Vehicle self-localization is an important and challenging issue in current driving assistance and autonomous driving research activities. This paper mainly investigates two kinds of methods for vehicle self-localization: active sensor based and passive sensor based. Active sensor based localization was firstly proposed for robot localization, and was introduced into autonomous driving recently. The Simultaneous Localization and Mapping (SLAM) techniques is the representative in active sensor based localization. The passive sensor based localization technologies are categorized and explained based on the type of sensors, Global Navigation Satellite System (GNSS), inertial sensors and cameras. In this paper, researches utilizing active sensors and passive sensors for autonomous vehicles are reviewed extensively. Finally, our challenges on self-localization in urban canyon by the system integration of passive sensors is introduced. GNSS error has been improved for the purpose of the self-localization in urban canyon. The performance of the proposed method would suggest possible solution autonomous vehicles which makes use of passive sensors more.