A Train cruise control system was developed using fuzzy rules to emulate the normal driver actions and judgments. The resultant train control was evaluated by using train simulation. The fuzzy rule base developed provided target power and braking levels based on assessments of grades, speed restrictions and current train speed. The control levels were further filtered using driving practice rules. The paper presents details and examples of the system in operation. The possible implementation and benefits of the system as a train advice system, or as a cruise control (non-vital control system), or as part of a vital control system are also discussed
The goal of Intelligent Transport Systems (ITS) is to fully automate driving. ITS is the application...
Artificial intelligence techniques applied to control processes are particularly useful when the ele...
This paper discusses a knowledge-based system that uses fuzzy set techniques to plan train circulati...
Optimisation of driving strategies for safety, fatigue, energy and timeliness were investigated usin...
A procedure for the data driven generation of fuzzy rules is described, which was used in the develo...
In order to improve the active safety driving vehicle and alleviate the intension of driving fatigue...
In order to improve the active safety driving vehicle and alleviate the intension of driving fatigue...
In rapid transit applications, it is often necessary to optimize the ride of the train for certain p...
M.Ing.The principal reasons for the development of a prototype improved control system are the high ...
This study aims to implement fuzzy logic controller using Mamdani and defuzzification method of Cent...
Artificial intelligence techniques applied to control processes are particularly useful when the ele...
Trabajo presentado en la International Conference on Computer Aided Systems Theory (EUROCAST 2003), ...
This study aims to implement fuzzy logic controller using Mamdani and defuzzification method of Cent...
Train controls at the Montreal Subway are revisited. A simulation environment is developed and used ...
Usually, vehicle applications require the use of artificial intelligent techniques to implement cont...
The goal of Intelligent Transport Systems (ITS) is to fully automate driving. ITS is the application...
Artificial intelligence techniques applied to control processes are particularly useful when the ele...
This paper discusses a knowledge-based system that uses fuzzy set techniques to plan train circulati...
Optimisation of driving strategies for safety, fatigue, energy and timeliness were investigated usin...
A procedure for the data driven generation of fuzzy rules is described, which was used in the develo...
In order to improve the active safety driving vehicle and alleviate the intension of driving fatigue...
In order to improve the active safety driving vehicle and alleviate the intension of driving fatigue...
In rapid transit applications, it is often necessary to optimize the ride of the train for certain p...
M.Ing.The principal reasons for the development of a prototype improved control system are the high ...
This study aims to implement fuzzy logic controller using Mamdani and defuzzification method of Cent...
Artificial intelligence techniques applied to control processes are particularly useful when the ele...
Trabajo presentado en la International Conference on Computer Aided Systems Theory (EUROCAST 2003), ...
This study aims to implement fuzzy logic controller using Mamdani and defuzzification method of Cent...
Train controls at the Montreal Subway are revisited. A simulation environment is developed and used ...
Usually, vehicle applications require the use of artificial intelligent techniques to implement cont...
The goal of Intelligent Transport Systems (ITS) is to fully automate driving. ITS is the application...
Artificial intelligence techniques applied to control processes are particularly useful when the ele...
This paper discusses a knowledge-based system that uses fuzzy set techniques to plan train circulati...