Vision and navigation for the Carnegie-Mellon navlab
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special Issue on Industrial Machine Vision and Computer Vision Technology:8MPart
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In the wake of the computer and information technology revolutions, vehicles are undergoing dramatic changes in their capabilities and how they interact with drivers. Although some vehicles can decide to either generate warnings for the human driver or control the vehicle autonomously, they must usually make these decisions in real time with only incomplete information. So, human drivers must still maintain control over the vehicle. I sketch a digital driving behavior model. By simulating and analyzing driver behavior during different maneuvers such as lane changing, lane following, and traffic avoidance, researchers participating in the Beijing Institute of Technology's digital-driving project will be able to examine the possible correlations or causal relations between the smart vehicle, IVISs, the intelligent road-traffic-information network, and the driver. We aim to successfully demonstrate that a digital-driving system can provide a direction for developing human-centered smart vehicles.