support) or satellite locations of our institutions (e.g. Richmond, VA). We expect that our method could be implemented in any location throughout the country and data readily assimilated into existing databases currently maintained by state DOTs.
We will work in conjunction with local agencies to develop the county campaign described here. Specifically, we are working closely with others (see Letters of Support) who plan to conduct bicycle and pedestrian counts including: the Director of Public Works for the Town of Blacksburg and the Alternative Transportation group at Virginia Tech. These two organization plan to purchase automated counters; we will work together to combine count datasets and design complementary count campaigns to ensure we most efficiently use our respective resources. By engaging these local organizations throughout the planning and implementation stages of this project, we hope to institutionalize our approach )and more generally the practice of bicycle and pedestrian traffic counts) to ensure our work has lasting impacts on the planning process in Blacksburg. Furthermore, we have identified one local planning agency that is interested in participating in future expansions of this project; the Roanoke Valley-Alleghany Regional Commission (RVARC) has expressed interest in assessing patterns of bicycle and pedestrian traffic in Roanoke, VA. RVARC has participated in volunteer-based counts and automated off-street trail counts in the past and would like to expand their count program. Other logical expansions would include Charlottesville and Alexandria, VA where members of our study team are located. We envision, at a minimum, conducting training sessions with local agencies such as RVARC on the findings of our studies; specifically commenting on best practices. We hope to identify future funding sources that would allow for us to expand our count campaigns to jurisdictions that show interest in quantifying spatial and temporal patterns of bicycle and pedestrian traffic.
Our work will represent the first count campaign for bicycles and pedestrians on streets that is explicitly designed for estimating performance measures on the entire network. We expect to develop a number of useful tools and best practices as part of this work. Our team is well positioned to accomplish the tasks described above within the specified project deadlines.
Key Outcomes and Products:
- Systematic validation of 3 count devices (pneumatic tubes, passive infrared, microwave).
- A description of the design of a counting program to estimate non-motorized traffic flows on streets and sidewalks in Blacksburg, VA using a combination of reference sites and short-duration count sites.
- Development of scaling factors to estimate bicycle and pedestrian AADT and MT on streets and sidewalks from short-duration counts.
- Land use regression models to estimate bicycle and pedestrian AADT and MT on all street segments in Blacksburg, VA.
- Examples of how the AADT estimates can be used to estimate exposure to safety (e.g. crashes) and environmental (e.g. air pollution).
Web Links to Reports and to the Project website
Final Report as of June 2016: