Application of Newtonian physics to predict the speed of a gravity racer

Gravity racing can be studied using numerical solutions to the equations of motion derived from Newton’s second law. This allows students to explore the physics of gravity racing and to understand how design and course selection influences vehicle speed. Using Euler’s method, we have developed a spreadsheet application that can be used to predict the speed of a gravity powered vehicle. The application includes the effects of air and rolling resistance. Examples of the use of the application for designing a gravity racer are presented and discussed. Predicted speeds are compared to the results of an official world record attempt

The usefulness of GPS bicycle tracking data for evaluating the impact of infrastructure change on bicycling behaviour

<b>Issue addressed</b>\ud \ud - A key strategy to increase active travel is the construction of bicycle infrastructure. Tools to evaluate this strategy are limited. This study assessed the usefulness of a smartphone GPS tracking system for evaluating the impact of this strategy on behavioural outcomes. \ud \ud <b>Methods</b>\ud \ud - Bicycling usage data were collected from Queenslanders who used a GPS tracking app on their smartphone in 2013-2014. ‘Heat’ and volume maps of the data were reviewed, and GPS bicycle counts were compared with surveillance data and bicycle counts from automatic traffic monitoring devices. \ud \ud <b>Results</b>\ud \ud - Heat maps broadly indicated changes in bicycling near infrastructure improvements. Volume maps provided changes in counts of cyclists due to these improvements although errors were noted in GIS geocoding of some GPS data. Large variations in cyclists’ use of the app across different cycling locations were evident. This variation limited the use of the GPS data for assessing differential changes in bicycling across locations. \ud \ud <b>Conclusion</b>\ud \ud - Smartphone GPS data are best for evaluating the impact of infrastructure improvement in one location. GPS data are problematic for making inferences about differential changes in bicycling across locations without sufficient numbers of traffic monitoring devices being available for triangulating GPS data with bicycle traffic count data. \ud So what? Smartphone GPS data can supplement existing data sources for evaluating changes in bicycling around a location in a transport network. These data are recommended for use in combination with existing data sources to improve our understanding of the influence of built environment change on cycling behaviour