使用近似的高階資訊於基於模糊邏輯的TORCS模擬汽車控制器之研究

Abstract

本文主要的研究目的在於藉由使用高階資訊的方式，以模糊邏輯的方式實現，將其應用在模擬汽車控制器上，讓控制器上面的人工智慧能夠以接近人類的思考方式做出恰當的反應。 高階資訊藉由控制器本身的偵測器偵測前方賽道，經模糊系統轉換成賽道中距離前方彎道的距離和目標彎道的極緩程度等資訊，控制器再利用這些資訊思考策略並決定速度、入彎位置、出彎方式…等等，作出近似人類思考模式的駕駛行為。

The main idea of thesis is that by using high-level information implemented by fuzzy logic based simulated car controller. The artificial of intelligence of controller can make proper decision or reaction based on the high-level information. The high-level information obtained by sensor detecting the distance between car and track, the fuzzy system transform this information into distance from the corner and the sharpness of the corner, then the controller planning to drive with the target speed and the proper position.