000 05476nam a22005895i 4500
001 978-3-031-01506-9
003 DE-He213
005 20240730163519.0
007 cr nn 008mamaa
008 220601s2020 sz | s |||| 0|eng d
020 _a9783031015069
_9978-3-031-01506-9
024 7 _a10.1007/978-3-031-01506-9
_2doi
050 4 _aTK1-9971
072 7 _aTHR
_2bicssc
072 7 _aTEC007000
_2bisacsh
072 7 _aTHR
_2thema
082 0 4 _a621.3
_223
100 1 _aCao, Haotian.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_978960
245 1 0 _aDecision Making, Planning, and Control Strategies for Intelligent Vehicles
_h[electronic resource] /
_cby Haotian Cao, Mingjun Li, Song Zhao, Xiaolin Song.
250 _a1st ed. 2020.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2020.
300 _aXII, 128 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSynthesis Lectures on Advances in Automotive Technology,
_x2576-8131
505 0 _aAcknowledgments -- Introduction -- Decision Making for Intelligent Vehicles -- Path and Speed Planning for Intelligent Vehicles -- Robust Trajectory Tracking Methods for Intelligent Vehicles -- Control Strategies for Human-Automation Cooperative Driving Systems -- Bibliography -- Authors' Biographies .
520 _aThe intelligent vehicle will play a crucial and essential role in the development of the future intelligent transportation system, which is developing toward the connected driving environment, ultimate driving safety, and comforts, as well as green efficiency. While the decision making, planning, and control are extremely vital components of the intelligent vehicle, these modules act as a bridge, connecting the subsystem of the environmental perception and the bottom-level control execution of the vehicle as well. This short book covers various strategies of designing the decision making, trajectory planning, and tracking control, as well as share driving, of the human-automation to adapt to different levels of the automated driving system. More specifically, we introduce an end-to-end decision-making module based on the deep Q-learning, and improved path-planning methods based on artificial potentials and elastic bands which are designed for obstacle avoidance. Then, the optimal method based on the convex optimization and the natural cubic spline is presented. As for the speed planning, planning methods based on the multi-object optimization and high-order polynomials, and a method with convex optimization and natural cubic splines, are proposed for the non-vehicle-following scenario (e.g., free driving, lane change, obstacle avoidance), while the planning method based on vehicle-following kinematics and the model predictive control (MPC) is adopted for the car-following scenario. We introduce two robust tracking methods for the trajectory following. The first one, based on nonlinear vehicle longitudinal or path-preview dynamic systems, utilizes the adaptive sliding mode control (SMC) law which can compensate for uncertainties to follow the speed or path profiles. The second one is based on the five-degrees-of-freedom nonlinear vehicle dynamical system that utilizes the linearized time-varying MPC to track the speed and path profile simultaneously. Toward human-automation cooperative driving systems, we introduce two control strategies to address the control authority and conflict management problems between the human driver and the automated driving systems. Driving safety field and game theory are utilized to propose a game-based strategy, which is used to deal with path conflicts during obstacle avoidance. Driver's driving intention, situation assessment, and performance index are employed for the development of the fuzzy-based strategy. Multiple case studies and demos are included in each chapter to show the effectiveness of the proposed approach. We sincerely hope the contents of this short book provide certain theoretical guidance and technical supports for the development of intelligent vehicle technology.
650 0 _aElectrical engineering.
_978961
650 0 _aMechanical engineering.
_95856
650 0 _aAutomotive engineering.
_978962
650 0 _aTransportation engineering.
_93560
650 0 _aTraffic engineering.
_915334
650 1 4 _aElectrical and Electronic Engineering.
_978963
650 2 4 _aMechanical Engineering.
_95856
650 2 4 _aAutomotive Engineering.
_978964
650 2 4 _aTransportation Technology and Traffic Engineering.
_932448
700 1 _aLi, Mingjun.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_978965
700 1 _aZhao, Song.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_978966
700 1 _aSong, Xiaolin.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_978967
710 2 _aSpringerLink (Online service)
_978968
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031000102
776 0 8 _iPrinted edition:
_z9783031003783
776 0 8 _iPrinted edition:
_z9783031026348
830 0 _aSynthesis Lectures on Advances in Automotive Technology,
_x2576-8131
_978969
856 4 0 _uhttps://doi.org/10.1007/978-3-031-01506-9
912 _aZDB-2-SXSC
942 _cEBK
999 _c84688
_d84688