Abstract
Traffic has become more complex in recent years and therefore the expectations that are placed on automobiles have also risen sharply. Support for drivers and the protection of the occupants of vehicles and other persons involved in road traffic have become essential. Rapid technical developments and innovative advances in recent years have enabled the development of plenty of Advanced Driver Assistance Systems that are based on different working principles such as radar, lidar or camera techniques. Some systems only warn the drivers via a visual, audible or haptical signal of a danger. Other systems are used to actively engage in the control of a vehicle in emergency situations. Although technical development is already quite mature, there are still many development opportunities for improving road safety. The further development of current applications and the creation of new applications that are based on sensor fusion are essential for the future. A short summary of capabilities of ADAS systems and selected ADAS modules was presented in this paper. The review was selected toward the future perspective of sensors fusion applied on the autonomous mobile platform.
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References
Winner, H., Hakuli, S., Wolf, G.: Handbuch Fahrerassistenzsysteme. Spriger Vieweg, Wiesbaden (2012)
Brookhuis, K.A., de Waard, D., Janssen, W.H.: Behavioural impacts of Advanced Driver Assistance Systems–an overview. TNO Human Factors Soesterberg; The Netherlands
Piao, J., McDonald, M.: Advanced driver assistance systems from autonomous to cooperative approach. Trans. Rev. 28, 659–684 (2008)
Schneider, J.H.: Modellierung und Erkennung von Fahrsituationen und Fahrmanövern für sicherheitsrelevante Fahrerassistenzsysteme. Fakultät für Elektrotechnik und Informationstechnik, TU Chemnitz (2009)
Bertozzi, M., Broggi, A., Carletti, M., Fascioli, A., Graf, T., Grisleri, P., Meinecke, M.: IR pedestrian detection for advanced driver assistance systems. In: Michaelis, B., Krell, G. (eds.) DAGM 2003. LNCS, vol. 2781, pp. 582–590. Springer, Heidelberg (2003)
Continental Automotive, ‘Advanced Driver Assistance Systems’. http://www.continental-automotive.com/www/automotive_de_en/themes/passenger_cars/chassis_safety/adas/
Boodlal, L., Chiang, K.-H.: Study of the Impact of a Telematics System on Safe and Fuel-efficient Driving in Trucks. U.S. Department of Transportation Federal Motor Carrier Safety Administration Office of Analysis, Research and Technology (2014)
Keller, C.G., Dang, T., Fritz, H., Joos, A., Rabe, C., Gavrila, D.M.: IEEE Xplore abstract - active pedestrian safety by automatic braking and evasive steering. IEEE Trans. Intell. Transp. Syst. 12, 1292–1304 (2011)
Tewolde, G.S.: Sensor and network technology for intelligent transportation systems. Presented at the May (2012)
Bengler, K., Dietmayer, K., Farber, B., Maurer, M., Stiller, C., Winner, H.: Three decades of driver assistance systems: review and future perspectives. IEEE Intell. Trans. Syst. Mag. 6, 6–22 (2014)
Vollrath, M., Briest, S., Schiessl, C., Drewes, K., Becker, U.: Ableitung von Anforderungen an Fahrerassistenzsysteme aus Sicht der Verkehrssicherheit. Berichte der Bundesanstalt für Straßenwesen. Bergisch Gladbach: Wirtschaftsverlag NW (2006)
Fildes, B., Keall, M., Thomas, P., Parkkari, K., Pennisi, L., Tingvall, C.: Evaluation of the benefits of vehicle safety technology: The MUNDS study. Accid. Anal. Prev. 55, 274–281 (2013)
David, K., Flach, A.: CAR-2-X and pedestrian safety. IEEE Veh. Technol. Mag. 5, 70–76 (2010)
Horter, M.H., Stiller, C., Koelen, C.: A hardware and software framework for automotive intelligent lighting. Presented at the June (2009)
Hegeman, G., Brookhuis, K., Hoogendoorn, S.: Opportunities of advanced driver assistance systems towards overtaking. Eur. J. Trans. Infrastruct. Res. EJTIR 5(4), 281 (2005)
Lu, M., Wevers, K., Heijden, R.V.D.: Technical feasibility of advanced driver assistance systems (ADAS) for road traffic safety. Trans. Planning Technol. 28, 167–187 (2005)
NXP - Automotive Radar Millimeter-Wave Technology. http://www.nxp.com/pages/automotive-radar-millimeter-wave-technology:AUTRMWT
TDA2x - Texas Instruments Wiki. http://processors.wiki.ti.com/index.php/TDA2x
Bosch Mobility Solutions. http://www.bosch-mobility-solutions.com/en/
AutoUniMo: FP7-PEOPLE-2013-IAPP AutoUniMo project “Automotive Production Engineering Unified Perspective based on Data Mining Methods and Virtual Factory Model” (grant agreement no: 612207). http://autounimo.aei.polsl.pl/
Continental Industrial Sensors-Willkommen bei Industrial Sensors. http://www.conti-online.com/www/industrial_sensors_de_de/
Kaempchen, N., Dietmayer, K.C.J.: Fusion of laserscanner and video for ADAS. IEEE Trans. Intell. Transp. Syst. TITS 16(5), 1–12 (2015)
Błachuta, M., Czyba, R., Janusz, W., Szafrański, G.: Data fusion algorithm for the altitude and vertical speed estimation of the VTOL platform. J. Intell. Rob. Syst. 74, 413–420 (2014)
Budzan, S., Kasprzyk, J.: Fusion of 3D laser scanner and depth images for obstacle recognition in mobile applications. Opt. Lasers Eng. 77, 230–240 (2016)
Sandblom, F., Sorstedt, J.: Sensor data fusion for multiple configurations. In: Presented at the June (2014)
Grzechca, D., Wrobel, T., Bielecki, P.: Indoor location and idetification of objects with video survillance system and WiFi module. In: Presented at the September (2014)
Tokarz, K., Czekalski, P., Sieczkowski, W.: Integration of ultrasonic and inertial methods in indoor navigation system. Theor. Appl. Inform. 26, 107–117 (2015)
Pamuła, D., Ziębiński, A.: Securing video stream captured in real time. Przegląd Elektrotechniczny. R. 86(9), 167–169 (2010)
Ziebinski, A., Swierc, S.: Soft core processor generated based on the machine code of the application. J. Circ. Syst. Comput. 25, 1650029 (2016)
Behere, S., Törngren, M.: A functional architecture for autonomous driving. In: Presented at the Proceedings of the First International Workshop on Automotive Software Architecture (2015)
Cupek, R., Ziebinski, A., Franek, M.: FPGA based OPC UA embedded industrial data server implementation. J. Circ. Syst. Comp. 22, 18 (2013)
Acknowledgements
This work was supported by the European Union through the FP7-PEOPLE-2013-IAPP AutoUniMo project “Automotive Production Engineering Unified Perspective based on Data Mining Methods and Virtual Factory Model” (grant agreement no: 612207) and research work financed from funds for science for years: 2016-2017 allocated to an international co-financed project.
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Ziebinski, A., Cupek, R., Erdogan, H., Waechter, S. (2016). A Survey of ADAS Technologies for the Future Perspective of Sensor Fusion. In: Nguyen, N., Iliadis, L., Manolopoulos, Y., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2016. Lecture Notes in Computer Science(), vol 9876. Springer, Cham. https://doi.org/10.1007/978-3-319-45246-3_13
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