Studying Travel Behavior in Napa County
Offering an unprecedented look into travel behavior of visitors, residents, employees, and students who make work and non-work trips in Napa County.
We collaborated with the Napa County Transportation Planning Agency and Napa County to gather information on travel behavior in the region. This was a great opportunity to integrate innovative data collection methods with enhancements to traditional methods. Travel behavior studies are always challenged by data collection due to factors such as cost, study scale, and inconvenience to travelers. To overcome these challenges and provide greater insight about Napa County travelers, we developed an integrated data collection and analytics approach. The key data collection components are listed below.
The data was integrated to create a complete picture of travel behavior for the County. Big data was particularly important in creating this picture and overcoming the common limitations associated with conventional data sets. In addition, the data was structured into origin-destination trip tables that could be easily compared to the output from local travel demand forecasting models and from other travel behavior data sources such as the Census. This allows for better model calibration and a higher level of confidence in the decisions based on these models.
The detailed technical report prepared for the study contains a wealth of insight into Napa County travel patterns but the following information was noteworthy because it directly addressees questions the community has about what contributes to existing traffic problems.
- 55% of trips had both their origin and their destination within Napa County based on mobile device data.
- 9% of trips passed through Napa County without making a stop based on mobile device and license plate data.
- Fridays are the busiest travel days for both personal and commercial vehicle travel on average. Commercial vehicles represent almost 5% of Friday traffic.
Understanding current travel patterns and travel markets with a high-level confidence is an important first step for any analysis or investigation into making decisions that will improve the transportation network.
Key data collection components:
The data was integrated to create a complete picture of travel behavior for the County.
The data was structured into origin-destination trip tables that could be easily compared to the output from local travel demand forecasting models and from other travel behavior sources such as Census.
Big Data was particularly important in creating this picture and overcoming the common limitations associated with conventional data sets.
This allows for better model calibration and a higher level of confidence in the decisions based on these models.
- In-person surveys were conducted at twelve wineries to gather more detailed travel behavior data for trips made by winery patrons.
- An online employer survey was also distributed to Napa County’s largest employers to gather information on the origin, destination, and travel characteristics of Napa County employees.
- Vehicle classification count and license plate data was collected at twelve local and external gateway locations.
- License plate matching was used to develop origin-destination trip tables of observed inter-regional and pass-through trips.
Cell Phone Data
Mobile device data was used to gather movement and usage patterns over a two-month period to generate estimates of observed trip origins and destinations as well as trip time period and inferred purpose. For trips with an origin or destination outside Napa County, the roadway used to enter/leave Napa County was identified.