Accurate Path Tracking by Adjusting Look-Ahead Point in Pure Pursuit Method
Path tracking is an essential aspect of the navigational process of self-driving cars. Especially, accurate path tracking is important for not only normal urban roads but also narrow and complex roads such as parking lot and alleyway. The pure pursuit method is one of the geometric path-tracking met...
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| Published in | International journal of automotive technology Vol. 22; no. 1; pp. 119 - 129 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Seoul
The Korean Society of Automotive Engineers
01.02.2021
Springer Nature B.V 한국자동차공학회 |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1229-9138 1976-3832 |
| DOI | 10.1007/s12239-021-0013-7 |
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| Abstract | Path tracking is an essential aspect of the navigational process of self-driving cars. Especially, accurate path tracking is important for not only normal urban roads but also narrow and complex roads such as parking lot and alleyway. The pure pursuit method is one of the geometric path-tracking methods. Using this method, the look-ahead point can be selected far away and the control input is computed in real-time, which is advantageous when the given path is not smooth or when the path is specified using waypoints. Moreover, this method is more robust to localization errors than the model-based path-tracking method. However, the original pure pursuit method and its variants have limited tracking performance. Therefore, this paper proposes a new method that heuristically selects a look-ahead point by considering the relationship between a vehicle and a path. Using this new look-ahead point, the vehicle can stably converge to the desired path and track the path without encountering the cutting-corner problem. The proposed method was tested using simulation and our self-driving car platform. Our results show that the vehicle tracks the desired path more accurately using our proposed algorithm than using the previous pure pursuit methods. |
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| AbstractList | Path tracking is an essential aspect of the navigational process of self-driving cars. Especially, accurate pathtracking is important for not only normal urban roads but also narrow and complex roads such as parking lot and alleyway. The pure pursuit method is one of the geometric path-tracking methods. Using this method, the look-ahead point can be selected far away and the control input is computed in real-time, which is advantageous when the given path is not smooth or when the path is specified using waypoints. Moreover, this method is more robust to localization errors than the modelbased path-tracking method. However, the original pure pursuit method and its variants have limited tracking performance. Therefore, this paper proposes a new method that heuristically selects a look-ahead point by considering the relationship between a vehicle and a path. Using this new look-ahead point, the vehicle can stably converge to the desired path and track the path without encountering the cutting-corner problem. The proposed method was tested using simulation and our selfdriving car platform. Our results show that the vehicle tracks the desired path more accurately using our proposed algorithm than using the previous pure pursuit methods. KCI Citation Count: 15 Path tracking is an essential aspect of the navigational process of self-driving cars. Especially, accurate path tracking is important for not only normal urban roads but also narrow and complex roads such as parking lot and alleyway. The pure pursuit method is one of the geometric path-tracking methods. Using this method, the look-ahead point can be selected far away and the control input is computed in real-time, which is advantageous when the given path is not smooth or when the path is specified using waypoints. Moreover, this method is more robust to localization errors than the model-based path-tracking method. However, the original pure pursuit method and its variants have limited tracking performance. Therefore, this paper proposes a new method that heuristically selects a look-ahead point by considering the relationship between a vehicle and a path. Using this new look-ahead point, the vehicle can stably converge to the desired path and track the path without encountering the cutting-corner problem. The proposed method was tested using simulation and our self-driving car platform. Our results show that the vehicle tracks the desired path more accurately using our proposed algorithm than using the previous pure pursuit methods. |
| Author | Ahn, Joonwoo Shin, Seho Park, Jaeheung Kim, Minsung |
| Author_xml | – sequence: 1 givenname: Joonwoo surname: Ahn fullname: Ahn, Joonwoo organization: Graduate School of Convergence Science and Technology, Seoul National University – sequence: 2 givenname: Seho surname: Shin fullname: Shin, Seho organization: System LSI, Samsung Electronics Co., Ltd – sequence: 3 givenname: Minsung surname: Kim fullname: Kim, Minsung organization: Graduate School of Convergence Science and Technology, Seoul National University – sequence: 4 givenname: Jaeheung surname: Park fullname: Park, Jaeheung email: park73@snu.ac.kr organization: Graduate School of Convergence Science and Technology, Seoul National University, Advanced Institute of Convergence Technology |
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| Cites_doi | 10.2307/2372560 10.1177/027836499501400602 10.1109/CAC48633.2019.8997258 10.1002/rob.20255 10.1007/s12239-014-0120-9 10.1109/TVT.2020.2981619 10.1109/TIV.2016.2578706 10.1109/ACC.1998.694619 10.1109/ROBOT.1990.126006 10.3182/20130902-3-CN-3020.00045 10.1109/TITS.2019.2892926 10.1109/AIM.2016.7577010 10.1002/rob.20147 10.2514/6.2008-7166 10.1109/ICICAS48597.2019.00197 |
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| Keywords | Geometric path-tracking method Accurate path tracking Path tracking Look-ahead point selection Pure pursuit method |
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| References | DubinsL EOn curves of minimal length with a constraint on average curvature, and with prescribed initial and terminal positions and tangentsAmerican J. Mathematics19577934975168945710.2307/2372560 BuXHouZChiRModel free adaptive iterative learning control for farm vehicle path trackingIFAC Proc. Volumes2013462015315810.3182/20130902-3-CN-3020.00045 Kuwata, Y., Teo, J., Karaman, S., Fiore, G., Frazzoli, E. and How, J. (2008). Motion planning in complex environments using closed-loop prediction. AIAA Guidance, Navigation and Control Conf. Exhibit. Honolulu, Hawaii. Peng, H., Wang, W., An, Q., Xiang, C. and Li, L. (2020). Path tracking and direct yaw moment coordinated control based on robust MPC with the finite time horizon for autonomous independent-drive vehicles. IEEE Trans. Vehicular Technology. RajamaniRVehicle dynamics and control2011Berlin, GermanySpringer Science & Business Media1097.70001 Coulter, R. C. (1992). Implementation of the pure pursuit path tracking algorithm. Carnegie-Mellon UNIV Pittsburgh PA Robotics INST. Wit, J. S. (2000). Vector pursuit path tracking for autonomous ground vehicles. Ph.D. Doctoral dissertation. University of Florida. Gainesville, FL, USA. XuSPengHDesign, analysis, and experiments of preview path tracking control for autonomous vehiclesIEEE Trans. Intelligent Transportation Systems2019211485810.1109/TITS.2019.2892926 Qinpeng, S., Zhonghua, W., Meng, L., Bin, L., Jin, C. and Jiaxiang, T. (2019). Path tracking control of wheeled mobile robot based on improved pure pursuit algorithm. 2019 Chinese Automation Congress (CAC). Hangzhou, China. Hingwe, P. and Tomizuka, M. (1998). A variable look-ahead controller for lateral guidance of four wheeled vehicles. Proc. 1998 American Control Conf. Philadelphia, PA, USA. PadenBČápMYongS ZYershovDFrazzoliEA survey of motion planning and control techniques for self-driving urban vehiclesIEEE Trans. Intelligent Vehicles201611335510.1109/TIV.2016.2578706 Campbell, S. (2007). Steering control of an autonomous ground vehicle with application to the DARPA urban challenge. Ph.D. Doctoral dissertation. Massachusetts Institute of Technology, Cambridge, MA, USA. Piao, C., Liu, X. and Lu, C. (2019). Lateral control using parameter self-tuning LQR on autonomous vehicle. 2019 Int. Conf. Intelligent Computing, Automation and Systems (ICICAS). Chongqing, China. d’Andréa-NovelBCampionGBastinGControl of nonholonomic wheeled mobile robots by state feedback linearizationInt. J. Robotics Research199514654355910.1177/027836499501400602 Kilinç, A. S. and Baybura, T. (2012). Determination of minimum horizontal curve radius used in the design of transportation structures, depending on the limit value of comfort criterion lateral jerk. TS06G-Engineering Surveying, Machine Control and Guidance, Rome, Italy. Chen, C. and Tan, H. S. (1999). Experimental study of dynamic look-ahead scheme for vehicle steering control. Proc. 1999 American Control Conf. San Diego, CA, USA. Andersen, H., Chong, Z. J., Eng, Y. H., Pendleton, S. and Ang, M. H. (2016). Geometric path tracking algorithm for autonomous driving in pedestrian environment. 2016 IEEE Int. Conf. Advanced Intelligent Mechatronics (AIM). Banff, Alberta, Canada. Kanayama, Y., Kimura, Y., Miyazaki, F. and Noguchi, T. (1990). A stable tracking control method for an autonomous mobile robot. Proc., IEEE Int. Conf. Robotics and Automation. Cincinnati, OH, USA. ThrunSMontemerloMDahlkampHStavensDAronADiebelJFongPGaleJHalpennyMHoffmannGLauKOakleyCPalatucciMPrattVStangPStrohbandSDupontCJendrossekL-EKoelenCMarkeyCRummelCvan NiekerkJJensenEAlessandriniPBradskiGDaviesBEttingerSKaehlerANefianAMahoneyPStanley: The robot that won the DARPA Grand ChallengeJ. Field Robotics200623966169210.1002/rob.20147 UrmsonCAnhaltJBagnellDBakerCBittnerRClarkM NDolanJDugginsDGalataliTGeyerCGittlemanMHarbaughSHebertMHowardT MKolskiSKellyALikhachevMMcNaughtonMMillerNPetersonKPilnickBRajkumarRRybskiPSaleskyBSeoY-WSinghSSniderJStentzAWhittakerWWolkowickiZZiglarJBaeHBrownTDemitrishDLitkouhiBNickolaouJSadekarVZhangWStrubleJTaylorMDarmsMFergusonDAutonomous driving in urban environments: Boss and the urban challengeJ. Field Robotics200825842546610.1002/rob.20255 Zhang, J. and Singh, S. (2014). LOAM: Lidar Odometry and Mapping in Real-time. 2014 Robotics: Science and Systems Conf. Berkeley, CA, USA. KimEKimJSunwooMModel predictive control strategy for smooth path tracking of autonomous vehicles with steering actuator dynamicsInt. J. Automotive Technology20141571155116410.1007/s12239-014-0120-9 Challenge, D. U. (2007). Route network definition file (RNDF) and mission data file (MDF) formats. Tech. Rep., Defense Advanced Research Projects Agency, Tech. Rep. 13_CR17 C Urmson (13_CR20) 2008; 25 R Rajamani (13_CR18) 2011 S Thrun (13_CR19) 2006; 23 13_CR15 B d’Andréa-Novel (13_CR7) 1995; 14 13_CR16 X Bu (13_CR2) 2013; 46 B Paden (13_CR14) 2016; 1 13_CR4 13_CR5 E Kim (13_CR12) 2014; 15 13_CR6 13_CR9 13_CR10 13_CR21 S Xu (13_CR22) 2019; 21 L E Dubins (13_CR8) 1957; 79 13_CR13 13_CR1 13_CR11 13_CR3 13_CR23 |
| References_xml | – reference: Campbell, S. (2007). Steering control of an autonomous ground vehicle with application to the DARPA urban challenge. Ph.D. Doctoral dissertation. Massachusetts Institute of Technology, Cambridge, MA, USA. – reference: KimEKimJSunwooMModel predictive control strategy for smooth path tracking of autonomous vehicles with steering actuator dynamicsInt. J. Automotive Technology20141571155116410.1007/s12239-014-0120-9 – reference: XuSPengHDesign, analysis, and experiments of preview path tracking control for autonomous vehiclesIEEE Trans. Intelligent Transportation Systems2019211485810.1109/TITS.2019.2892926 – reference: UrmsonCAnhaltJBagnellDBakerCBittnerRClarkM NDolanJDugginsDGalataliTGeyerCGittlemanMHarbaughSHebertMHowardT MKolskiSKellyALikhachevMMcNaughtonMMillerNPetersonKPilnickBRajkumarRRybskiPSaleskyBSeoY-WSinghSSniderJStentzAWhittakerWWolkowickiZZiglarJBaeHBrownTDemitrishDLitkouhiBNickolaouJSadekarVZhangWStrubleJTaylorMDarmsMFergusonDAutonomous driving in urban environments: Boss and the urban challengeJ. Field Robotics200825842546610.1002/rob.20255 – reference: Andersen, H., Chong, Z. J., Eng, Y. H., Pendleton, S. and Ang, M. H. (2016). Geometric path tracking algorithm for autonomous driving in pedestrian environment. 2016 IEEE Int. Conf. Advanced Intelligent Mechatronics (AIM). Banff, Alberta, Canada. – reference: Kanayama, Y., Kimura, Y., Miyazaki, F. and Noguchi, T. (1990). A stable tracking control method for an autonomous mobile robot. Proc., IEEE Int. Conf. Robotics and Automation. Cincinnati, OH, USA. – reference: Hingwe, P. and Tomizuka, M. (1998). A variable look-ahead controller for lateral guidance of four wheeled vehicles. Proc. 1998 American Control Conf. Philadelphia, PA, USA. – reference: d’Andréa-NovelBCampionGBastinGControl of nonholonomic wheeled mobile robots by state feedback linearizationInt. J. Robotics Research199514654355910.1177/027836499501400602 – reference: RajamaniRVehicle dynamics and control2011Berlin, GermanySpringer Science & Business Media1097.70001 – reference: PadenBČápMYongS ZYershovDFrazzoliEA survey of motion planning and control techniques for self-driving urban vehiclesIEEE Trans. Intelligent Vehicles201611335510.1109/TIV.2016.2578706 – reference: Qinpeng, S., Zhonghua, W., Meng, L., Bin, L., Jin, C. and Jiaxiang, T. (2019). Path tracking control of wheeled mobile robot based on improved pure pursuit algorithm. 2019 Chinese Automation Congress (CAC). Hangzhou, China. – reference: ThrunSMontemerloMDahlkampHStavensDAronADiebelJFongPGaleJHalpennyMHoffmannGLauKOakleyCPalatucciMPrattVStangPStrohbandSDupontCJendrossekL-EKoelenCMarkeyCRummelCvan NiekerkJJensenEAlessandriniPBradskiGDaviesBEttingerSKaehlerANefianAMahoneyPStanley: The robot that won the DARPA Grand ChallengeJ. Field Robotics200623966169210.1002/rob.20147 – reference: Wit, J. S. (2000). Vector pursuit path tracking for autonomous ground vehicles. Ph.D. Doctoral dissertation. University of Florida. Gainesville, FL, USA. – reference: BuXHouZChiRModel free adaptive iterative learning control for farm vehicle path trackingIFAC Proc. Volumes2013462015315810.3182/20130902-3-CN-3020.00045 – reference: Zhang, J. and Singh, S. (2014). LOAM: Lidar Odometry and Mapping in Real-time. 2014 Robotics: Science and Systems Conf. Berkeley, CA, USA. – reference: Kuwata, Y., Teo, J., Karaman, S., Fiore, G., Frazzoli, E. and How, J. (2008). Motion planning in complex environments using closed-loop prediction. AIAA Guidance, Navigation and Control Conf. Exhibit. Honolulu, Hawaii. – reference: DubinsL EOn curves of minimal length with a constraint on average curvature, and with prescribed initial and terminal positions and tangentsAmerican J. Mathematics19577934975168945710.2307/2372560 – reference: Chen, C. and Tan, H. S. (1999). Experimental study of dynamic look-ahead scheme for vehicle steering control. Proc. 1999 American Control Conf. San Diego, CA, USA. – reference: Peng, H., Wang, W., An, Q., Xiang, C. and Li, L. (2020). Path tracking and direct yaw moment coordinated control based on robust MPC with the finite time horizon for autonomous independent-drive vehicles. IEEE Trans. Vehicular Technology. – reference: Piao, C., Liu, X. and Lu, C. (2019). Lateral control using parameter self-tuning LQR on autonomous vehicle. 2019 Int. Conf. Intelligent Computing, Automation and Systems (ICICAS). Chongqing, China. – reference: Kilinç, A. S. and Baybura, T. (2012). Determination of minimum horizontal curve radius used in the design of transportation structures, depending on the limit value of comfort criterion lateral jerk. TS06G-Engineering Surveying, Machine Control and Guidance, Rome, Italy. – reference: Coulter, R. C. (1992). Implementation of the pure pursuit path tracking algorithm. Carnegie-Mellon UNIV Pittsburgh PA Robotics INST. – reference: Challenge, D. U. (2007). Route network definition file (RNDF) and mission data file (MDF) formats. Tech. Rep., Defense Advanced Research Projects Agency, Tech. Rep. – volume: 79 start-page: 497 issue: 3 year: 1957 ident: 13_CR8 publication-title: American J. Mathematics doi: 10.2307/2372560 – volume: 14 start-page: 543 issue: 6 year: 1995 ident: 13_CR7 publication-title: Int. J. Robotics Research doi: 10.1177/027836499501400602 – ident: 13_CR23 – ident: 13_CR17 doi: 10.1109/CAC48633.2019.8997258 – volume: 25 start-page: 425 issue: 8 year: 2008 ident: 13_CR20 publication-title: J. Field Robotics doi: 10.1002/rob.20255 – ident: 13_CR21 – ident: 13_CR3 – volume: 15 start-page: 1155 issue: 7 year: 2014 ident: 13_CR12 publication-title: Int. J. Automotive Technology doi: 10.1007/s12239-014-0120-9 – ident: 13_CR5 – ident: 13_CR4 – ident: 13_CR6 – ident: 13_CR15 doi: 10.1109/TVT.2020.2981619 – volume: 1 start-page: 33 issue: 1 year: 2016 ident: 13_CR14 publication-title: IEEE Trans. Intelligent Vehicles doi: 10.1109/TIV.2016.2578706 – ident: 13_CR9 doi: 10.1109/ACC.1998.694619 – ident: 13_CR10 doi: 10.1109/ROBOT.1990.126006 – volume: 46 start-page: 153 issue: 20 year: 2013 ident: 13_CR2 publication-title: IFAC Proc. Volumes doi: 10.3182/20130902-3-CN-3020.00045 – ident: 13_CR11 – volume: 21 start-page: 48 issue: 1 year: 2019 ident: 13_CR22 publication-title: IEEE Trans. Intelligent Transportation Systems doi: 10.1109/TITS.2019.2892926 – volume-title: Vehicle dynamics and control year: 2011 ident: 13_CR18 – ident: 13_CR1 doi: 10.1109/AIM.2016.7577010 – volume: 23 start-page: 661 issue: 9 year: 2006 ident: 13_CR19 publication-title: J. Field Robotics doi: 10.1002/rob.20147 – ident: 13_CR13 doi: 10.2514/6.2008-7166 – ident: 13_CR16 doi: 10.1109/ICICAS48597.2019.00197 |
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| SubjectTerms | Algorithms Automotive Engineering Autonomous cars Engineering Path tracking Roads & highways Tracks (paths) Waypoints 자동차공학 |
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| Title | Accurate Path Tracking by Adjusting Look-Ahead Point in Pure Pursuit Method |
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