Abstract: A computer implemented method for evaluating autonomous vehicle safety that includes defining criteria for safety of autonomous vehicles in a test space, and dividing the test space into an intended test space and a un-intended test space for the criteria for safety of autonomous vehicles. The intended test space includes characterizations for the autonomous vehicle that can be quantified, and the un-intended test space includes characterizations that are not quantifiable. The method further includes measuring the safety of the autonomous vehicles in the intended test space. The applying the un-intended test space is applied to the intended test space as feedback into the intended test space; and evaluating the intended test space including the feedback from the unintended test space using a combined simulation of peripheral vehicles and autonomous vehicles to provide the evaluation of autonomous vehicle safety.

Abstract: A computer implemented method for evaluating autonomous vehicle safety that includes defining criteria for safety of autonomous vehicles in a test space, and dividing the test space into an intended test space and a un-intended test space for the criteria for safety of autonomous vehicles. The intended test space includes characterizations for the autonomous vehicle that can be quantified, and the un-intended test space includes characterizations that are not quantifiable. The method further includes measuring the safety of the autonomous vehicles in the intended test space. The applying the un-intended test space is applied to the intended test space as feedback into the intended test space; and evaluating the intended test space including the feedback from the unintended test space using a combined simulation of peripheral vehicles and autonomous vehicles to provide the evaluation of autonomous vehicle safety.

Abstract: A computer implemented method for scenario generation for autonomous vehicle navigation that can include defining a cellular automaton layer that defines a road network level behavior with at least one rule directed to pathways by vehicles on a passageway for travel. The method may further include defining an active matter layer that defines a vehicle level behavior with at least one rule directed to movement of the vehicles on an ideal route for the pathways; and defining a driver agent layer that defines driving nature with at least one rule that impacts changes in the vehicle level behavior dependent upon a characterization of driver behavior. The method may further include combining outputs from the different layer to provide scenario generations for autonomous vehicle navigation. The combining of the outputs can utilize a pseudo random value to determine at an order in the execution and duration of execution for the layers.

Abstract: A computer implemented method for generating traffic pathways that includes recording images from a transportation site with a fixed position camera. The method further includes extracting vehicle point data from the images, and calculating projected vehicle characteristics from the extracted point data to provide an extracted vehicle continuous data set. The method may further include generating a simulated traffic flow and simulated vehicle motion from the extracted vehicle continuous data set. A traffic pathway can be calculated using simulated vehicle motion and simulated traffic flow. The traffic pathway can be used for directing a guided vehicle on the transportation site.

Abstract: A computer implemented method for scenario generation for autonomous vehicle navigation that can include defining a cellular automaton layer that defines a road network level behavior with at least one rule directed to pathways by vehicles on a passageway for travel. The method may further include defining an active matter layer that defines a vehicle level behavior with at least one rule directed to movement of the vehicles on an ideal route for the pathways; and defining a driver agent layer that defines driving nature with at least one rule that impacts changes in the vehicle level behavior dependent upon a characterization of driver behavior. The method may further include combining outputs from the different layer to provide scenario generations for autonomous vehicle navigation. The combining of the outputs can utilize a pseudo random value to determine at an order in the execution and duration of execution for the layers.

Abstract: A computer implemented method for generating traffic pathways that includes recording images from a transportation site with a fixed position camera. The method further includes extracting vehicle point data from the images, and calculating projected vehicle characteristics from the extracted point data to provide an extracted vehicle continuous data set. The method may further include generating a simulated traffic flow and simulated vehicle motion from the extracted vehicle continuous data set. A traffic pathway can be calculated using simulated vehicle motion and simulated traffic flow. The traffic pathway can be used for directing a guided vehicle on the transportation site.

Abstract: A computer implemented method for evaluating autonomous vehicle safety that includes defining criteria for safety of autonomous vehicles in a test space, and dividing the test space into an intended test space and a un-intended test space for the criteria for safety of autonomous vehicles. The intended test space includes characterizations for the autonomous vehicle that can be quantified, and the un-intended test space includes characterizations that are not quantifiable. The method further includes measuring the safety of the autonomous vehicles in the intended test space. The applying the un-intended test space is applied to the intended test space as feedback into the intended test space; and evaluating the intended test space including the feedback from the unintended test space using a combined simulation of peripheral vehicles and autonomous vehicles to provide the evaluation of autonomous vehicle safety.