Weitere Kapitel dieses Buchs durch Wischen aufrufen
In recent years, the idea of autonomous vehicles has taken on importance since some automobile companies have decided to develop their own autonomous cars. However, not every “autonomous car” is fully autonomous since there are different levels of autonomy. Currently, there is a variety of studies and a great deal of research about autonomous vehicles and on how to achieve full autonomy; even more, these are not limited to cars, but also include research surrounding mobile robots, drones, remotely operated vehicles (ROVs), and others. All these robots or vehicles have the same principles, in addition to having the same basics of the hardware. However, not the same can be said about the software because every solution requires unique algorithms for their data processing. In this chapter, the most important topics related to autonomous vehicles are explained as clearly as possible. This chapter covers from its main concepts to path planning, going through the basic components that an autonomous vehicle must have, all the way to the perception it has of its environment, including the identification of obstacles, signs and routes. Then, inquiry will be made into the most commonly used hardware for the development of these vehicles. In the last part of this chapter, the case study “Intelligent Transportation Scheme for Autonomous Vehicles in Smart Campus” is incorporated in order to help illustrate the goal of this chapter. Finally, an insight is included on how the innovation on business models can and will change the future of vehicles.
Bitte loggen Sie sich ein, um Zugang zu diesem Inhalt zu erhalten
Sie möchten Zugang zu diesem Inhalt erhalten? Dann informieren Sie sich jetzt über unsere Produkte:
Bauman, Z. (2000). Liquid modernity. Cambridge, UK: Polity Press.
Chesbrough, H. W. (2003). Open innovation: The new imperative for creating and profiting from technology. Boston: Harvard Business School Press.
Chesbrough, H. W. (2003). The era of open innovation. MIT Sloan Management Review, 44(3), 35–41.
Alexander, O., & Pigneur, Y. (2010). Business model generation. Hoboken, NJ: Wiley.
Taxonomy and definitions for terms related to driving automation systems for on-road motor vehicles J3016_201806. (2018). Retrieved February 5, 2019, from https://www.sae.org/standards/content/j3016_201806/
Raspberry Pi. (2019). Retrieved February 5, 2019, from https://www.raspberrypi.org/
Zini 1880. (2019). Retrieved February 5, 2019, from https://zareason.com/zini-1880.html
What Is GPS? (2019). Retrieved February 5, 2019, from https://www.gps.gov/systems/gps/
BeiDou Navigation Satellite System. (2019). Retrieved February 6, 2019, from http://en.beidou.gov.cn/
Indian Regional Navigation Satellite System (IRNSS). (2019). Retrieved February 6, 2019, from https://www.isro.gov.in/irnss-programme
European Global Satellite-Based Navigation System. (2019). Retrieved February 6, 2019, from https://www.gsa.europa.eu/european-gnss/galileo/galileo-european-global-satellite-based-navigation-system
Graham, A. (2010). Communications, radar and electronic warfare. Hoboken: Wiley. Available from: ProQuest Ebook Central. [7 February 2019].
LIDAR vs RADAR Comparison. Which System is Better for Automotive? (2018). Retrieved February 7, 2019, from https://www.archer-soft.com/en/blog/lidar-vs-radar-comparison-which-system-better-automotive
Winner, H. (2016). Automotive RADAR. In H. Winner, S. Hakuli, F. Lotz, & C. Singer (Eds.), Handbook of driver assistance systems. Cham: Springer. CrossRef
Mobile Industrial Robots. (2019). Retrieved February 11, 2019, from http://www. jacobsenconstruction.com/projects/dabc-asrs-expansion-warehouse-remodel/
Ekren, B. Y., & Heragu, S. S. (2012). A new technology for unit-load automated storage system: Autonomous vehicle storage and retrieval system. In R. Manzini (Ed.), Warehousing in the global supply chain. London: Springer. https://doi.org/10.1007/978-1-4471-2274-6_12. CrossRef
Kuo, P.-H., et al. (2007). Design models for unit load storage and retrieval systems using autonomous vehicle technology and resource conserving storage and dwell point policies. Applied Mathematical Modelling, 31(10), 2332–2346. https://doi.org/10.1016/j.apm.2006.09.011. CrossRefMATH
Waymo unveils self-driving taxi service in Arizona for paying customers. (2018). Retrieved February 11, 2019, from https://www.reuters.com/article/us-waymo-selfdriving-focus/waymo-unveils-self-driving-taxi-service-in-arizona-for-paying-customers-idUSKBN1O41M2
iRobot. (2019). Retrieved February 11, 2019, from https://store.irobot.com/default/home
Özgüner, U., Acarman, T., & Redmill, K. (2011). Autonomous ground vehicles (pp. 69–106). Boston: Artech House.
Weitkamp, C. (2005). Lidar (pp. 3–4). New York, NY: Springer. CrossRef
Caltagirone, L., Scheidegger, S., Svensson, L., & Wahde, M. (2017). Fast LIDAR-based road detection using fully convolutional neural networks. In 2017 IEEE Intelligent Vehicles Symposium (IV).
Velodyne VLP-16. (2019). Retrieved February 27, 2019, from https://velodynelidar.com/vlp-16.html/
Velodyne HDL-64E. (2019). Retrieved February 27, 2019, from https://velodynelidar.com/hdl-64e.html/
Renishaw plc. Optical Encoders and LiDAR Scanning. (2019). Retrieved February 27, 2019, from https://www.renishaw.it/it/optical-encoders-and-lidar-scanning%2D%2D39244/
YeeFen Lim, H. (2018). Autonomous vehicles and the law: Technology, algorithms and ethics (p. 28). Edward Elgar Publishing.
InnovizOne. (2019). Retrieved February 27, 2019, from https://innoviz.tech/innovizone/
Kinect Sensor. (2019). Retrieved February 27, 2019, from Amir, S., Waqar, A., Siddiqui, M. A., et al. (2017). Kinect controlled UGV. Wireless Personal Communications 95, 631. https://doi.org/10.1007/s11277-016-3915-3.
Giori, C., & Fascinari, M. (2013). Kinect in motion (pp. 9–10). Birmingham, UK: Packt Pub..
Bernini, N., Bertozzi, M., Castangia, L., Patander, M., & Sabbatelli, M. (2014). Real-time obstacle detection using stereo vision for autonomous ground vehicles: A survey. In 17th International IEEE Conference on Intelligent Transportation Systems (ITSC).
Thrun, S., Burgard, W., & Fox, D. (2006). Probabilistic robotics (p. 221). Cambridge, MA: MIT Press. MATH
Siciliano, B., & Khatib, O. (2008). Springer handbook of robotics (p. 857). Berlin: Springer. CrossRef
Li, Z., Zhu, Q., & Gold, C. (2004). Digital terrain modeling (p. 7). Boca Raton: CRC Press. CrossRef
Mach, R., & Petschek, P. (2007). Visualization of digital terrain and landscape data (p. 38). Berlin: Springer.
Hernandez-Aceituno, J., Arnay, R., Toledo, J., & Acosta, L. (2016). Using Kinect on an autonomous vehicle for outdoors obstacle detection. IEEE Sensors Journal, 16(10), 3603–3610. CrossRef
Wedel, A., & Cremers, D. (2011). Stereo scene flow for 3D motion analysis (p. 89). Springer.
Plemenos, D., & Miaoulis, G. (2013). Intelligent computer graphics 2012 (pp. 243–263). Berlin: Springer. CrossRef
Schaub, A. (2017). Robust perception from optical sensors for reactive behaviors in autonomous robotic vehicles (p. 161). Springer.
Jensen, M., Philipsen, M., Mogelmose, A., Moeslund, T., & Trivedi, M. (2016). Vision for looking at traffic lights: Issues, survey, and perspectives. IEEE Transactions on Intelligent Transportation Systems, 17(7), 1800–1815. CrossRef
Mogelmose, A., Trivedi, M., & Moeslund, T. (2012). Vision-based traffic sign detection and analysis for intelligent driver assistance systems: Perspectives and survey. IEEE Transactions on Intelligent Transportation Systems, 13(4), 1484–1497. CrossRef
Trepagnier, P., Nagel, J., & McVay Kinney, P. Navigation and control system for autonomous vehicles. US Patent 8,050,863 B2.
Cox, I., & Wilfong, G. (1990). Autonomous robot vehicles. New York, NY: Springer. CrossRef
Jiang, X., Hornegger, J., & Koch, R. (2014). Pattern recognition (p. 4). Cham: Springer.
Cadena, C., Carlone, L., Carrillo, H., Latif, Y., Scaramuzza, D., Neira, J., Reid, I., & Leonard, J. J. (2016). Past, present, and future of simultaneous localization and mapping: Toward the robust perception age. IEEE Transactions on Robotics, 32(6), 1309–1332. Retrieved from https://ieeexplore.ieee.org/document/7747236. CrossRef
Siegwart, R., & Nourbakhsh, I. R. (2004). Introduction to autonomous mobile robots. Cambridge, MA: MIT Press.
Puente, I., González-Jorge, H., Martínez-Sánchez, J., & Arias, P. (2013). Review of mobile mapping and surveying technologies. Measurement, 46(7), 2127–2145. Retrieved from https://www.sciencedirect.com/science/article/pii/S0263224113000730. CrossRef
Gonzalez-Jorge, H., Rodríguez-Gonzálvez, P., Martínez-Sánchez, J., González-Aguilera, D., Arias, P., Gesto, M., & Díaz-Vilariño, L. (2015). Metrological comparison between Kinect I and Kinect II sensors. Measurement, 70, 21–26. CrossRef
Fankhauser, P., Bloesch, M., Rodriguez, D., Kaestner, R., Hutter, M., & Siegwart, R. (2015, July). Kinect v2 for mobile robot navigation: Evaluation and modeling. In 2015 International Conference on Advanced Robotics (ICAR), Istanbul, pp. 388–394. Retrieved from https://ieeexplore.ieee.org/document/7251485
Beul, M., Krombach, N., Zhong, Y., Droeschel, D., Nieuwenhuisen, M., & Behnke, S. (2015, July). A high-performance MAV for autonomous navigation in complex 3D environments. In 2015 International Conference on Unmanned Aircraft Systems (ICUAS), Denver, CO. https://ieeexplore.ieee.org/document/7152417
Gupta, S., Davidson, J., Levine, S., Sukthankar, R., & Malik, J. (2017, November). Cognitive mapping and planning for visual navigation. In 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI. Retrieved from https://ieeexplore.ieee.org/document/8100252
Lacaze, A., Moscovitz, Y., DeClaris, N., & Murphy, K. Path planning for autonomous vehicles driving over rough terrain. In Proceedings of the 1998 IEEE International Symposium on Intelligent Control (ISIC) held jointly with IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA) Intell.
Ferguson, D., & Stentz, A. The Field D∗ algorithm for improved path planning and replanning in uniform and non-uniform cost environments. Technical Report CMU-TR-RI-05-19, Carnegie Mellon University.
Básaca-Preciado, L. C., Orozco-Garcia, N. A., & Terrazas-Gaynor, J. M., et al. (2018). Intelligent transportation scheme for autonomous vehicle in smart campus. IEEE, pp. 3193–3199.
Martinez-Austria, P. F., Bandala, E. R., & Patiño-Gómez, C. (2016). Temperature and heat wave trends in northwest Mexico. Physics and Chemistry of the Earth, Parts A/B/C, 91, 20–26. CrossRef
Åström, D. O., Bertil, F., & Joacim, R. (2011). Heat wave impact on morbidity and mortality in the elderly population: A review of recent studies. Maturitas, 69, 99–105. CrossRef
Básaca-Preciado, L. C., et al. (2014). Optical 3D laser measurement system for navigation of autonomous mobile robot. Optics and Laser in Engineering, 54, 159–169. https://doi.org/10.1016/j.optlaseng.2013.08.005. CrossRef
Lucas, H. C., Jr., et al. (2009). Disruptive technology: How Kodak missed the digital photography revolution. Journal of Strategic Information Systems, 18, 46–55. CrossRef
Resident population in the United States in 2017, Statista. (2018). The Statistics Portal. Retrieved from January 25, 2019, from https://www.statista.com/statistics/797321/us-population-by-generation/
Díaz Caravantes, R. E., Castro Luque, A. L., & Aranda Gallegos, P. (2014). Mortality by excessive natural heat in Northwest Mexico: Social conditions associated with this cause of death. Front Norte, 26, 155–177.
- Autonomous Mobile Vehicle System Overview for Wheeled Ground Applications
Luis Carlos Básaca-Preciado
Néstor Aarón Orozco-García
Oscar A. Rosete-Beas
Miguel A. Ponce-Camacho
Kevin B. Ruiz-López
Verónica A. Rojas-Mendizabal
Julio Francisco Hurtado-Campa
Juan Manuel Terrazas-Gaynor
- Chapter 15