Fast lane: Estimating the speed 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 behavior. 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 acceleration/deceleration of bikes will cause the cyclists to fall and bring an accident.
Task:
This project aims to understand to what extent the riders would accelerate/decelerate the bike to make safe turn. Data collection using modern sensors, e.g., cameras, accelerometers and IMU sensors, is needed for different road conditions. Based on the collected data, further data analytics will be done to understand the tilting angle and speed during the turns of the bicycle.
Work:
40% Data collection, 40% data analytics, 20%Writing
Contact:
Akhil Pallamreddy (a.r.pallamreddy@utwente.nl)