000 | 05685nam a22005775i 4500 | ||
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001 | 978-3-031-01507-6 | ||
003 | DE-He213 | ||
005 | 20240730165127.0 | ||
007 | cr nn 008mamaa | ||
008 | 220601s2021 sz | s |||| 0|eng d | ||
020 |
_a9783031015076 _9978-3-031-01507-6 |
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024 | 7 |
_a10.1007/978-3-031-01507-6 _2doi |
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050 | 4 | _aTK1-9971 | |
072 | 7 |
_aTHR _2bicssc |
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_aTEC007000 _2bisacsh |
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072 | 7 |
_aTHR _2thema |
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082 | 0 | 4 |
_a621.3 _223 |
100 | 1 |
_aJi, Jie. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _987529 |
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245 | 1 | 0 |
_aPath Planning and Tracking for Vehicle Collision Avoidance in Lateral and Longitudinal Motion Directions _h[electronic resource] / _cby Jie Ji, Hong Wang, Yue Ren. |
250 | _a1st ed. 2021. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2021. |
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300 |
_aXII, 144 p. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aSynthesis Lectures on Advances in Automotive Technology, _x2576-8131 |
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505 | 0 | _aAcknowledgments -- Introduction -- Path-Planning Algorithms for Collision Avoidance -- Path-Tracking Algorithms for Collision Avoidance -- Optimal Local Trajectory for Vehicle Collision Avoidance Maneuvers -- Design of Robust Feedback Controller for Path Tracking -- Collision Avoidance in Longitudinal Direction With/Without V2X Communication -- Conclusions and Future Works -- References -- Authors' Biographies . | |
520 | _aIn 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 designedto 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. | ||
650 | 0 |
_aElectrical engineering. _987532 |
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650 | 0 |
_aMechanical engineering. _95856 |
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650 | 0 |
_aAutomotive engineering. _987534 |
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650 | 0 |
_aTransportation engineering. _93560 |
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650 | 0 |
_aTraffic engineering. _915334 |
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650 | 1 | 4 |
_aElectrical and Electronic Engineering. _987536 |
650 | 2 | 4 |
_aMechanical Engineering. _95856 |
650 | 2 | 4 |
_aAutomotive Engineering. _987540 |
650 | 2 | 4 |
_aTransportation Technology and Traffic Engineering. _932448 |
700 | 1 |
_aWang, Hong. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _987542 |
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700 | 1 |
_aRen, Yue. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _987543 |
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710 | 2 |
_aSpringerLink (Online service) _987546 |
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773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783031000119 |
776 | 0 | 8 |
_iPrinted edition: _z9783031003790 |
776 | 0 | 8 |
_iPrinted edition: _z9783031026355 |
830 | 0 |
_aSynthesis Lectures on Advances in Automotive Technology, _x2576-8131 _987547 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-031-01507-6 |
912 | _aZDB-2-SXSC | ||
942 | _cEBK | ||
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