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A robotic driver has been designed on the basis of an analysis of a human driver's action in following a given driving schedule. The self-learning algorithm enables the robot to learn the vehicle characteristics without human intervention. Based on learned relationships, the robotic driver can determine an appropriate accelerator position and execute other operations through sophisticated calculations using the future scheduled vehicle speed and vehicle characteristics data. Compensation is also provided to minimize vehicle speed error. The robotic driver can reproduce the same types of exhaust emission and fuel economy data obtained with human drivers with good repeatability. It doesn't require long preparation time. Thereby making it possible to reduce experimentation work in the vehicle development process while providing good accuracy and reliability.

The method for measuring air-fuel ratio is generally based on analysis of the exhaust gas components and its calculations. A new instrument has been developed which uses this method, but it attaches an oxygen sensor for exhaust gas analysis to the exhaust pipe and calculates the air-fuel ratio directly from the sensor output using a microprocessor. The response time of this instrument is 100 milliseconds and because it does not require an exhaust gas sampling system its weight is only 2.5 kg. This paper describes the operation theory, construction and characteristics of this instrument, as well as the results of air-fuel ratio of measurements on engines and vehicles using this instrument in a transient state.