Publisher
Springer International Publishing
Reference14 articles.
1. Lu, M., Wevers, K., Van Der Heijden, R.: Technical feasibility of advanced driver assistance systems (ADAS) for road traffic safety. Transportation Planning and Technology 28(3), 167–187 (2005)
2. Hojjati-Emami, K., Dhillon, B., Jenab, K.: Reliability prediction for the vehicles equipped with advanced driver assistance systems (ADAS) and passive safety systems (PSS). International Journal of Industrial Engineering Computations 3(5), 731–742 (2012)
3. Maag, C., Muhlbacher, D., Mark, C., Kruger, H.-P.: Studying effects of advanced driver assistance systems (ADAS) on individual and group level using multi-driver simulation. IEEE Intelligent Transportation Systems Magazine 4(3), 45–54 (2012)
4. Borkar, A., Hayes, M., Smith, M.T.: A non overlapping camera network: Calibration and application towards lane departure warning. In: International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011 (2011)
5. Tapia-Espinoza, R., Torres-Torriti, M.: Robust lane sensing and departure warning under shadows and occlusions. Sensors 13(3), 3270–3298 (2013)
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