Local Path Planning for Autonomous Vehicles Based on the Natural Behavior of the Biological Action-Perception Motion

Local path planning is a key task for the motion planners of autonomous vehicles since it commands the vehicle across its environment while avoiding any obstacles. To perform this task, the local path planner generates a trajectory and a velocity profile, which are then sent to the vehicle’s actuato...

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Published inEnergies (Basel) Vol. 15; no. 5; p. 1769
Main Authors Bautista-Camino, Pedro, Barranco-Gutiérrez, Alejandro, Cervantes, Ilse, Rodríguez-Licea, Martin, Prado-Olivarez, Juan, Pérez-Pinal, Francisco
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.03.2022
Subjects
Acceleration
Actuators
Algorithms
Artificial intelligence
Autonomous vehicles
Behavior
Constraint modelling
Design
Elections
Fuzzy logic
Kinematics
local path planning
Localization
Mathematical functions
Motion detection
Motion planning
obstacles avoidance
Optimization techniques
Planning
Robots
Security
Trajectory planning
Vehicles
Velocity distribution
Visual perception
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Abstract Local path planning is a key task for the motion planners of autonomous vehicles since it commands the vehicle across its environment while avoiding any obstacles. To perform this task, the local path planner generates a trajectory and a velocity profile, which are then sent to the vehicle’s actuators. This paper proposes a new local path planner for autonomous vehicles based on the Attractor Dynamic Approach (ADA), which was inspired by the behavior of movement of living beings, along with an algorithm that takes into account four acceleration policies, the ST dynamic vehicle model, and several constraints regarding the comfort and security. The original functions that define the ADA were modified in order to adapt it to the non-holonomic vehicle’s constraints and to improve its response when an impact scenario is detected. The present approach is validated in a well-known simulator for autonomous vehicles under three representative cases of study where the vehicle was capable of generating local paths that ensure the security of the vehicle in such cases. The results show that the approach proposed in this paper is a promising tool for the local path planning of autonomous vehicles since it is able to generate trajectories that are both safe and efficient.
AbstractList Local path planning is a key task for the motion planners of autonomous vehicles since it commands the vehicle across its environment while avoiding any obstacles. To perform this task, the local path planner generates a trajectory and a velocity profile, which are then sent to the vehicle’s actuators. This paper proposes a new local path planner for autonomous vehicles based on the Attractor Dynamic Approach (ADA), which was inspired by the behavior of movement of living beings, along with an algorithm that takes into account four acceleration policies, the ST dynamic vehicle model, and several constraints regarding the comfort and security. The original functions that define the ADA were modified in order to adapt it to the non-holonomic vehicle’s constraints and to improve its response when an impact scenario is detected. The present approach is validated in a well-known simulator for autonomous vehicles under three representative cases of study where the vehicle was capable of generating local paths that ensure the security of the vehicle in such cases. The results show that the approach proposed in this paper is a promising tool for the local path planning of autonomous vehicles since it is able to generate trajectories that are both safe and efficient.
Author Bautista-Camino, Pedro
Rodríguez-Licea, Martin
Barranco-Gutiérrez, Alejandro
Prado-Olivarez, Juan
Cervantes, Ilse
Pérez-Pinal, Francisco
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CitedBy_id crossref_primary_10_1007_s13369_023_08541_x
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Cites_doi 10.3390/s21237898
10.3390/electronics8090943
10.1007/s11370-020-00314-x
10.1016/j.aej.2021.04.074
10.3390/electronics11030294
10.1016/j.vlsi.2017.07.007
10.3390/electronics9111826
10.1109/TITS.2015.2498841
10.1177/0954407021993623
10.1109/MC.2017.3001256
10.1109/TVCG.2021.3114777
10.1109/TITS.2019.2913998
10.1504/IJVAS.2018.096154
10.1016/0921-8890(92)90004-I
10.1109/CWCAS.2014.6994609
10.1109/LRA.2019.2926224
10.1109/ACCESS.2020.2984695
10.23919/ChiCC.2018.8482915
10.1002/rob.20255
10.23919/AEITAUTOMOTIVE50086.2020.9307439
10.1109/TITS.2020.3024655
10.1016/j.trc.2018.12.003
10.1109/TIV.2021.3123341
10.1016/j.ymssp.2015.10.021
10.3390/en14237974
10.1109/TITS.2019.2901817
10.1109/IVS.2017.7995802
10.1109/ACCESS.2020.2983149
10.1109/MITS.2019.2953551
10.1109/TRO.2010.2085790
10.1109/TITS.2017.2756099
10.3390/machines5010006
10.1093/acprof:oso/9780199300563.001.0001
10.1109/ACCESS.2018.2868339
10.1109/LRA.2021.3135940
10.1109/IVS.2015.7225800
10.1109/TIV.2018.2874532
10.1109/ICCES.2018.8639396
10.1007/s40313-013-0006-5
10.1002/rob.20147
10.3390/en12122342
10.1080/13588265.2016.1164444
10.1109/ITSC.2019.8917427
10.1109/JAS.2017.7510811
10.1109/TIE.2019.2898599
10.23919/EETA.2019.8804556
10.1080/00423119408969076
10.1109/TMECH.2015.2493980
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References Li (ref_18) 2017; 87
Grigorescu (ref_33) 2019; 4
Guo (ref_3) 2018; 5
Aradi (ref_10) 2020; 23
ref_14
Claussmann (ref_22) 2019; 21
Abraham (ref_50) 2016; 21
ref_56
ref_55
ref_54
ref_52
ref_51
Receveur (ref_42) 2020; 13
ref_19
Suzuki (ref_31) 2018; 3
Song (ref_32) 2020; 8
Li (ref_16) 2015; 21
Nashashibi (ref_21) 2016; 17
ref_25
ref_23
Rasouli (ref_8) 2019; 21
ref_20
Choi (ref_30) 2010; 40
Huang (ref_5) 2022; 61
ref_29
ref_27
ref_26
Gkartzonikas (ref_1) 2019; 98
Lim (ref_11) 2018; 19
Hou (ref_9) 2021; 28
ref_34
Fancher (ref_53) 1994; 23
Yu (ref_38) 2018; 6
Li (ref_17) 2021; 7
Soulignac (ref_13) 2010; 27
Zong (ref_28) 2021; 235
Urmson (ref_12) 2008; 25
ref_39
ref_37
Pereira (ref_24) 2013; 24
Feraco (ref_36) 2020; 83938
ref_47
ref_45
ref_44
Dose (ref_43) 1992; 10
ref_41
Shi (ref_7) 2017; 59
Huang (ref_40) 2019; 67
Thrun (ref_49) 2006; 23
Yurtsever (ref_2) 2020; 8
Hamid (ref_35) 2018; 14
ref_48
Qian (ref_15) 2020; 14
Machado (ref_46) 2018; 43
Liu (ref_57) 2017; 50
ref_4
ref_6
References_xml – ident: ref_14
  doi: 10.3390/s21237898
– ident: ref_52
  doi: 10.3390/electronics8090943
– volume: 13
  start-page: 315
  year: 2020
  ident: ref_42
  article-title: Autonomous car decision making and trajectory tracking based on genetic algorithms and fractional potential fields
  publication-title: Intell. Serv. Robot.
  doi: 10.1007/s11370-020-00314-x
  contributor:
    fullname: Receveur
– volume: 61
  start-page: 911
  year: 2022
  ident: ref_5
  article-title: Application of interval state estimation in vehicle control
  publication-title: Alex. Eng. J.
  doi: 10.1016/j.aej.2021.04.074
  contributor:
    fullname: Huang
– ident: ref_54
  doi: 10.3390/electronics11030294
– volume: 59
  start-page: 148
  year: 2017
  ident: ref_7
  article-title: Algorithm and hardware implementation for visual perception system in autonomous vehicle: A survey
  publication-title: Integration
  doi: 10.1016/j.vlsi.2017.07.007
  contributor:
    fullname: Shi
– ident: ref_19
  doi: 10.3390/electronics9111826
– volume: 17
  start-page: 1135
  year: 2016
  ident: ref_21
  article-title: A Review of Motion Planning Techniques for Automated Vehicles
  publication-title: IEEE Trans. Intell. Transp. Syst.
  doi: 10.1109/TITS.2015.2498841
  contributor:
    fullname: Nashashibi
– volume: 235
  start-page: 2086
  year: 2021
  ident: ref_28
  article-title: Research on local path planning based on improved RRT algorithm
  publication-title: Proc. Inst. Mech. Eng. Part D J. Automob. Eng.
  doi: 10.1177/0954407021993623
  contributor:
    fullname: Zong
– ident: ref_39
– volume: 50
  start-page: 18
  year: 2017
  ident: ref_57
  article-title: Computer architectures for autonomous driving
  publication-title: Computer
  doi: 10.1109/MC.2017.3001256
  contributor:
    fullname: Liu
– volume: 28
  start-page: 1030
  year: 2021
  ident: ref_9
  article-title: Visual Evaluation for Autonomous Driving
  publication-title: IEEE Trans. Vis. Comput. Graph.
  doi: 10.1109/TVCG.2021.3114777
  contributor:
    fullname: Hou
– volume: 21
  start-page: 1826
  year: 2019
  ident: ref_22
  article-title: A review of motion planning for highway autonomous driving
  publication-title: IEEE Trans. Intell. Transp. Syst.
  doi: 10.1109/TITS.2019.2913998
  contributor:
    fullname: Claussmann
– volume: 14
  start-page: 134
  year: 2018
  ident: ref_35
  article-title: A review on threat assessment, path planning and path tracking strategies for collision avoidance systems of autonomous vehicles
  publication-title: Int. J. Veh. Auton. Syst.
  doi: 10.1504/IJVAS.2018.096154
  contributor:
    fullname: Hamid
– volume: 10
  start-page: 253
  year: 1992
  ident: ref_43
  article-title: A dynamical systems approach to task-level system integration used to plan and control autonomous vehicle motion
  publication-title: Robot. Auton. Syst.
  doi: 10.1016/0921-8890(92)90004-I
  contributor:
    fullname: Dose
– ident: ref_48
  doi: 10.1109/CWCAS.2014.6994609
– ident: ref_56
– volume: 4
  start-page: 3441
  year: 2019
  ident: ref_33
  article-title: NeuroTrajectory: A Neuroevolutionary Approach to Local State Trajectory Learning for Autonomous Vehicles
  publication-title: IEEE Robot. Autom. Lett.
  doi: 10.1109/LRA.2019.2926224
  contributor:
    fullname: Grigorescu
– volume: 8
  start-page: 62107
  year: 2020
  ident: ref_32
  article-title: Dynamic Path Planning for Unmanned Vehicles Based on Fuzzy Logic and Improved Ant Colony Optimization
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2020.2984695
  contributor:
    fullname: Song
– ident: ref_41
– ident: ref_26
  doi: 10.23919/ChiCC.2018.8482915
– volume: 25
  start-page: 425
  year: 2008
  ident: ref_12
  article-title: Autonomous driving in urban environments: Boss and the urban challenge
  publication-title: J. Field Robot.
  doi: 10.1002/rob.20255
  contributor:
    fullname: Urmson
– ident: ref_27
  doi: 10.23919/AEITAUTOMOTIVE50086.2020.9307439
– volume: 23
  start-page: 740
  year: 2020
  ident: ref_10
  article-title: Survey of deep reinforcement learning for motion planning of autonomous vehicles
  publication-title: IEEE Trans. Intell. Transp. Syst.
  doi: 10.1109/TITS.2020.3024655
  contributor:
    fullname: Aradi
– volume: 98
  start-page: 323
  year: 2019
  ident: ref_1
  article-title: What have we learned? A review of stated preference and choice studies on autonomous vehicles
  publication-title: Transp. Res. Part C Emerg. Technol.
  doi: 10.1016/j.trc.2018.12.003
  contributor:
    fullname: Gkartzonikas
– ident: ref_45
– ident: ref_55
  doi: 10.1109/TIV.2021.3123341
– volume: 87
  start-page: 118
  year: 2017
  ident: ref_18
  article-title: Development of a new integrated local trajectory planning and tracking control framework for autonomous ground vehicles
  publication-title: Mech. Syst. Signal Process.
  doi: 10.1016/j.ymssp.2015.10.021
  contributor:
    fullname: Li
– ident: ref_4
  doi: 10.3390/en14237974
– volume: 21
  start-page: 900
  year: 2019
  ident: ref_8
  article-title: Autonomous vehicles that interact with pedestrians: A survey of theory and practice
  publication-title: IEEE Trans. Intell. Transp. Syst.
  doi: 10.1109/TITS.2019.2901817
  contributor:
    fullname: Rasouli
– ident: ref_51
  doi: 10.1109/IVS.2017.7995802
– volume: 8
  start-page: 58443
  year: 2020
  ident: ref_2
  article-title: A survey of autonomous driving: Common practices and emerging technologies
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2020.2983149
  contributor:
    fullname: Yurtsever
– volume: 14
  start-page: 57
  year: 2020
  ident: ref_15
  article-title: Synchronous Maneuver Searching and Trajectory Planning for Autonomous Vehicles In Dynamic Traffic Environments
  publication-title: IEEE Intell. Transp. Syst. Mag.
  doi: 10.1109/MITS.2019.2953551
  contributor:
    fullname: Qian
– volume: 27
  start-page: 89
  year: 2010
  ident: ref_13
  article-title: Feasible and optimal path planning in strong current fields
  publication-title: IEEE Trans. Robot.
  doi: 10.1109/TRO.2010.2085790
  contributor:
    fullname: Soulignac
– volume: 19
  start-page: 613
  year: 2018
  ident: ref_11
  article-title: Hierarchical trajectory planning of an autonomous car based on the integration of a sampling and an optimization method
  publication-title: IEEE Trans. Intell. Transp. Syst.
  doi: 10.1109/TITS.2017.2756099
  contributor:
    fullname: Lim
– ident: ref_47
– ident: ref_6
  doi: 10.3390/machines5010006
– ident: ref_20
  doi: 10.1093/acprof:oso/9780199300563.001.0001
– volume: 83938
  start-page: V004T04A006
  year: 2020
  ident: ref_36
  article-title: Optimal Trajectory Generation Using an Improved Probabilistic Road Map Algorithm for Autonomous Driving
  publication-title: Am. Soc. Mech. Eng.
  contributor:
    fullname: Feraco
– volume: 6
  start-page: 53960
  year: 2018
  ident: ref_38
  article-title: A Path Planning and Navigation Control System Design for Driverless Electric Bus
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2018.2868339
  contributor:
    fullname: Yu
– volume: 7
  start-page: 984
  year: 2021
  ident: ref_17
  article-title: Learning an Explainable Trajectory Generator Using the Automaton Generative Network (AGN)
  publication-title: IEEE Robot. Autom. Lett.
  doi: 10.1109/LRA.2021.3135940
  contributor:
    fullname: Li
– ident: ref_37
  doi: 10.1109/IVS.2015.7225800
– ident: ref_44
– volume: 3
  start-page: 547
  year: 2018
  ident: ref_31
  article-title: Automatic Two-Lane Path Generation for Autonomous Vehicles Using Quartic B-Spline Curves
  publication-title: IEEE Trans. Intell. Veh.
  doi: 10.1109/TIV.2018.2874532
  contributor:
    fullname: Suzuki
– ident: ref_34
  doi: 10.1109/ICCES.2018.8639396
– volume: 40
  start-page: 2
  year: 2010
  ident: ref_30
  article-title: Continuous Curvature Path Generation Based on Bézier Curves for Autonomous Vehicles
  publication-title: Int. J. Appl. Math.
  contributor:
    fullname: Choi
– volume: 24
  start-page: 106
  year: 2013
  ident: ref_24
  article-title: Navigation of an autonomous car using vector fields and the dynamic window approach
  publication-title: J. Control Autom. Electr. Syst.
  doi: 10.1007/s40313-013-0006-5
  contributor:
    fullname: Pereira
– volume: 23
  start-page: 661
  year: 2006
  ident: ref_49
  article-title: Stanley: The robot that won the DARPA Grand Challenge
  publication-title: J. Field Robot.
  doi: 10.1002/rob.20147
  contributor:
    fullname: Thrun
– ident: ref_29
  doi: 10.3390/en12122342
– volume: 21
  start-page: 211
  year: 2016
  ident: ref_50
  article-title: Assessment of the impact speed and angle conditions for the EN1317 barrier tests
  publication-title: Int. J. Crashworthiness
  doi: 10.1080/13588265.2016.1164444
  contributor:
    fullname: Abraham
– ident: ref_25
  doi: 10.1109/ITSC.2019.8917427
– volume: 43
  start-page: 1
  year: 2018
  ident: ref_46
  article-title: Attractor dynamics approach to joint transportation by autonomous robots: Theory, implementation and validation on the factory floor
  publication-title: Auton. Robots
  contributor:
    fullname: Machado
– volume: 5
  start-page: 418
  year: 2018
  ident: ref_3
  article-title: Vehicle dynamic state estimation: State of the art schemes and perspectives
  publication-title: IEEE/CAA J. Autom. Sin.
  doi: 10.1109/JAS.2017.7510811
  contributor:
    fullname: Guo
– volume: 67
  start-page: 1376
  year: 2019
  ident: ref_40
  article-title: A motion planning and tracking framework for autonomous vehicles based on artificial potential field elaborated resistance network approach
  publication-title: IEEE Trans. Ind. Electron.
  doi: 10.1109/TIE.2019.2898599
  contributor:
    fullname: Huang
– ident: ref_23
  doi: 10.23919/EETA.2019.8804556
– volume: 23
  start-page: 575
  year: 1994
  ident: ref_53
  article-title: Evaluating headway control using range versus range-rate relationships
  publication-title: Veh. Syst. Dyn.
  doi: 10.1080/00423119408969076
  contributor:
    fullname: Fancher
– volume: 21
  start-page: 740
  year: 2015
  ident: ref_16
  article-title: Real-time trajectory planning for autonomous urban driving: Framework, algorithms, and verifications
  publication-title: IEEE/ASME Trans. Mechatron.
  doi: 10.1109/TMECH.2015.2493980
  contributor:
    fullname: Li
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Snippet Local path planning is a key task for the motion planners of autonomous vehicles since it commands the vehicle across its environment while avoiding any...
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SubjectTerms Acceleration
Actuators
Algorithms
Artificial intelligence
Autonomous vehicles
Behavior
Constraint modelling
Design
Elections
Fuzzy logic
Kinematics
local path planning
Localization
Mathematical functions
Motion detection
Motion planning
obstacles avoidance
Optimization techniques
Planning
Robots
Security
Trajectory planning
Vehicles
Velocity distribution
Visual perception
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Title Local Path Planning for Autonomous Vehicles Based on the Natural Behavior of the Biological Action-Perception Motion
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