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Biking schedules : a new tool for bicycle travel analysis

University of British Columbia

With an increasing focus on bicycling as a mode of urban transportation, there is a pressing need for advanced tools for bicycle travel analysis and modeling. The objective of this thesis is to introduce “Biking schedules” to represent archetypal urban cycling dynamics along with its methods of construction and potential applications. Biking schedules are constructed by appending short trip segments, called microtrips, together. Three different methods of constructing biking schedules with both speed and road grade attributes are developed. As an initial proof-of-concept, the methods are applied and compared using a pre-existing demonstration data set of 55 hours of 1-Hz on-road GPS data from three cyclists. Biking schedules are evaluated based on their ability to represent the speed dynamics, power output, and breathing rates of a calibration data set and then validated for different riders. The impact of using coarser 3, 5, and 10 second GPS logging intervals on the accuracy of the schedules is also evaluated. Results indicate that the best biking schedule construction method depends on the volume and resolution of the calibration data set. Overall, biking schedules can successfully represent most of the assessed characteristics of cycling dynamics in the calibration data set within 5%. As a second step, the biking schedule construction methods are further developed and validated by collecting and applying a large, naturalistic, GPS-based data set of 2314 bicycle trips in Vancouver, Canada. We specifically explored the optimal microtrip definition to be adopted in constructing biking schedules. The choice of the optimal microtrip definition depends on the parameter that biking schedules are originally generated to model. Generally, the 150m microtrips generated the most precise biking schedules. The collected data are also used to compare the travel characteristics and construct biking schedules for regular and electric bikes. Results show that electric bikes travel 7 km/hr and accelerate 0.17 km/hr/sec faster than regular bicycles. Moreover, the total energy used to move electric bikes is almost twice as much as the energy used by regular bikes. These results have implications in designing bike lanes and safety analysis. Potential applications for biking schedules are also discussed.

Text

2018-04-19

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/65514

Civil Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/