Alice Plebe , Henrik Svensson , Sara Mahmoud , Mauro Da Lio
{"title":"受人类启发的自动驾驶:一项调查","authors":"Alice Plebe , Henrik Svensson , Sara Mahmoud , Mauro Da Lio","doi":"10.1016/j.cogsys.2023.101169","DOIUrl":null,"url":null,"abstract":"<div><p>Autonomous vehicles promise to revolutionize society and improve the daily life of many, making them a coveted aim for a vast research community. To enable complex reasoning in autonomous vehicles, researchers are exploring new methods beyond traditional engineering approaches, in particular the idea of drawing inspiration from the only existing being able to drive: the human. The mental processes behind the human ability to drive can inspire new approaches with the potential to bridge the gap between artificial drivers and human drivers. In this review, we categorize and evaluate existing work on autonomous driving influenced by cognitive science, neuroscience, and psychology. We propose a taxonomy of the various sources of inspiration and identify the potential advantages with respect to traditional approaches. Although these human-inspired methods have not yet reached widespread adoption, we believe they are critical to the future of fully autonomous vehicles.</p></div>","PeriodicalId":55242,"journal":{"name":"Cognitive Systems Research","volume":"83 ","pages":"Article 101169"},"PeriodicalIF":2.1000,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Human-inspired autonomous driving: A survey\",\"authors\":\"Alice Plebe , Henrik Svensson , Sara Mahmoud , Mauro Da Lio\",\"doi\":\"10.1016/j.cogsys.2023.101169\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Autonomous vehicles promise to revolutionize society and improve the daily life of many, making them a coveted aim for a vast research community. To enable complex reasoning in autonomous vehicles, researchers are exploring new methods beyond traditional engineering approaches, in particular the idea of drawing inspiration from the only existing being able to drive: the human. The mental processes behind the human ability to drive can inspire new approaches with the potential to bridge the gap between artificial drivers and human drivers. In this review, we categorize and evaluate existing work on autonomous driving influenced by cognitive science, neuroscience, and psychology. We propose a taxonomy of the various sources of inspiration and identify the potential advantages with respect to traditional approaches. Although these human-inspired methods have not yet reached widespread adoption, we believe they are critical to the future of fully autonomous vehicles.</p></div>\",\"PeriodicalId\":55242,\"journal\":{\"name\":\"Cognitive Systems Research\",\"volume\":\"83 \",\"pages\":\"Article 101169\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2023-09-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cognitive Systems Research\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1389041723001031\",\"RegionNum\":3,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cognitive Systems Research","FirstCategoryId":"102","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1389041723001031","RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Autonomous vehicles promise to revolutionize society and improve the daily life of many, making them a coveted aim for a vast research community. To enable complex reasoning in autonomous vehicles, researchers are exploring new methods beyond traditional engineering approaches, in particular the idea of drawing inspiration from the only existing being able to drive: the human. The mental processes behind the human ability to drive can inspire new approaches with the potential to bridge the gap between artificial drivers and human drivers. In this review, we categorize and evaluate existing work on autonomous driving influenced by cognitive science, neuroscience, and psychology. We propose a taxonomy of the various sources of inspiration and identify the potential advantages with respect to traditional approaches. Although these human-inspired methods have not yet reached widespread adoption, we believe they are critical to the future of fully autonomous vehicles.
期刊介绍:
Cognitive Systems Research is dedicated to the study of human-level cognition. As such, it welcomes papers which advance the understanding, design and applications of cognitive and intelligent systems, both natural and artificial.
The journal brings together a broad community studying cognition in its many facets in vivo and in silico, across the developmental spectrum, focusing on individual capacities or on entire architectures. It aims to foster debate and integrate ideas, concepts, constructs, theories, models and techniques from across different disciplines and different perspectives on human-level cognition. The scope of interest includes the study of cognitive capacities and architectures - both brain-inspired and non-brain-inspired - and the application of cognitive systems to real-world problems as far as it offers insights relevant for the understanding of cognition.
Cognitive Systems Research therefore welcomes mature and cutting-edge research approaching cognition from a systems-oriented perspective, both theoretical and empirically-informed, in the form of original manuscripts, short communications, opinion articles, systematic reviews, and topical survey articles from the fields of Cognitive Science (including Philosophy of Cognitive Science), Artificial Intelligence/Computer Science, Cognitive Robotics, Developmental Science, Psychology, and Neuroscience and Neuromorphic Engineering. Empirical studies will be considered if they are supplemented by theoretical analyses and contributions to theory development and/or computational modelling studies.