Bike unturned: Estimating the tilt during turns
Problem Statement:
The world of mobility is being digitized, resulting in an intelligent transportation system (ITS). Bicycles can play a significant role in this, and can even become a key pillar of a sustainable, safe and effective mobile society. However, so far they are not fully integrated into the new era, which will bring potential risks due to the shared road infrastructures and unexpected cycling behaviour. Our group in collaboration with TU Delft, TNO, Accell group and Saxion University of Applied Science is developing and testing a novel connected vehicles ecosystem which combines the capabilities of sensing, wireless technology and data science to make bicycle transportation more safe, reliable, and comfortable (more information can be found here).
One of the subproblems we are addressing now is the lateral maneuvering of bikes during cycling. Improper tilting of bikes will cause the cyclists to fall and bring an accident.
Task:
This project aims to understand to what extent the riders would tilt the bikes towards the direction of the turn to make safe manoeuvre. Data collection using modern sensors, e.g., cameras and IMU sensors, is needed for different weather conditions. Based on the collected data, further data analytics will be done to understand the tilting angle of the cyclists.
Work:
40% Data collection, 40% data analytics, 20%Writing
Contact:
Akhil Pallamreddy (a.r.pallamreddy@utwente.nl)