Abstract
Different algorithms for path tracking have been described and implemented for autonomous vehicles. Traditional geometric algorithms like Pure Pursuit use position information to compute vehicle’s steering angle to follow a predefined path. The main issue of these algorithms resides in cutting corners since no curvature information is taken into account. In order to overcome this problem, we present a sub-system for path tracking where an algorithm that analyzes GPS information off-line classifies high curvature segments and estimates the ideal speed for each one. Additionally since the evaluation of our sub-system is performed through a simulation of an adaptive Pure Pursuit algorithm, we propose a method to estimate dynamically its look-ahead distance based on the vehicle speed and lateral error. As it will be shown through experimental results, our sub-system introduces improvements in comfort and safety due to the extracted geometry information and speed control, stabilizing the vehicle and minimizing the lateral error.
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References
Green Book: A policy on Geometric Design of Highways and Streets. AASHTO, 5th edn., vol. 49 (2004). ISBN 1–56051
Coulter, R.C.: Implementation of the pure pursuit path tracking algorithm. Technical report, DTIC Document (1992)
Douglas, D.H., Peucker, T.K.: Algorithms for the reduction of the number of points required to represent a digitized line or its caricature. Cartogr. Int. J. Geogr. Inf. Geovis. 10(2), 112–122 (1973)
Eidehall, A., Pohl, J., Gustafsson, F.: Joint road geometry estimation and vehicle tracking. Control Eng. Pract. 15(12), 1484–1494 (2007)
Fitzsimmons, E.J., Lindheimer, T.E., Schrock, S.D., Gonterwitz, K.: Evaluation of large truck crashes at horizontal curves on two-lane rural highways in kansas. In: Transportation Research Board 92nd Annual Meeting, No. 13–2340 (2013)
Giesbrecht, J., Mackay, D., Collier, J., Verret, S.: Path tracking for unmanned ground vehicle navigation. DRDC Suffield TM 224 (2005)
Girbés, V., Armesto, L., Tornero, J., Solanes, J.E.: Continuous-curvature kinematic control for path following problems. In: 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 4335–4340. IEEE (2011)
Hans, Z., Souleyrette, R., Bogenreif, C.: Horizontal curve identification and evaluation. Technical report (2012)
Ivanov, R.: Real-time GPS track simplification algorithm for outdoor navigation of visually impaired. J. Netw. Comput. Appl. 35(5), 1559–1567 (2012)
Kannan, S., Thangavelu, A., Kalivaradhan, R.: An intelligent driver assistance system (I-DAS) for vehicle safety modelling using ontology approach. Int. J. Ubicomp 1(3), 15–29 (2010)
Kelly, A.: A feedforward control approach to the local navigation problem for autonomous vehicles. Carnegie Mellon University, The Robotics Institute (1994)
Lehtonen, E., Lappi, O., Koirikivi, I., Summala, H.: Effect of driving experience on anticipatory look-ahead fixations in real curve driving. Accid. Anal. Prev. 70, 195–208 (2014)
Lehtonen, E., Lappi, O., Kotkanen, H., Summala, H.: Look-ahead fixations in curve driving. Ergonomics 56(1), 34–44 (2013)
Li, Z., Chitturi, M., Bill, A., Noyce, D.: Automated identification and extraction of horizontal curve information from geographic information system roadway maps. Transp. Res. Rec. J. Transp. Res. Board 2291, 80–92 (2012)
Liu, R., Duan, J.: A path tracking algorithm of intelligent vehicle by preview strategy. In: 2013 32nd Chinese Control Conference (CCC), pp. 5630–5635. IEEE (2013)
Low, C.B., Wang, D.: GPS-based path following control for a car-like wheeled mobile robot with skidding and slipping. IEEE Trans. Control Syst. Technol. 16(2), 340–347 (2008)
Lundquist, C., Schon, T.B.: Road geometry estimation and vehicle tracking using a single track model. In: 2008 IEEE Intelligent Vehicles Symposium, pp. 144–149. IEEE (2008)
Lundquist, C., Schön, T.B.: Joint ego-motion and road geometry estimation. Inf. Fusion 12(4), 253–263 (2011)
Park, B., Han, W.Y.: Reference velocity estimation method for on-road unmanned ground vehicle. In: 2013 10th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), pp. 230–231. IEEE (2013)
Park, M.W., Lee, S.W., Han, W.Y.: Development of lateral control system for autonomous vehicle based on adaptive pure pursuit algorithm. In: 2014 14th International Conference on Control, Automation and Systems (ICCAS), pp. 1443–1447. IEEE (2014)
Park, M., Lee, S., Han, W.: Development of steering control system for autonomous vehicle using geometry-based path tracking algorithm. ETRI J. 37(3), 617–625 (2015)
Snider, J.M.: Automatic steering methods for autonomous automobile path tracking. Robotics Institute, Pittsburgh, PA, Technical report, CMU-RITR-09-08 (2009)
Wang, C., Hu, Z., Uchimura, K.: Precise curvature estimation by cooperating with digital road map. In: 2008 IEEE Intelligent Vehicles Symposium, pp. 859–864. IEEE (2008)
Wit, J.S.: Vector pursuit path tracking for autonomous ground vehicles. Technical report, DTIC Document (2000)
Acknowledgments
Special thanks to National Council of Science and Technology (CONACYT) for the financial support. CONACYT is Mexico’s entity in charge of the promotion of scientific and technological activities, granting scholarships for graduate studies (masters and doctoral) in Mexico and foreign countries.
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Gámez Serna, C., Lombard, A., Ruichek, Y., Abbas-Turki, A. (2017). GPS-Based Curve Estimation for an Adaptive Pure Pursuit Algorithm. In: Sidorov, G., Herrera-Alcántara, O. (eds) Advances in Computational Intelligence. MICAI 2016. Lecture Notes in Computer Science(), vol 10061. Springer, Cham. https://doi.org/10.1007/978-3-319-62434-1_40
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DOI: https://doi.org/10.1007/978-3-319-62434-1_40
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