Abstract: Example non-limiting technology herein provides several specific approaches for making CWTOF lidar more flexible and amendable to waveform controls. A first method examines how different mathematical wave models can be applied to the continuous wave approach to increase accuracy and reduce calibration burden. Second, an example is described of how carrier waveforms can be modulated with the continuous waveform and then demodulated prior to summation in order to improve noise rejection from both environmental and electronic sources. Third, an example is presented of how DCS frames can be updated with every sample rather than every 5th sample as commonly done (4 DCS frames and 1 ambient frame), which is especially advantageous for tracking faster objects. Fourth, an example of post-collection DCS frame signal processing is given that significantly reduces temporal noise. Fifth, a method is shown for using alternate frames at different integration times to significantly increase the dynamic range of the system.

Abstract: A vehicle safety system performs close-in incipient collision detection that combines high sample rate near-field sensors with advanced real-time processing to accurately determine imminent threats and the likelihood of a collision before a collision occurs. This allows applicable countermeasures to be deployed based upon the probability of a collision, while also taking into account the type of threat and the impending impact's location on the vehicle. This radically new approach will soon transform the passive safety market to greatly reduce injuries from automotive crashes and save lives.

Abstract: A vehicle safety system performs close-in incipient collision detection that combines high sample rate near-field sensors with advanced real-time processing to accurately determine and report risky driver behavior.

Abstract: A vehicle safety system performs close-in incipient collision detection that combines high sample rate near-field sensors with advanced real-time processing to accurately determine imminent threats and the likelihood of a collision before a collision occurs. This allows applicable countermeasures to be deployed based upon the probability of a collision, while also taking into account the type of threat and the impending impact's location on the vehicle. This radically new approach will soon transform the passive safety market to greatly reduce injuries from automotive crashes and save lives.

Abstract: A vehicle safety system performs close-in incipient collision detection that combines high sample rate near-field sensors with advanced real-time processing to accurately determine imminent threats and the likelihood of a collision before a collision occurs. This allows applicable countermeasures to be deployed based upon the probability of a collision, while also taking into account the type of threat and the impending impact's location on the vehicle. This radically new approach will soon transform the passive safety market to greatly reduce injuries from automotive crashes and save lives.

Abstract: A vehicle safety system performs close-in incipient collision detection that combines high sample rate near-field sensors with advanced real-time processing to accurately determine imminent threats and the likelihood of a collision before a collision occurs. This allows applicable countermeasures to be deployed based upon the probability of a collision, while also taking into account the type of threat and the impending impact's location on the vehicle. This radically new approach will soon transform the passive safety market to greatly reduce injuries from automotive crashes and save lives.

Abstract: A vehicle safety system performs close-in incipient collision detection that combines high sample rate near-field sensors with advanced real-time processing to accurately determine and report risky driver behavior.

Abstract: A method for capturing a scene image of signage from a vehicle moving on a road or from a person's perspective not in a vehicle, the method includes the steps of capturing scene images of signage, recording video data of the scene image of signage into a memory, the video data being formed by image frames, tagging each image frame of the image frames or a group of the image frames with time data and location data, identifying a specific signage in the image frame, counting a least a potential number of people and a potential number of vehicles around the specific signage in the image frame, measuring a viewing angle formed between a driving direction of the vehicle or between a direction of movement of a person not in a vehicle and a viewing direction to the specific signage from the camera, classifying the specific signage into one of signage groups, and forming one or more databases including the classified signage groups and impact of each signage object.