Zhang, Yizhen (2006) Engineering design synthesis of sensor and control systems for intelligent vehicles. Dissertation (Ph.D.), California Institute of Technology. http://resolver.caltech.edu/CaltechETD:etd-05252006-221412
This thesis investigates the application of formal engineering design synthesis methodologies to the development of sensor and control systems for intelligent vehicles.
A formal engineering design synthesis methodology based on evolutionary computation is presented, with special emphasis on dealing with modern engineering design challenges, such as high or variable complexity of design solutions, multiple conflicting design objectives, and noisy evaluation results, etc. The efficacy of the evolutionary design synthesis method is validated through multiple different case studies, where a variety of novel design solutions are generated to represent different engineering design trade-offs, and they have achieved performances comparable to, if not better than, that of hand-coded solutions in the same simplified environment. More importantly, this automatic design synthesis method shows great potential to handle more complex design problems, where a good hand-coded solution may be very difficult or even impossible to obtain. Moreover, the evolutionary design synthesis methodology appears promising to deal with uncertainty in the problem efficiently and adapt to the collective task nature well.
In addition, multiple levels of vehicle simulation models with different computational cost and fidelity as well as necessary driver behaviors are implemented for different types of simulation experiments conducted for different research purposes. Efforts are made to try to generate good candidate solutions efficiently with less computational time and human engineering effort.
Furthermore, a new threat assessment measure, time-to-last-second-braking (Tlsb), is proposed, which directly characterizes human natural judgment of the urgency and severity of threats in terms of time. Based on driver reaction time experimental results, new warning and overriding criteria are proposed in terms of the new Tlsb measure, and the performance is analyzed statistically in terms of two typical sample pre-crash traffic scenarios. Less affected by driver behavior variability, the new criteria characterize the current dynamic situations better than the previous ones, providing more appropriate warning and more effective overriding at the last moment. Finally, the possibility of frontal collision avoidance through steering (lane-changing) is discussed, and similarly the time-to-last-second-steering (Tlss) measure is proposed and compared with Tlsb.
|Item Type:||Thesis (Dissertation (Ph.D.))|
|Subject Keywords:||collision warning; evolutionary robotics; last-second braking; neural network; sensor evolution; Webots simulation|
|Degree Grantor:||California Institute of Technology|
|Division:||Engineering and Applied Science|
|Major Option:||Mechanical Engineering|
|Thesis Availability:||Public (worldwide access)|
|Defense Date:||3 May 2006|
|Author Email:||yizhen (AT) caltech.edu|
|Default Usage Policy:||No commercial reproduction, distribution, display or performance rights in this work are provided.|
|Deposited By:||Imported from ETD-db|
|Deposited On:||01 Jun 2006|
|Last Modified:||26 Dec 2012 02:46|
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