In recent years, there has been an increasing push among local transportation agencies to encourage bicycling for commuting and recreational purposes. Scientific research has linked bicycling to increased physical activity as well as reduced energy consumption and carbon footprint along with reduced levels of vehicle ownership and traffic congestion. For this purpose, providing appropriate tools to the planning agencies is of primary importance as they can identify and evaluate strategies to promote bicycling along with infrastructure improvements. Thus, in this study we discuss the results related to bicyclists recreational travel behavior in Los Angeles County. As part of this work, statistical models determine propensity and frequency of recreational travel at the individual level. In addition, we also build the predictive model by transferring some parameters from other regions, such as San Francisco and Portland areas. However, the transferability is based on scaling the magnitude of these parameters that accounts for individual trade-off behavior or marginal rates of substitution.

One of the key features of this study, is its ability to jointly determine the decision and frequency of recreational travel of individuals. Additionally, we determine this demand both at disaggregate and aggregate levels for policy analysis. Further, we also report results based on the methodology that allocates recreational trips to individual bicycle facilities, thereby predicting bicycle miles traveled (BMT) within the region. Overall, we control for individual and household demographics (i.e., age, gender and household composition and vehicle ownership) along with built-environment attributes (i.e., presence and access to bicycle facilities and transit connectivity). The final objective of this study is to provide Los Angeles County Metropolitan Transportation Authority with a GIS-based tool that unifies the proposed framework in evaluating their strategies for bicycle planning purposes. Moreover, within this framework we also demonstrate the capability of the toolbox in predicting future demand for bicycle recreational travel in Los Angeles County based on changes in future sociodemographic and built-environment characteristics.