In order to make full use of the driver’s long-term driving experience in the process of perception, interaction and vehicle control of road traffic information, a driving behavior rule extraction algorithm based on ...In order to make full use of the driver’s long-term driving experience in the process of perception, interaction and vehicle control of road traffic information, a driving behavior rule extraction algorithm based on artificial neural network interface(ANNI) and its integration is proposed. Firstly, based on the cognitive learning theory, the cognitive driving behavior model is established, and then the cognitive driving behavior is described and analyzed. Next, based on ANNI, the model and the rule extraction algorithm(ANNI-REA) are designed to explain not only the driving behavior but also the non-sequence. Rules have high fidelity and safety during driving without discretizing continuous input variables. The experimental results on the UCI standard data set and on the self-built driving behavior data set, show that the method is about 0.4% more accurate and about 10% less complex than the common C4.5-REA, Neuro-Rule and REFNE. Further, simulation experiments verify the correctness of the extracted driving rules and the effectiveness of the extraction based on cognitive driving behavior rules. In general, the several driving rules extracted fully reflect the execution mechanism of sequential activity of driving comprehensive cognition, which is of great significance for the traffic of mixed traffic flow under the network of vehicles and future research on unmanned driving.展开更多
The hermeneutic concept of horizon contributes to the philosophical understanding of scientific cognition. In the context of scientific cognitive practices, the concept of horizon provides a way of understanding the d...The hermeneutic concept of horizon contributes to the philosophical understanding of scientific cognition. In the context of scientific cognitive practices, the concept of horizon provides a way of understanding the distinctive characteristics of scientific observation and knowing. Horizon is a key factor that facilitates the cognitive subject to select objects and their backgrounds. In order to make new accomplishment in scientific discoveries, it is essential to broaden the horizon and intzoduce new cognitive instrumentalities and methods. This requires people to be adept at finding out the limitations of their thinking and overcome them consciously. Conscious horizon expansion is essential to the integration of intuition and logical thinking process in scientific cognitive activities, as well as to the establishment of the essential connection/relation between different disciplines and research fields, prompting inter-disciplinary communication and producing methods of thinking. This article is an attempt to explore the significance of horizon for scientific cognition. As we will show, by integrating intuitive thinking and logical thinking through the expansion of horizon, a new cognitive model will be provided.展开更多
基金Project(2017YFB0102503)supported by the National Key Research and Development Program of ChinaProjects(U1664258,51875255,61601203)supported by the National Natural Science Foundation of China+1 种基金Projects(DZXX-048,2018-TD-GDZB-022)supported by the Jiangsu Province’s Six Talent Peak,ChinaProject(18KJA580002)supported by Major Natural Science Research Project of Higher Learning in Jiangsu Province,China
文摘In order to make full use of the driver’s long-term driving experience in the process of perception, interaction and vehicle control of road traffic information, a driving behavior rule extraction algorithm based on artificial neural network interface(ANNI) and its integration is proposed. Firstly, based on the cognitive learning theory, the cognitive driving behavior model is established, and then the cognitive driving behavior is described and analyzed. Next, based on ANNI, the model and the rule extraction algorithm(ANNI-REA) are designed to explain not only the driving behavior but also the non-sequence. Rules have high fidelity and safety during driving without discretizing continuous input variables. The experimental results on the UCI standard data set and on the self-built driving behavior data set, show that the method is about 0.4% more accurate and about 10% less complex than the common C4.5-REA, Neuro-Rule and REFNE. Further, simulation experiments verify the correctness of the extracted driving rules and the effectiveness of the extraction based on cognitive driving behavior rules. In general, the several driving rules extracted fully reflect the execution mechanism of sequential activity of driving comprehensive cognition, which is of great significance for the traffic of mixed traffic flow under the network of vehicles and future research on unmanned driving.
文摘The hermeneutic concept of horizon contributes to the philosophical understanding of scientific cognition. In the context of scientific cognitive practices, the concept of horizon provides a way of understanding the distinctive characteristics of scientific observation and knowing. Horizon is a key factor that facilitates the cognitive subject to select objects and their backgrounds. In order to make new accomplishment in scientific discoveries, it is essential to broaden the horizon and intzoduce new cognitive instrumentalities and methods. This requires people to be adept at finding out the limitations of their thinking and overcome them consciously. Conscious horizon expansion is essential to the integration of intuition and logical thinking process in scientific cognitive activities, as well as to the establishment of the essential connection/relation between different disciplines and research fields, prompting inter-disciplinary communication and producing methods of thinking. This article is an attempt to explore the significance of horizon for scientific cognition. As we will show, by integrating intuitive thinking and logical thinking through the expansion of horizon, a new cognitive model will be provided.
