说明：as well as to non-vehicle use
cases with bicycles and motorbikes, vehicle-to pedestrian (V2P), vehicle-to-home
(V2H) and vehicle-to-grid (V2G), vehicle-to-network (V2N)) and infotainment. <renyilu> 上传 | 大小：6mb
说明：自动驾驶架构设计，IEEE论文
Architecture design is one of the most important problems for an intelligent system. In this paper, a practical framework of hardware and software is proposed to reveal the external configuration and internal mechanism of an autonomou <AaronFu> 上传 | 大小：7mb
说明：Advancing to higher levels of driving automation brings unpredicted challenges and with them, many situations that cannot be foreseen. In order to overcome these problems, set of functionalities in modern vehicle is growing in terms of algorithmic co <AaronFu> 上传 | 大小：328kb
说明：What machine learning (ML) technique is used for system intelligence implementation in ADAS (advanced driving assistance system)? This paper tries to answer this question. This paper analyzes ADAS and ML independently and then relate which ML techniq <AaronFu> 上传 | 大小：6mb
说明：The technological advancements of recent years have steadily increased the complexity of vehicle-internal software systems, and the ongoing development towards autonomous driving will further aggravate this situation. This is leading to a level of co <AaronFu> 上传 | 大小：163kb
说明：In this paper, we present a hierarchical mapping method that allows us to obtain accurate metric maps of large en- vironments in real time. The lower (or local) map level is composed of a set of local maps that are guaranteed to be statistically inde <AaronFu> 上传 | 大小：455kb
说明：This position paper introduces the concept of ar- tificial “co-drivers” as an enabling technology for future intel- ligent transportation systems. In Sections I and II, the design principles of co-drivers are introduced and framed within gen- eral hu <AaronFu> 上传 | 大小：1mb
