Background:
According to the 2001 Nationwide Household Travel Survey (NHTS), over 60% of all personal trips are five miles or less in length - a reasonable distance to ride a bike - and nearly 40% are two miles or less. However, only about 1% of trips are made on bicycles. In contrast, bicycling is a popular form of recreation throughout the country.

Understanding the role of the built environment in decisions to bicycle may lead to positive infrastructure and policy changes. Several studies support the notion that providing bicycle infrastructure, particularly lanes and paths, can increase bicycle use. Many of these studies, however, rely on aggregate data, making it difficult to examine the direct relationship between infrastructure and behavior, much less route choice. Studies that have focused on route choice of cyclists generally use two methods: (1) surveys that ask questions about general preferences for types of facilities, sometimes giving respondents specific scenarios to rank; and (2) surveys that ask bicyclists to remember their route for a specific trip using a paper map or other mechanism. These studies provide some insights on route choice and the role of infrastructure. However, relying on recall or hypothetical situations may not accurately reflect behavior.

Objectives:
This paper will present the results of an ALR-funded study that collected data from bicyclists using GPS technology. Two main objectives were to: (1) Test the use of readily available technology (personal digital assistants with GPS) to objectively measure bicycling activity; and (2) Examine route choice behavior. Specific research questions include:

• How do cyclists’ routes differ from the shortest network distance? How far do cyclists deviate from the shortest route to use bicycle infrastructure?
• How do cyclists choose their routes? How do network characteristics (e.g. bike lanes or heavy traffic) influence those decisions? How do other factors, such as cycling with a child or the age or gender of the cyclist, influence these decisions?
• How might the route chosen influence the health benefits of the physical activity?

Methods:
Participants were recruited through a variety of methods, with the objective of having a wide range demographically, and a range of types of bicyclists, e.g. people who bike every day to work and people who only bike recreationally. Each participant was asked to take a PDA/GPS unit with them every time they rode their bike for seven days. The unit recorded their position every three seconds, providing detailed information on the cyclists’ route. For each trip, the participant inputted the trip purpose (e.g. work, shopping, exercise, etc.) and the weather. After the data was downloaded, participants reviewed maps of each trip and answered questions about the accuracy of the route recorded and factors that influenced that route decision. The downloaded data was linked to the street and bicycle network using GIS. For each trip recorded, we know the date, travel time, speed, distance, and elevation change, in addition to route. Linking the trip to the network reveals whether and for how long and far the cyclist traveled on a road with a bike lane (or other bike facility), a designated bike route, or on a trail/path, in addition to the type of road. Participants also completed a general survey about their bicycling behavior, attitudes towards cycling and other travel modes, perceptions of their environment, and demographics. To date we have collected and processed data from 110 bicyclists. By the end of the calendar year, we expect to have data from 160 cyclists to include in the paper.

Results:
Cyclists participating in the study to date recorded over 1,500 bicycle trips. For these trips, the two most important factors influencing route choice were avoiding streets with lots of vehicle traffic and minimizing total distance. Both factors scored an average of 3.5 on a 1-5 scale (1=not at all important, 5=very important). Riding in a bike lane ranked third (2.9), closely followed by reducing wait time due to stop signs/lights (2.7). The final paper will include analysis of the GPS data, answering the research questions.

Conclusions:
The results of this research will help identify which features of road and bicycle network are correlated with bicycle use and to what extent. The amount of public funds devoted to bicycle infrastructure has increased significantly in recent years. With this increasing level of funding, along with other local policies and standards to increase cycling, it is important that the investments are effective in increasing cycling. The results from this route choice analysis can help inform policies for locating new bicycle infrastructure.

Support:
Robert Wood Johnson Foundation funded via  Active Living Research and Oregon Transportation Research and Education Consortium (OTREC).