The invention provides a method for constructing an automatic driving prediction energy-saving cognitive model based on ACT-R, and the method comprises the steps: carrying out the continuous sensing of external information through a visual module based on the safety situation estimation of perceptual declarative knowledge, transmitting the information to a memory module through visual buffering, and carrying out the prediction and safety situation estimation; constructing an automatic driving decision rule and a decision result based on the process knowledge, and triggering one or more decision plans and decision results by using the declarative knowledge and the safety situation estimation result in combination with a conventional automatic driving decision algorithm; and based on the vehicle transverse and longitudinal control of the optimized energy consumption, executing the transverse and longitudinal control of the vehicle by taking the energy consumption as an optimization target. According to the construction method of the ACT-R based automatic driving prediction energy-saving cognitive model provided by the invention, a human psychology ACT-R model is introduced into automatic driving prediction, prediction cognitive modeling is carried out on a driving environment, and the user experience of automatic driving is improved by taking optimization of energy consumption asa model target.

Method for constructing automatic driving prediction energy-saving cognitive model based on ACT-R

An autonomous vehicle, system and method of operating the autonomous vehicle are provided. The system includes a sensor, a reasoning engine and a navigation system. The sensor receives token data. Thereasoning engine performs an abductive inference on a fact determined from the token data to estimate a backward condition, and a deductive inference to the estimated backward condition in to order to predict a forward condition. The navigation system operates the autonomous vehicle based on the predicted forward condition.

Nedunuri Srinivas

Papers

Reasoning system for sensemaking in autonomous driving