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Path Planning and Tracking for Vehicle Collision Avoidance in Lateral and Longitudinal Motion Directions (Paperback)
Loot Price: R1,636
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Path Planning and Tracking for Vehicle Collision Avoidance in Lateral and Longitudinal Motion Directions (Paperback)
Series: Synthesis Lectures on Advances in Automotive Technology
Expected to ship within 10 - 15 working days
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In recent years, the control of Connected and Automated Vehicles
(CAVs) has attracted strong attention for various automotive
applications. One of the important features demanded of CAVs is
collision avoidance, whether it is a stationary or a moving
obstacle. Due to complex traffic conditions and various vehicle
dynamics, the collision avoidance system should ensure that the
vehicle can avoid collision with other vehicles or obstacles in
longitudinal and lateral directions simultaneously. The
longitudinal collision avoidance controller can avoid or mitigate
vehicle collision accidents effectively via Forward Collision
Warning (FCW), Brake Assist System (BAS), and Autonomous Emergency
Braking (AEB), which has been commercially applied in many new
vehicles launched by automobile enterprises. But in lateral motion
direction, it is necessary to determine a flexible collision
avoidance path in real time in case of detecting any obstacle.
Then, a path-tracking algorithm is designed to assure that the
vehicle will follow the predetermined path precisely, while
guaranteeing certain comfort and vehicle stability over a wide
range of velocities. In recent years, the rapid development of
sensor, control, and communication technology has brought both
possibilities and challenges to the improvement of vehicle
collision avoidance capability, so collision avoidance system still
needs to be further studied based on the emerging technologies. In
this book, we provide a comprehensive overview of the current
collision avoidance strategies for traditional vehicles and CAVs.
First, the book introduces some emergency path planning methods
that can be applied in global route design and local path
generation situations which are the most common scenarios in
driving. A comparison is made in the path-planning problem in both
timing and performance between the conventional algorithms and
emergency methods. In addition, this book introduces and designs an
up-to-date path-planning method based on artificial potential field
methods for collision avoidance, and verifies the effectiveness of
this method in complex road environment. Next, in order to
accurately track the predetermined path for collision avoidance,
traditional control methods, humanlike control strategies, and
intelligent approaches are discussed to solve the path-tracking
problem and ensure the vehicle successfully avoids the collisions.
In addition, this book designs and applies robust control to solve
the path-tracking problem and verify its tracking effect in
different scenarios. Finally, this book introduces the basic
principles and test methods of AEB system for collision avoidance
of a single vehicle. Meanwhile, by taking advantage of data sharing
between vehicles based on V2X (vehicle-to-vehicle or
vehicle-to-infrastructure) communication, pile-up accidents in
longitudinal direction are effectively avoided through cooperative
motion control of multiple vehicles.
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