This study developed a method to incorporate reduced exposure to traffic-related air pollution as a consideration in the bicycle route planning process in order to improve the quality of the biking experience and promote active travel.
This dissertation studies how individual experiences and skills can inform one's attitudes and adoption of different travel modes. Specifically, the researcher focuses on how childhood bicycling experiences and teenage driver's license delays impact adult travel behavior.
This presentation will discuss the importance of explicitly considering the air quality impact in the planning process with examples from the planning of new bicycle facilities in Riverside, California.
This paper presents a method for incorporating exposure to traffic-related air pollution as another consideration in the bicycle route planning process.
These are the Python scripts used in the research project titled, "BikewaySim Technology Transfer: City of Atlanta, Georgia". Note that these scripts may not be the latest version.
This tabular dataset describes the travel behavior and travel mode related attitudes of residents and bike-share users in the greater Sacramento region.
Investigators tested the influence of an array of explanatory factors on driver’s license possession, using a binomial logistic model, and on license timing, using multilevel survival analysis and censored regression models.