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Over the years, the field of intelligent vehicles has become a major research theme
in intelligent transportation systems since traffic accidents are serious and growing
problems all over the world. The goal of an intelligent vehicle is to augment vehicle
autonomous driving either entirely or partly for the purposes of safety, comfortability,
and saving energy. Indeed, many technologies of intelligent vehicles root in
autonomous mobile robots. The tasks of intelligent vehicles become evenmore challenging
compared to indoor mobile robots for two reasons. First, real-time dynamic
complex environment perception and modeling will challenge current indoor robot
technologies. Autonomous intelligent vehicles have to finish the basic procedures:
perceiving and modeling environment, localizing and building maps, planning paths
and making decisions, and controlling the vehicles within limit time for real-time
purposes. Meanwhile, we face the challenge of processing large amounts of data
from multi-sensors, such as cameras, lidars, radars. This is extremely hard in more
complex outdoor environments. Toward this end, we have to implement those tasks
in more efficient ways. Second, vehiclemotion control faces the challenges of strong
nonlinear characteristics due to high mass, especially in the processes of high speed
and sudden steering. In this case, both lateral and longitudinal control algorithms of
indoor robots do not work well.
This book presents our recent research work on intelligent vehicles and is aimed
at the researchers and graduate students interested in intelligent vehicles. Our goal
in writing this book is threefold. First, it creates an updated reference book of intelligent
vehicles. Second, this book not only presents object/obstacle detection and
recognition, but also introduces vehicle lateral and longitudinal control algorithms,
which benefits the readers keen to learn broadly about intelligent vehicles. Finally,
we put emphasis on high-level concepts, and at the same time provide the low-level
details of implementation. We try to link theory, algorithms, and implementation to
promote intelligent vehicle research. |
