Pub Date : 2017-11-01DOI: 10.2352/j.imagingsci.technol.2017.61.6.060403
Duyoung Heo, Eun-Ju Lee, ByoungChul Ko
{"title":"Pedestrian Detection at Night Using Deep Neural Networks and Saliency Maps","authors":"Duyoung Heo, Eun-Ju Lee, ByoungChul Ko","doi":"10.2352/j.imagingsci.technol.2017.61.6.060403","DOIUrl":"https://doi.org/10.2352/j.imagingsci.technol.2017.61.6.060403","url":null,"abstract":"","PeriodicalId":177462,"journal":{"name":"Autonomous Vehicles and Machines","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116686842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-04-08DOI: 10.2352/ISSN.2470-1173.2017.19.AVM-023
Ahmad El Sallab, Mohammed Abdou, E. Perot, S. Yogamani
Reinforcement learning is considered to be a strong AI paradigm which can be used to teach machines through interaction with the environment and learning from their mistakes. Despite its perceived utility, it has not yet been successfully applied in automotive applications. Motivated by the successful demonstrations of learning of Atari games and Go by Google DeepMind, we propose a framework for autonomous driving using deep reinforcement learning. This is of particular relevance as it is difficult to pose autonomous driving as a supervised learning problem due to strong interactions with the environment including other vehicles, pedestrians and roadworks. As it is a relatively new area of research for autonomous driving, we provide a short overview of deep reinforcement learning and then describe our proposed framework. It incorporates Recurrent Neural Networks for information integration, enabling the car to handle partially observable scenarios. It also integrates the recent work on attention models to focus on relevant information, thereby reducing the computational complexity for deployment on embedded hardware. The framework was tested in an open source 3D car racing simulator called TORCS. Our simulation results demonstrate learning of autonomous maneuvering in a scenario of complex road curvatures and simple interaction of other vehicles.
{"title":"Deep Reinforcement Learning framework for Autonomous Driving","authors":"Ahmad El Sallab, Mohammed Abdou, E. Perot, S. Yogamani","doi":"10.2352/ISSN.2470-1173.2017.19.AVM-023","DOIUrl":"https://doi.org/10.2352/ISSN.2470-1173.2017.19.AVM-023","url":null,"abstract":"Reinforcement learning is considered to be a strong AI paradigm which can be used to teach machines through interaction with the environment and learning from their mistakes. Despite its perceived utility, it has not yet been successfully applied in automotive applications. Motivated by the successful demonstrations of learning of Atari games and Go by Google DeepMind, we propose a framework for autonomous driving using deep reinforcement learning. This is of particular relevance as it is difficult to pose autonomous driving as a supervised learning problem due to strong interactions with the environment including other vehicles, pedestrians and roadworks. As it is a relatively new area of research for autonomous driving, we provide a short overview of deep reinforcement learning and then describe our proposed framework. It incorporates Recurrent Neural Networks for information integration, enabling the car to handle partially observable scenarios. It also integrates the recent work on attention models to focus on relevant information, thereby reducing the computational complexity for deployment on embedded hardware. The framework was tested in an open source 3D car racing simulator called TORCS. Our simulation results demonstrate learning of autonomous maneuvering in a scenario of complex road curvatures and simple interaction of other vehicles.","PeriodicalId":177462,"journal":{"name":"Autonomous Vehicles and Machines","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122435017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-01-29DOI: 10.2352/ISSN.2470-1173.2017.19.AVM-012
Vladimir Zlokolica, B. Deegan, Patrick Denny, M. P. Griffin, Barry Dever
{"title":"Free-view multi-camera visualization and harmonization for automotive systems","authors":"Vladimir Zlokolica, B. Deegan, Patrick Denny, M. P. Griffin, Barry Dever","doi":"10.2352/ISSN.2470-1173.2017.19.AVM-012","DOIUrl":"https://doi.org/10.2352/ISSN.2470-1173.2017.19.AVM-012","url":null,"abstract":"","PeriodicalId":177462,"journal":{"name":"Autonomous Vehicles and Machines","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115460488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-01-29DOI: 10.2352/ISSN.2470-1173.2017.19.AVM-014
Christian Fuchs, D. Paulus
{"title":"Perspectively Correct Bird's Views Using Stereo Vision","authors":"Christian Fuchs, D. Paulus","doi":"10.2352/ISSN.2470-1173.2017.19.AVM-014","DOIUrl":"https://doi.org/10.2352/ISSN.2470-1173.2017.19.AVM-014","url":null,"abstract":"","PeriodicalId":177462,"journal":{"name":"Autonomous Vehicles and Machines","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127817753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-01-29DOI: 10.2352/ISSN.2470-1173.2017.19.AVM-019
S. Echefu, Jacob Lauzon, Suvam Bag, Rasika Kangutkar, A. Bhatt, R. Ptucha
{"title":"Milpet - The Self-Driving Wheelchair","authors":"S. Echefu, Jacob Lauzon, Suvam Bag, Rasika Kangutkar, A. Bhatt, R. Ptucha","doi":"10.2352/ISSN.2470-1173.2017.19.AVM-019","DOIUrl":"https://doi.org/10.2352/ISSN.2470-1173.2017.19.AVM-019","url":null,"abstract":"","PeriodicalId":177462,"journal":{"name":"Autonomous Vehicles and Machines","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134467223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-01-29DOI: 10.2352/ISSN.2470-1173.2017.19.AVM-022
Suvam Bag, V. Venkatachalapathy, R. Ptucha
{"title":"Motion Estimation Using Visual Odometry and Deep Learning Localization","authors":"Suvam Bag, V. Venkatachalapathy, R. Ptucha","doi":"10.2352/ISSN.2470-1173.2017.19.AVM-022","DOIUrl":"https://doi.org/10.2352/ISSN.2470-1173.2017.19.AVM-022","url":null,"abstract":"","PeriodicalId":177462,"journal":{"name":"Autonomous Vehicles and Machines","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116842450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-01-29DOI: 10.2352/ISSN.2470-1173.2017.19.AVM-025
B. Shankar, D. Jayachandra, K. K. Hati
{"title":"Face Pose Estimation From Rigid Face Landmarks For Driver Monitoring Systems","authors":"B. Shankar, D. Jayachandra, K. K. Hati","doi":"10.2352/ISSN.2470-1173.2017.19.AVM-025","DOIUrl":"https://doi.org/10.2352/ISSN.2470-1173.2017.19.AVM-025","url":null,"abstract":"","PeriodicalId":177462,"journal":{"name":"Autonomous Vehicles and Machines","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115682364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-01-29DOI: 10.2352/ISSN.2470-1173.2017.19.AVM-024
M. Andalibi, D. Chandler
Glare due to sunlight, moonlight, or other light sources can be a serious impediment during autonomous or manual driving. Automatically detecting the presence, location, and severity of such glare can be of critical importance for an autonomous driving system, which may then give greater priority to other sensors or cues/parts of the scene. We present an algorithm for automatic real-time glare detection that uses a combination of: (1) the intensity, saturation, and local contrast of the input frame; (2) shape detection; and (3) solar azimuth and elevation computed based on the position and heading information from the GPS (used under daylight conditions). These data are used to generate a glare occurrence map that indicates the center location(s) and extent(s) of the glare region(s). Testing on a variety of daytime and nighttime scenes demonstrates that the proposed system is effective at glare detection and is capable of real-time operation.
{"title":"Automatic Glare Detection via Photometric, Geometric, and Global Positioning Information","authors":"M. Andalibi, D. Chandler","doi":"10.2352/ISSN.2470-1173.2017.19.AVM-024","DOIUrl":"https://doi.org/10.2352/ISSN.2470-1173.2017.19.AVM-024","url":null,"abstract":"Glare due to sunlight, moonlight, or other light sources can be a serious impediment during autonomous or manual driving. Automatically detecting the presence, location, and severity of such glare can be of critical importance for an autonomous driving system, which may then give greater priority to other sensors or cues/parts of the scene. We present an algorithm for automatic real-time glare detection that uses a combination of: (1) the intensity, saturation, and local contrast of the input frame; (2) shape detection; and (3) solar azimuth and elevation computed based on the position and heading information from the GPS (used under daylight conditions). These data are used to generate a glare occurrence map that indicates the center location(s) and extent(s) of the glare region(s). Testing on a variety of daytime and nighttime scenes demonstrates that the proposed system is effective at glare detection and is capable of real-time operation.","PeriodicalId":177462,"journal":{"name":"Autonomous Vehicles and Machines","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116199383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-01-29DOI: 10.2352/ISSN.2470-1173.2017.19.AVM-451
N. Koren, RobertC Sumner, Henry L. T. Koren
{"title":"Measuring MTF with wedges: pitfalls and best practices","authors":"N. Koren, RobertC Sumner, Henry L. T. Koren","doi":"10.2352/ISSN.2470-1173.2017.19.AVM-451","DOIUrl":"https://doi.org/10.2352/ISSN.2470-1173.2017.19.AVM-451","url":null,"abstract":"","PeriodicalId":177462,"journal":{"name":"Autonomous Vehicles and Machines","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130106744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-01-29DOI: 10.2352/ISSN.2470-1173.2017.19.AVM-017
Kedar Chitnis, Mihir Mody, P. Swami, R. Sivaraj, C. Ghone, M. Biju, B. Narayanan, Yashwant Dutt, Aish Dubey
{"title":"Enabling Functional Safety ASIL Compliance for Autonomous Driving Software Systems","authors":"Kedar Chitnis, Mihir Mody, P. Swami, R. Sivaraj, C. Ghone, M. Biju, B. Narayanan, Yashwant Dutt, Aish Dubey","doi":"10.2352/ISSN.2470-1173.2017.19.AVM-017","DOIUrl":"https://doi.org/10.2352/ISSN.2470-1173.2017.19.AVM-017","url":null,"abstract":"","PeriodicalId":177462,"journal":{"name":"Autonomous Vehicles and Machines","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129847399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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