Measuring Cyclist’s Inputs, the Kinematic and Dynamic Properties of a City Bicycle, and Estimating the Road Profile via Sensor Fusion

Abstract

In this paper, we present the instrumentation of a city bicycle with different sensors and devic-es in order to measure cyclists’ inputs (i.e., pedaling and steering) and the dynamical and kinematic properties of the bicycle. The instrumentation includes two tri-axial accelerometers, an Inertial Measurement Unit (IMU), GPS, a potentiometer, a laser scanner, a pedaling power meter, and speed and cadence sensors, in addition to a mobile eye tracker worn by the cyclists. After the instrumentation and adjustment of the sensors, a study was conducted in the city of Stockholm using the instrumented bicycle with the aim to evaluate cycling safety and comfort on snowy surface conditions. The outputs of this experiment will be employed further to study the interaction of cyclists with road infrastructure and other road users and their impact on cyclists’ behavior and cycling safety.

The Visual Behaviour of the Cyclist: Comparison between Simulated and Real Scenarios

“…For the on-site test, 64% of the users had familiarity with the experiment route (57% of males, 75% of females). However, none of them had used a bicycle simulator before [53,54]. No user knew the purpose of the test, so as not to affect the results.…”

“…The software repeats the procedure until it reaches an accuracy for the ap pearance position of 0.60 (Figure 5). After data had been acquired using pupil captur with a laptop, the Pupil Player software was used to post-process the eye-tracking dat [53]. Through the overlap of the two images linked to the pupil and the external environ ment, it is possible to obtain a video that evaluates the ocular path in relation to the se quence of external images, both in the external environment and in the simulator (Figure 5 and 6).…”

Assessing the Accessibility of Cycling Infrastructure for Wheelchair Users: Insights from an On-Road Experiment and Online Questionnaire Study

“…The case study shows that there are similar behaviors between cyclists and wheelchairusers when sharing cycling infrastructure; for example, both road users expect smooth surfaces and well-designed ramps to make their commuting faster and more comfortable [33,34]; both are affected by the improper geometric design of the road, which force them to depart the lane on sharp curves and took shortcuts to shorten the traveled distance. It is also noticed that wheelchair users are more affected by the unevenness of the road profile, which forces them to reduce their speed more often than cyclists.…”