34 Advances in Drowsy Driver Assistance Systems Through Data Fusion Darrell S. Bowman . William A. Schaudt . Richard J. Hanowski Center for Truck and Bus Safety, Virginia Tech Transportation Institute, Transportation Research Plaza, Blacksburg, VA, USA 1 Introduction .................................................................. 896 2 Defining the Problem: Fatigue Versus Drowsiness .......................... 897 3 Salient Measures of Driver Drowsiness ...................................... 897 3.1 Driver-Based Approaches ...................................................... 898 3.1.1 Electroencephalography (EEG) Measure ...................................... 898 3.1.2 Ocular Measures ............................................................... 898 3.2 Vehicle-Based Approaches ..................................................... 900 3.2.1 Lane Position/Line Crossing ................................................... 900 3.2.2 Steering Wheel Inputs ......................................................... 900 3.3 Measures of Driver Drowsiness Summary .................................... 901 4 Development of a Robust Drowsy Driver Assistance System ................ 901 4.1 Case Study of Prototype DDAS Utilizing a Data Fusion Approach .......... 904 4.1.1 Drowsiness Indicator Selection ................................................ 905 4.1.2 Fusion of Data from Two Drowsiness Indicators ............................. 906 4.1.3 Testing and Evaluation of Prototype DDAS ................................... 908 5 Conclusion .................................................................... 909 A. Eskandarian (ed.), Handbook of Intelligent Vehicles, DOI 10.1007/978-0-85729-085-4_34, # Springer-Verlag London Ltd. 2012