Browsing by Author "Fu, Shan"

Now showing 1 - 4 of 4
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    Advanced driver assistance systems information management and presentation
    (Cranfield University, 2004-06) Dugarry, Alexandre; Fu, Shan
    With the development of advanced driving assistance systems, in-vehicle communication and information systems, there are situations where the driver becomes overloaded by information, creating potentially dangerous conditions. In this Thesis a novel strategy is proposed, to prioritise and present information. Firstly two main criteria are extracted, that allow the ability to rank messages: the risk associated with the non-presentation of the message, and its relevance to the environment. Fuzzy cognitive maps enable to represent expert knowledge and model these relationships. Secondly, a strategy to present information is proposed. Using an importance index, calculated from the previous risk and relevance indices, but also information nature, time constraints and access frequency, a set of best interfaces is selected. Furthermore design a model of driver workload is designed, based on the multiple resources theory. By estimating in real time the workload of the driver, the system enables to choose an optimal interface, that should prevent overload. This Thesis presents then the tools developed for the implementation and testing of the model. A video capture and data transfer program, based on the IEEE-1394 bus, enable in-vehicle real-time data capture and collection. Moreover, a software package for replay of the acquired data, analysis and simulation is developed. Finally, the implementation of the prioritisation and presentation strategy is outlined. The last part of this work is dedicated to the experiments and results. Using an experimental vehicle, data in different driving conditions are collected. the experiment is completed by creating data to simulate potentially dangerous situations, where driver is overloaded with information. The results show that the information management and presentation system is able to prevent overload in most conditions. Its structure and design allow to incorporate expert knowledge to refine the classification.
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    Intelligent imaging systems for automotive applications
    (SPIE, 2003-03-31) Thompson, Chris; Huang, Yingping; Fu, Shan
    In common with many other application areas, visual signals are becoming an increasingly important information source for many automotive applications. For several years CCD cameras have been used as research tools for a range of automotive applications. Infrared cameras, RADAR and LIDAR are other types of imaging sensors that have also been widely investigated for use in cars. This paper will describe work in this field performed in C2VIP over the last decade - starting with Night Vision Systems and looking at various other Advanced Driver Assistance Systems. Emerging from this experience, we make the following observations which are crucial for "intelligent" imaging systems: 1. Careful arrangement of sensor array. 2. Dynamic-Self-Calibration. 3. Networking and processing. 4. Fusion with other imaging sensors, both at the image level and the feature level, provides much more flexibility and reliability in complex situations. We will discuss how these problems can be addressed and what are the outstanding issues.
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    Schlieren methods for high pressure turbulent jet flames
    (2009-06-01T00:00:00Z) Li, L.; Fu, Shan; Witton, John J.
    Turbulent flame speeds of a premixed synthetic natural gas mixture were measured using a jet flow apparatus over a range of pressures to 0·8 MPa at an equivalence ratio of 0·9. The method adopted was the 'flame angle' technique, using schlieren imaging to obtain the flame vertex angle from the peak density gradient. Image analysis techniques were developed to reduce interpretation errors and to give information on the velocity and combined gradient distribution local to the flame fron
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    Vision based experimental investigation of two-phase flow in a rising pipe
    (2003-04-28T00:00:00Z) Fu, Shan; Yeung, Hoi
    Multiphase pipeline flow is very important to oil, gas and process industry. This is a class of problems where comprehensive simulations, although desirable on physical grounds, are not practical due to the large aspect ratio between the pipe length and diameter. In order to enhance the understanding of the pipeline flow, as well as to validate and identify the critical aspects of these models, intensive experimental data are needed. This will define how these models can be improved.