Detection of critical driving situations in motorcycles
type: CreativeWork
description: Motorcycles are statically unstable and only become stabilised in motion, as a result of an induced complex system of dynamic forces. The rapid advancements in computer information and electronic technologies have led to increased interest to address stability issues, hence improving motorcycle safety through embedded electronic systems. The motion along a curved path is one situation often encountered in motorcycles that could lead to loss of control and accidents. This occurs when the lateral frictional forces offered by wheel friction with the ground are not large enough to balance out the induced centrifugal forces. This is for instance encountered under slippery road conditions. In this project, the mathematical theory used to model the dynamics of a motorcycle is used to develop a computer program capable of detecting critical driving conditions in steady turns. The program implements a numerical iterative solution which establishes whether sufficient frictional force is available at the wheel contact points for a set of input conditions including the motorcycle structural design parameters, motorcycle forward velocity and steering angle, and the wheel frictional characteristics. The numerical convergence characteristics of the algorithm are tested in the project by modelling a typical motorcycle over a wide range of operating conditions. The developed computer model is used as basis for the conceptual design of a Critical Driving Detection System which is mainly intended to alert the driver as soon as possible when there exists the possibility of loss of control. The necessary measurement inputs through the use of onboard sensor technology are identified together with mathematical manipulation functions required to enable the most important measurement data to be used directly by the computer model. Furthermore, a data acquisition system for the various measured input parameters of the Critical Driving Detection System was designed and constructed. This inclu…
abstract: Motorcycles are statically unstable and only become stabilised in motion, as a result of an induced complex system of dynamic forces. The rapid advancements in computer information and electronic technologies have led to increased interest to address stability issues, hence improving motorcycle safety through embedded electronic systems. The motion along a curved path is one situation often encountered in motorcycles that could lead to loss of control and accidents. This occurs when the lateral frictional forces offered by wheel friction with the ground are not large enough to balance out the induced centrifugal forces. This is for instance encountered under slippery road conditions. In this project, the mathematical theory used to model the dynamics of a motorcycle is used to develop a computer program capable of detecting critical driving conditions in steady turns. The program implements a numerical iterative solution which establishes whether sufficient frictional force is available at the wheel contact points for a set of input conditions including the motorcycle structural design parameters, motorcycle forward velocity and steering angle, and the wheel frictional characteristics. The numerical convergence characteristics of the algorithm are tested in the project by modelling a typical motorcycle over a wide range of operating conditions. The developed computer model is used as basis for the conceptual design of a Critical Driving Detection System which is mainly intended to alert the driver as soon as possible when there exists the possibility of loss of control. The necessary measurement inputs through the use of onboard sensor technology are identified together with mathematical manipulation functions required to enable the most important measurement data to be used directly by the computer model. Furthermore, a data acquisition system for the various measured input parameters of the Critical Driving Detection System was designed and constructed. This inclu…
language: en
keywords: Traffic accidents, Automobiles -- Collision damage, Technology assessment
date published: 2013
date modified: 2026-07-27T20:11:32Z
provider: University of Malta
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Malta