Pub Date : 2014-06-08DOI: 10.1109/IVS.2014.6856465
Huan Huang, Shiying Li, Kai Tang, Renfa Li
We present a two-stage method to accurately segment single or multiple moving objects and their shadows, especially when the moving objects have similar chromaticity and intensity to their shadows or when they are immersed in the shadows of other moving objects. Our algorithm first detects potential shadows via brightness ratios at each motion region, which is already separated from the background of an image sequence. Movement patterns are then applied to optimize the regions of moving objects and their shadows. We conducted experiments using our captured image sequences and public videos of Highway I and II to verify our method. The results demonstrate the method's efficiency quantitatively and qualitatively in comparison with ground truth and several advanced methods.
{"title":"Accurate segmentation of moving objects and their shadows via brightness ratios and movement patterns","authors":"Huan Huang, Shiying Li, Kai Tang, Renfa Li","doi":"10.1109/IVS.2014.6856465","DOIUrl":"https://doi.org/10.1109/IVS.2014.6856465","url":null,"abstract":"We present a two-stage method to accurately segment single or multiple moving objects and their shadows, especially when the moving objects have similar chromaticity and intensity to their shadows or when they are immersed in the shadows of other moving objects. Our algorithm first detects potential shadows via brightness ratios at each motion region, which is already separated from the background of an image sequence. Movement patterns are then applied to optimize the regions of moving objects and their shadows. We conducted experiments using our captured image sequences and public videos of Highway I and II to verify our method. The results demonstrate the method's efficiency quantitatively and qualitatively in comparison with ground truth and several advanced methods.","PeriodicalId":254500,"journal":{"name":"2014 IEEE Intelligent Vehicles Symposium Proceedings","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133396359","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 : 2014-06-08DOI: 10.1109/IVS.2014.6856549
Clément Zinoune, P. Bonnifait, J. Guzman
Currently, Advanced Driving Assistance Systems (ADAS) increasingly rely on information stored in vehicle on board digital maps. The vehicle position is projected onto the map to establish oncoming road context. However, errors might exist in the road geometry stored in the maps. The integrity of this map-matched estimate must be monitored in real-time to avoid errors that can lead to hazardous situations. This paper presents a monitoring system and fault detection, isolation and adaptation formalism which benefits of multiple vehicle journeys (e.g. commuting). We demonstrate that it is possible to assert correct navigation information within the first journey to a new area and to isolate areas where the road geometry is erroneous after the second journey. The approach takes into account errors that might occur on the estimation of the global vehicle position. The proposed formalism was experimentally validated using a passenger vehicle driven in different map and GNSS conditions.
{"title":"Integrity monitoring of navigation systems using repetitive journeys","authors":"Clément Zinoune, P. Bonnifait, J. Guzman","doi":"10.1109/IVS.2014.6856549","DOIUrl":"https://doi.org/10.1109/IVS.2014.6856549","url":null,"abstract":"Currently, Advanced Driving Assistance Systems (ADAS) increasingly rely on information stored in vehicle on board digital maps. The vehicle position is projected onto the map to establish oncoming road context. However, errors might exist in the road geometry stored in the maps. The integrity of this map-matched estimate must be monitored in real-time to avoid errors that can lead to hazardous situations. This paper presents a monitoring system and fault detection, isolation and adaptation formalism which benefits of multiple vehicle journeys (e.g. commuting). We demonstrate that it is possible to assert correct navigation information within the first journey to a new area and to isolate areas where the road geometry is erroneous after the second journey. The approach takes into account errors that might occur on the estimation of the global vehicle position. The proposed formalism was experimentally validated using a passenger vehicle driven in different map and GNSS conditions.","PeriodicalId":254500,"journal":{"name":"2014 IEEE Intelligent Vehicles Symposium Proceedings","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116721855","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 : 2014-06-08DOI: 10.1109/IVS.2014.6856512
Valentin Magnier, D. Gruyer
In this paper a new algorithm for multi-targets tracking for roadway environment is proposed. This new approach is based on two parallel tracking stages. Its objective is to improve associations between targets and tracks by avoiding wrong associations which can cause errors on track's path determination. Another interesting point of the proposed approach lies in the fact that the two trackings stages are operated together only when association ambiguities are detected. otherwise, only one tracking is used. This mechanism leads to save computational resources. This contribution comes after previous works achieved at the LIVIC (Laboratory on interactions between vehicles, road network and drivers) regarding to Multi-Hypothesis Tracking (MHT) using the Dempster-Shafer Theory. These previous works discussed the potential interest of considering at the same time multi-hypothesis solutions instead of mono-hypothesis ones. This new approach is more focused on the identification of ambiguities, and runs simultaneously two tracking stages in order to solve these ambiguities thanks to the Dempster-Shafer multi-criteria association rules. The paper will therefore explain quickly the basis of the MHT and then describe the Dual Tracking Ambiguities' Solving (DTAS) algorithm. Finally, a relevant case of study showing the interest of the DTAS will be discussed.
{"title":"Dual multi-targets tracking for ambiguities' identification and solving","authors":"Valentin Magnier, D. Gruyer","doi":"10.1109/IVS.2014.6856512","DOIUrl":"https://doi.org/10.1109/IVS.2014.6856512","url":null,"abstract":"In this paper a new algorithm for multi-targets tracking for roadway environment is proposed. This new approach is based on two parallel tracking stages. Its objective is to improve associations between targets and tracks by avoiding wrong associations which can cause errors on track's path determination. Another interesting point of the proposed approach lies in the fact that the two trackings stages are operated together only when association ambiguities are detected. otherwise, only one tracking is used. This mechanism leads to save computational resources. This contribution comes after previous works achieved at the LIVIC (Laboratory on interactions between vehicles, road network and drivers) regarding to Multi-Hypothesis Tracking (MHT) using the Dempster-Shafer Theory. These previous works discussed the potential interest of considering at the same time multi-hypothesis solutions instead of mono-hypothesis ones. This new approach is more focused on the identification of ambiguities, and runs simultaneously two tracking stages in order to solve these ambiguities thanks to the Dempster-Shafer multi-criteria association rules. The paper will therefore explain quickly the basis of the MHT and then describe the Dual Tracking Ambiguities' Solving (DTAS) algorithm. Finally, a relevant case of study showing the interest of the DTAS will be discussed.","PeriodicalId":254500,"journal":{"name":"2014 IEEE Intelligent Vehicles Symposium Proceedings","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114789784","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 : 2014-06-08DOI: 10.1109/IVS.2014.6856532
F. Flohr, Madalin Dumitru-Guzu, Julian F. P. Kooij, D. Gavrila
We present an approach for the joint probabilistic estimation of pedestrian head and body orientation in the context of intelligent vehicles. For both, head and body, we convert the output of a set of orientation-specific detectors into a full (continuous) probability density function. The parts are localized with a pictorial structure approach which balances part-based detector output with spatial constraints. Head and body orientation estimates are furthermore coupled probabilistically to account for anatomical constraints. Finally, the coupled single-frame orientation estimates are integrated over time by particle filtering. The experiments involve 37 pedestrian tracks obtained from an external stereo vision-based pedestrian detector in realistic traffic settings. We show that the proposed joint probabilistic orientation estimation approach reduces the mean head and body orientation error by 10 degrees and more.
{"title":"Joint probabilistic pedestrian head and body orientation estimation","authors":"F. Flohr, Madalin Dumitru-Guzu, Julian F. P. Kooij, D. Gavrila","doi":"10.1109/IVS.2014.6856532","DOIUrl":"https://doi.org/10.1109/IVS.2014.6856532","url":null,"abstract":"We present an approach for the joint probabilistic estimation of pedestrian head and body orientation in the context of intelligent vehicles. For both, head and body, we convert the output of a set of orientation-specific detectors into a full (continuous) probability density function. The parts are localized with a pictorial structure approach which balances part-based detector output with spatial constraints. Head and body orientation estimates are furthermore coupled probabilistically to account for anatomical constraints. Finally, the coupled single-frame orientation estimates are integrated over time by particle filtering. The experiments involve 37 pedestrian tracks obtained from an external stereo vision-based pedestrian detector in realistic traffic settings. We show that the proposed joint probabilistic orientation estimation approach reduces the mean head and body orientation error by 10 degrees and more.","PeriodicalId":254500,"journal":{"name":"2014 IEEE Intelligent Vehicles Symposium Proceedings","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115461232","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 : 2014-06-08DOI: 10.1109/IVS.2014.6856540
Kuo-Yun Liang, J. Mårtensson, K. Johansson
Vehicle platooning is important for heavy-duty vehicle manufacturers, due to the reduced aerodynamic drag for the follower vehicles, which gives an overall lower fuel consumption. Heavy-duty vehicle drivers are aware this fact and sometimes drive close to other heavy-duty vehicles. However, it is not currently well known how many vehicles are actually driving in such spontaneous platoons today. This paper studies the platooning rate of 1,800 heavy-duty vehicles by analyzing sparse vehicle position data from a region in Europe during one day. Map-matching and path-inference algorithms are used to determine which paths the vehicles took. The spontaneous platooning rate is found to be 1.2 %, which corresponds to a total fuel saving of 0.07% compared to if none of the vehicles were platooning. Furthermore, we introduce several virtual coordination schemes. We show that coordinations can increase the platooning rate and fuel saving with a factor of ten with minor adjustments from the current travel schedule. The platooning rate and fuel savings can be significantly greater if higher flexibility is allowed.
{"title":"Fuel-saving potentials of platooning evaluated through sparse heavy-duty vehicle position data","authors":"Kuo-Yun Liang, J. Mårtensson, K. Johansson","doi":"10.1109/IVS.2014.6856540","DOIUrl":"https://doi.org/10.1109/IVS.2014.6856540","url":null,"abstract":"Vehicle platooning is important for heavy-duty vehicle manufacturers, due to the reduced aerodynamic drag for the follower vehicles, which gives an overall lower fuel consumption. Heavy-duty vehicle drivers are aware this fact and sometimes drive close to other heavy-duty vehicles. However, it is not currently well known how many vehicles are actually driving in such spontaneous platoons today. This paper studies the platooning rate of 1,800 heavy-duty vehicles by analyzing sparse vehicle position data from a region in Europe during one day. Map-matching and path-inference algorithms are used to determine which paths the vehicles took. The spontaneous platooning rate is found to be 1.2 %, which corresponds to a total fuel saving of 0.07% compared to if none of the vehicles were platooning. Furthermore, we introduce several virtual coordination schemes. We show that coordinations can increase the platooning rate and fuel saving with a factor of ten with minor adjustments from the current travel schedule. The platooning rate and fuel savings can be significantly greater if higher flexibility is allowed.","PeriodicalId":254500,"journal":{"name":"2014 IEEE Intelligent Vehicles Symposium Proceedings","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115957917","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 : 2014-06-08DOI: 10.1109/IVS.2014.6856564
Oliver Hartmann, Michael Gabb, R. Schweiger, K. Dietmayer
Digital maps are becoming increasingly important for driver assistance systems: providing optimal lighting conditions in night scenarios, presenting the road geometry to the driver, or for usage in autonomous driving tasks. However, recorded digital maps own one drawback: due to road changes and inaccurate recordings, discrepancies between the map and the real world exist. Because these discrepancies can lead to severe application level failures, detection of map errors is essential to ensure overall system integrity. This work proposes a new approach to online verification of digital maps for automotive usage. In contrast to previous work, the described system is able to detect errors in front of the vehicle. On the basis of a large database of map geometry and sensor information, a neural network is trained to classify the digital map integrity by optimally fusing different information sources depending on their strength and reliability. Although generally applicable, it is shown that a combination of orthogonal measurement principles is greatly beneficial for this decision task. A radar sensor, infra-red imagery and road geometry information estimated from visible light images are employed as input for the neural fusion. Experiments on real-world data verify the proposed concepts.
{"title":"Towards autonomous self-assessment of digital maps","authors":"Oliver Hartmann, Michael Gabb, R. Schweiger, K. Dietmayer","doi":"10.1109/IVS.2014.6856564","DOIUrl":"https://doi.org/10.1109/IVS.2014.6856564","url":null,"abstract":"Digital maps are becoming increasingly important for driver assistance systems: providing optimal lighting conditions in night scenarios, presenting the road geometry to the driver, or for usage in autonomous driving tasks. However, recorded digital maps own one drawback: due to road changes and inaccurate recordings, discrepancies between the map and the real world exist. Because these discrepancies can lead to severe application level failures, detection of map errors is essential to ensure overall system integrity. This work proposes a new approach to online verification of digital maps for automotive usage. In contrast to previous work, the described system is able to detect errors in front of the vehicle. On the basis of a large database of map geometry and sensor information, a neural network is trained to classify the digital map integrity by optimally fusing different information sources depending on their strength and reliability. Although generally applicable, it is shown that a combination of orthogonal measurement principles is greatly beneficial for this decision task. A radar sensor, infra-red imagery and road geometry information estimated from visible light images are employed as input for the neural fusion. Experiments on real-world data verify the proposed concepts.","PeriodicalId":254500,"journal":{"name":"2014 IEEE Intelligent Vehicles Symposium Proceedings","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123934930","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 : 2014-06-08DOI: 10.1109/IVS.2014.6856485
D. Margaria, E. Falletti, T. Acarman
This tutorial paper highlights possible issues related to the integrity and authentication of the GNSS position in road applications. In fact, the Global Navigation Satellite System (GNSS) community is already aware of the conceptual and practical problems related to the availability of the position integrity (i.e. position confidence, protection level) and authentication in urban scenarios. However, these issues seem not to be widely known in the Intelligent Transportation Systems (ITS) domain. These limitations need to be carefully considered and addressed in the perspective of deploying reliable and robust systems based on positioning information.
{"title":"The need for GNSS position integrity and authentication in ITS: Conceptual and practical limitations in urban contexts","authors":"D. Margaria, E. Falletti, T. Acarman","doi":"10.1109/IVS.2014.6856485","DOIUrl":"https://doi.org/10.1109/IVS.2014.6856485","url":null,"abstract":"This tutorial paper highlights possible issues related to the integrity and authentication of the GNSS position in road applications. In fact, the Global Navigation Satellite System (GNSS) community is already aware of the conceptual and practical problems related to the availability of the position integrity (i.e. position confidence, protection level) and authentication in urban scenarios. However, these issues seem not to be widely known in the Intelligent Transportation Systems (ITS) domain. These limitations need to be carefully considered and addressed in the perspective of deploying reliable and robust systems based on positioning information.","PeriodicalId":254500,"journal":{"name":"2014 IEEE Intelligent Vehicles Symposium Proceedings","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128948090","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 : 2014-06-08DOI: 10.1109/IVS.2014.6856615
C. Olaverri-Monreal, Joel Gonçalves, K. Bengler
Traveling with children in tow can pose a serious distraction to the driver, effectively drawing much of the necessary attention away from the road and causing a disruption in normal driving patterns. In this paper we investigate the driver's capacity to operate a vehicle safely when being exposed to a noise stimulus, specifically in the form of a crying baby for an extended period of time. For this purpose, we developed a tailored driving simulator framework to efficiently configure new experiments, built on modular components to make it easier to upgrade and update the experiment scenario and overall conditions. We then compared the driving behavior of parents to individuals without children focusing particularly on the affects on driving performance when a sudden event occurred on the road. We aim to study driving patterns under stressful conditions such as having children as occupants in the vehicle to be able to classify drivers for background training purposes regarding in-vehicle behavior. Results have shown the tendencies of parents when having a baby in the vehicle to produce better driving performances.
{"title":"Studying the driving performance of drivers with children aboard by means of a framework for flexible experiment configuration","authors":"C. Olaverri-Monreal, Joel Gonçalves, K. Bengler","doi":"10.1109/IVS.2014.6856615","DOIUrl":"https://doi.org/10.1109/IVS.2014.6856615","url":null,"abstract":"Traveling with children in tow can pose a serious distraction to the driver, effectively drawing much of the necessary attention away from the road and causing a disruption in normal driving patterns. In this paper we investigate the driver's capacity to operate a vehicle safely when being exposed to a noise stimulus, specifically in the form of a crying baby for an extended period of time. For this purpose, we developed a tailored driving simulator framework to efficiently configure new experiments, built on modular components to make it easier to upgrade and update the experiment scenario and overall conditions. We then compared the driving behavior of parents to individuals without children focusing particularly on the affects on driving performance when a sudden event occurred on the road. We aim to study driving patterns under stressful conditions such as having children as occupants in the vehicle to be able to classify drivers for background training purposes regarding in-vehicle behavior. Results have shown the tendencies of parents when having a baby in the vehicle to produce better driving performances.","PeriodicalId":254500,"journal":{"name":"2014 IEEE Intelligent Vehicles Symposium Proceedings","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130494024","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 : 2014-06-08DOI: 10.1109/IVS.2014.6856605
Aayush Bansal, H. Badino, Daniel F. Huber
Localization is a central problem for intelligent vehicles. Visual localization can supplement or replace GPS-based localization approaches in situations where GPS is unavailable or inaccurate. Although visual localization has been demonstrated in a variety of algorithms and systems, the problem of how to best configure such a system remains largely an open question. Design choices, such as “where should the camera be placed?” and “how should it be oriented?” can have substantial effect on the cost and robustness of a fielded intelligent vehicle. This paper analyzes how different sensor configuration parameters and environmental conditions affect visual localization performance with the goal of understanding what causes certain configurations to perform better than others and providing general principles for configuring systems for visual localization. We ground the investigation using extensive field testing of a visual localization algorithm, and the data sets used for the analysis are made available for comparative evaluation.
{"title":"Understanding how camera configuration and environmental conditions affect appearance-based localization","authors":"Aayush Bansal, H. Badino, Daniel F. Huber","doi":"10.1109/IVS.2014.6856605","DOIUrl":"https://doi.org/10.1109/IVS.2014.6856605","url":null,"abstract":"Localization is a central problem for intelligent vehicles. Visual localization can supplement or replace GPS-based localization approaches in situations where GPS is unavailable or inaccurate. Although visual localization has been demonstrated in a variety of algorithms and systems, the problem of how to best configure such a system remains largely an open question. Design choices, such as “where should the camera be placed?” and “how should it be oriented?” can have substantial effect on the cost and robustness of a fielded intelligent vehicle. This paper analyzes how different sensor configuration parameters and environmental conditions affect visual localization performance with the goal of understanding what causes certain configurations to perform better than others and providing general principles for configuring systems for visual localization. We ground the investigation using extensive field testing of a visual localization algorithm, and the data sets used for the analysis are made available for comparative evaluation.","PeriodicalId":254500,"journal":{"name":"2014 IEEE Intelligent Vehicles Symposium Proceedings","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130282092","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 : 2014-06-08DOI: 10.1109/IVS.2014.6856593
M. Zofka, R. Kohlhaas, T. Schamm, Johann Marius Zöllner
The design and development process of advanced driver assistance systems (ADAS) is divided into different phases, where the algorithms are implemented as a model, then as software and finally as hardware. Since it is unfeasable to simulate all possible driving situations for environmental perception and interpretation algorithms, there is still a need for expensive and time-consuming real test drives of thousands of kilometers. Therefore we present a novel approach for testing and evaluation of vision-based ADAS, where reliable simulations are fused with recorded data from test drives to provide a task-specific reference model. This approach provides ground truth with much higher reliability and reproducability than real test drives and authenticity than using pure simulations and can be applied already in early steps of the design process. We illustrate the effectiveness of our approach by testing a vision-based collision mitigation system on recordings of a german highway.
{"title":"Semivirtual simulations for the evaluation of vision-based ADAS","authors":"M. Zofka, R. Kohlhaas, T. Schamm, Johann Marius Zöllner","doi":"10.1109/IVS.2014.6856593","DOIUrl":"https://doi.org/10.1109/IVS.2014.6856593","url":null,"abstract":"The design and development process of advanced driver assistance systems (ADAS) is divided into different phases, where the algorithms are implemented as a model, then as software and finally as hardware. Since it is unfeasable to simulate all possible driving situations for environmental perception and interpretation algorithms, there is still a need for expensive and time-consuming real test drives of thousands of kilometers. Therefore we present a novel approach for testing and evaluation of vision-based ADAS, where reliable simulations are fused with recorded data from test drives to provide a task-specific reference model. This approach provides ground truth with much higher reliability and reproducability than real test drives and authenticity than using pure simulations and can be applied already in early steps of the design process. We illustrate the effectiveness of our approach by testing a vision-based collision mitigation system on recordings of a german highway.","PeriodicalId":254500,"journal":{"name":"2014 IEEE Intelligent Vehicles Symposium Proceedings","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130949176","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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