Abstract
This paper concerns the problem of driving assistance and, in particular, how to improve the perception of the surrounding environment to make this assistance really helpful. The main aims of a Driving Assistance System are to improve the security of the driver, passengers, and other road users. Driving is a complex activity, where the interactions between the driver, the vehicle, and the environment are continuous and numerous. The vehicle moves in a dynamic environment, so the Driving Assistance System, for its diagnosis, needs a map that represents as well as possible the actual situation of this environment. This paper presents a multi-sensor fusion module embedded in a real vehicle. The problem considered here is the dynamic reconstruction of the environment of the vehicle, based on measurements of a set of sensors.
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Abou Khaled, O., Hadi, R., and Le Fort, N.: A real-time supervision of a vehicle in adynamic environment, in Proceedings of the IFAC Intelligent Autonomous Vehicles, Espoo, Finland, June 1995.
Rombaut, M.: Prolab2: A driving assitance system, Special Issue of Computer andMathematics with Applications, Computing Technologies for Intelligent Vehicle Highway Systems 22 (1995) 103–118.
Baghdassarian, C., Lange, H., Sahli, H., and Laurgeau, C.: Fast recognition of roadmarkings with use of the model of the scene in each level of processing, in 16th DAGM Symposium and 18th Workshop of VAGM, September 1994, pp. 685–695.
Trassoudaine, L., Hutber, D., Checchin, P., Alizona, J., Gallice, J., and Thonnat, M.: Building an environment map around the prolab2 vehicle using a controllable range sensor, in Proc. of Intelligent Vehicles'94, Paris, October 1994, pp. 562–567.
Burie, J. C. and Postaire, J. G.: A coarse to fine matching procedure for linear stereo vision, inInternational Federation of Automatic Control, 7th Symposium on Transportation Systems: Theory and Application of Advanced Technology, Vol. 1, Tianjin, China, 24–26 August 1994, pp. 164–169.
Bellon, A., Derutin, J. P., Heitz, F., and Ricquebourg, Y.: Real time collision avoidance at road crossingson board the prometheus prolab2 vehicule, in Proc. of Intelligent Vehicles'94, Paris, October 1994, pp. 56–61.
Beucher, S. and Bilodeau, M.: Road segmentation and obstacle detection using a fast watershedtransformation, in Intelligent Vehicles 94, IEEE Industrial Electronic Society, Paris, October 1994, pp. 296–297.
Bar-Shalom, Y. and Fortmann, T. E.: Tracking and data association, in Mathematics inSciences and Engineering, Vol. 179, Academic Press, 1988.
Rombaut, M. and Meizel D.:Dynamic data temporal multisensor fusion in the prometheus prolab2 demonstrator, in 1994 IEEE International Conference on Robotics and Automation, San Diego, CA, May 8–13 1994, p. 3676.
Eleter, B.and Rombaut, M.: Intelligent mapping of the prolab2 vehicle dynamic environment, in IMACS Int'l Symposium on Signal Processing, Robotics and Neural Networks, Lille, France, 1994.
Leonard, J. J. and Durrant-Whyte, H.: Application of multi-target tracking to sonar-based mobile robot navigation, in Proc. of the 29th Conf. on Decision and Control, pp. 3118–3123.
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Rombaut, M., Le Fort-Piat, N. Driving Activity: How to Improve Knowledge of the Environment. Journal of Intelligent and Robotic Systems 18, 399–408 (1997). https://doi.org/10.1023/A:1007981207108
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DOI: https://doi.org/10.1023/A:1007981207108