Longitudinal and Lateral Control in Automated Highway Systems: Their Past, Present and Future

  • Mohammad Alfraheed
  • Alicia Dröge
  • Max Klingender
  • Daniel Schilberg
  • Sabina Jeschke
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7102)

Abstract

Due to the increase in road transportation by 35% over the last years in Europe it is essential to find solutions to optimize highway traffic. Therefore, several projects involving automated highway systems were initiated. In these systems, the longitudinal and lateral controls enable (with the help of other components) vehicles to be coupled electronically to form a platoon. Here, just the first vehicle is driven actively and the following vehicles are controlled automatically. Several projects were initiated to develop systems for different environments (i.e. Urban, Motorway). However, the developed techniques still are limited in their application range and e.g. cannot be applied in unstructured environment (i.e. rural or dirty areas). Furthermore, they were not tested for many different heterogeneous vehicles like trucks or passenger cars. This paper presents the past and present of automated highway systems and discusses solutions for future developments, e.g. how existing technologies can be adapted for a wider application range.

Keywords

Automated Highway System Unstructured Environment Heterogeneous Platoon Longitudinal and Lateral Control 

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References

  1. 1.
    Commision of the European Communities. Europe at a crossroad - The need for sustainable transport. Manuscript of the European Commission, Brussels (2003)Google Scholar
  2. 2.
    Commission of the European Communities. Keep Europe Moving – Sustainable Mobility for our Continent, Brussels (2006)Google Scholar
  3. 3.
    Tsugawa, S., Kato, S.: Energy ITS: another application of vehicular communications. IEEE Communications Magazine 48, 120–126 (2010)CrossRefGoogle Scholar
  4. 4.
    Kunze, R., Ramakers, R., Henning, K., Jeschke, S.: Organization and Operation of Electronically Coupled Truck Platoons on German Motorways. In: Xie, M., Xiong, Y., Xiong, C., Liu, H., Hu, Z. (eds.) ICIRA 2009. LNCS, vol. 5928, pp. 135–146. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  5. 5.
    Kunze, R., Tummel, C., Henning, K.: Determination of the order of electronically coupled trucks on German motorways. In: 2009 2nd International Conference on Power Electronics and Intelligent Transportation System (PEITS), pp. S.41–S.46 (2009)Google Scholar
  6. 6.
    Shladover, S.: AHS research at the California PATH program and future AHS research needs. In: IEEE International Conference on Vehicular Electronics and Safety, ICVES 2008, pp. S.4– S.5 (2008) Google Scholar
  7. 7.
  8. 8.
    Khodayari, A., Ghaffari, A., Ameli, S., Flahatgar, J.: A historical review on lateral and longitudinal control of autonomous vehicle motions. In: 2010 2nd International Conference on Mechanical and Electrical Technology (ICMET), pp. S.421–S.429 (2010)Google Scholar
  9. 9.
    Fritz, H.: Longitudinal and lateral control of heavy duty trucks for automated vehicle following in mixed traffic: experimental results from the CHAUFFEUR project. In: Proceedings of the IEEE International Conference on Control Applications, vol. 2, pp. S.1348–S.1352 (1999)Google Scholar
  10. 10.
    Kunze, R., Haberstroh, M., Ramakers, R., Henning, K., Jeschke, S.: Automated truck platoons on motorways - a contribution to the safety on roads. In: Procceedings of 15th International Conference Road Safety on Four Continents, RS4C, Abu Dhabi, United Arab Emirates (2010)Google Scholar
  11. 11.
    Ramakers, R., Henning, K., Gies, S., Abel, D., Max, H.: Electronically coupled truck platoons on German highways. In: IEEE International Conference on Systems, Man and Cybernetics, SMC 2009, pp. S.2409–S.2414 (2009)Google Scholar
  12. 12.
    Philipp, M., Thomas, S., Klaus, H.: A Data-Mining Technique for the Planning and Organization of Truck Platoons. In: Gehalten auf der International Conference on Heavy Vehicle Transport TechnologyGoogle Scholar
  13. 13.
    Tsugawa, S.: A history of automated highway systems in Japan and future issues. In: IEEE International Conference on Vehicular Electronics and Safety, ICVES 2008, pp. S.2–S.3 (2008)Google Scholar
  14. 14.
    Kato, S., Tsugawa, S., Tokuda, K., Matsui, T., Fujii, H.: Vehicle control algorithms for cooperative driving with automated vehicles and intervehicle communications. IEEE Transactions on Intelligent Transportation Systems 3, 155–161 (2002)CrossRefGoogle Scholar
  15. 15.
    Fritz, H., Gern, A., Schiemenz, H., Bonnet, C.: CHAUFFEUR Assistant: a driver assistance system for commercial vehicles based on fusion of advanced ACC and lane keeping. In: 2004 IEEE Intelligent Vehicles Symposium, pp. S.495–S.500 (2004)Google Scholar
  16. 16.
    Happe, J., Leonie, P., Eva, P.: Drei Einsatzszenarien für elektronisch gekoppelte Lkw-Konvois auf Autobahnen. In: Einsatzszenarien für Fahrerassistenzsysteme im Güterverkehr und deren Bewertung, Fortschritt- Bereichte VDI, pp. S.146–S.185. VDI: Düsseldorf: VDI Verlag (2003)Google Scholar
  17. 17.
    Klaus, H., Eva, P., Johannes, H.: Einsatzszenarien für Fahrerassistenzsysteme im Güterverkehr. In: Fortschritt-Bericht VDI. VDI: Düsseldorf: VDI Verlag (2003)Google Scholar
  18. 18.
    Petry, L.: Einschränkungsfreie Mobilitätspraktiken? In: Möglichkeiten zur Realisierung am Beispiel der Familie. wvb Wissenschaftlicher Verlag, Berlin (2006)Google Scholar
  19. 19.
    Daviet, P., Parent, M.: Longitudinal and lateral servoing of vehicles in a platoon. In: Proceedings of the 1996 IEEE Intelligent Vehicles Symposium, pp. S.41–S.46 (1996)Google Scholar
  20. 20.
    Lapierre, E., Massot, M.: Praxitele: the missing link. World Transit Research (1999)Google Scholar
  21. 21.
    Parent, M.: Automated urban vehicles: state of the art and future directions. In: 8th Control, Automation, Robotics and Vision Conference, ICARCV 2004, vol. 1, pp. S.138–S.142 (2004)Google Scholar
  22. 22.
    Parent, M., De La Fortelle, A.: Cybercars: Past, Present and Future of the Technology. cs/0510059 (2005)Google Scholar
  23. 23.
  24. 24.
  25. 25.
    Leibe, B., Schindler, K., Cornelis, N., Van Gool, L.: Coupled Object Detection and Tracking from Static Cameras and Moving Vehicles. IEEE Transactions on Pattern Analysis and Machine Intelligence 30, 1683–1698 (2008)CrossRefGoogle Scholar
  26. 26.
    Robert, K.: Video-based traffic monitoring at day and night vehicle features detection tracking. In: 12th International IEEE Conference on Intelligent Transportation Systems, ITSC 2009, pp. S.1–S.6 (2009)Google Scholar
  27. 27.
    Lin, S., Tang, J., Zhang, X., Lv, Y.: Research on traffic moving object detection, tracking and track-generating. In: IEEE International Conference on Automation and Logistics, ICAL 2009, pp. S.783–S.788 (2009)Google Scholar
  28. 28.
    Bradski, G.R., Kaehler, A.: Learning OpenCV. O’Reilly Media (2008)Google Scholar
  29. 29.
    Grabner, H., Bischof, H.: On-line Boosting and Vision. In: 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. S.260–S.267 (2006)Google Scholar
  30. 30.
    Avidan, S.: Ensemble Tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence 29, 261–271 (2007)CrossRefGoogle Scholar
  31. 31.
    Okuma, K., Taleghani, A., de Freitas, N., Little, J.J., Lowe, D.G.: A Boosted Particle Filter: Multitarget Detection and Tracking. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004, Part I. LNCS, vol. 3021, pp. 28–39. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  32. 32.
    Han, M., Xu, W., Tao, H., Gong, Y.: An algorithm for multiple object trajectory tracking. In: Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2004, vol. 1, pp. S.I-864–S.I-871 (2004)Google Scholar
  33. 33.
    Wu, B., Nevatia, R.: Detection and Tracking of Multiple, Partially Occluded Humans by Bayesian Combination of Edgelet based Part Detectors. International Journal of Computer Vision 75, 247–266 (2007)CrossRefGoogle Scholar
  34. 34.
    Bay, H., Ess, A., Tuytelaars, T., Van Gool, L.: Speeded-Up Robust Features (SURF). Computer Vision and Image Understanding 110, 346–359 (2008)CrossRefGoogle Scholar
  35. 35.
    Seemann, E., Leibe, B., Schiele, B.: Multi-Aspect Detection of Articulated Objects. In: 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. S.1582–S.1588 (2006)Google Scholar
  36. 36.
    Leibe, B., Schindler, K., Van Gool, L.: Coupled Detection and Trajectory Estimation for Multi-Object Tracking. In: IEEE 11th International Conference on Computer Vision, ICCV 2007, pp. S.1–S.8 (2007)Google Scholar
  37. 37.
    Leibe, B., Cornelis, N., Cornelis, K., Van Gool, L.: Dynamic 3D Scene Analysis from a Moving Vehicle. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2007, pp. S.1–S.8 (2007)Google Scholar
  38. 38.
    Xianqiao, C., Qing, W., Xinping, Y., Xiuming, C.: The Enhancement for Foggy Traffic Image Based on EM Algorithm. In: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing, vol. 02, pp. 261–264. IEEE Computer Society, Washington, DC (2009)CrossRefGoogle Scholar
  39. 39.
    Shwartz, S., Namer, E., Schechner, Y.: Blind Haze Separation. In: 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. S.1984–S.1991 (2006)Google Scholar
  40. 40.
    Nayar, S., Narasimhan, S.: Vision in bad weather. In: 1999. The Proceedings of the Seventh IEEE International Conference on Computer Vision, vol. 2, pp. S.820–S.827 (1999)Google Scholar
  41. 41.
    Tan, R.: Visibility in bad weather from a single image. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2008, pp. S.1–S.8 (2008)Google Scholar
  42. 42.
    Fattal, R.: Single image dehazing. ACM Transactions on Graphics (TOG), S.72:1–S.72:9 (2008)Google Scholar
  43. 43.
    Carr, P., Hartley, R.: Improved Single Image Dehazing Using Geometry. In: Digital Image Computing: Techniques and Applications, pp. S.103–S.110. IEEE Computer Society, Los Alamitos (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Mohammad Alfraheed
    • 1
  • Alicia Dröge
    • 1
  • Max Klingender
    • 1
  • Daniel Schilberg
    • 1
  • Sabina Jeschke
    • 1
  1. 1.Institute of Information Management in Mechanical Engineering & Center of Learning and Knowledge Management.AachenGermany

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