Pub Date : 2011-06-05DOI: 10.1109/IVS.2011.5940548
Cuong Tran, A. Doshi, M. Trivedi
Pedal errors have been reported as a cause of fatal traffic accidents. However it is not well understood why and when these pedal errors happen as well as how to mitigate them. In this paper, we study pedal error events in a real-world stop-and-go driving experiment, in which we quantitatively analyze foot behavior with measurements from embedded vehicle sensors (e.g. brake or acceleration pedal state) as well as a video input looking at the driver's foot. Our analysis shows some initial insights in factors influencing pedal errors (beside other possible causes like driver age, gender, and driver workload), including Sequential Effects and Cue Modality. We also develop a new vision-based approach for driver foot behavior analysis and use it to predict brake and acceleration pedal presses. Experimental results over twelve different subjects show that the proposed approach correctly detects pedal misapplications approximately 200ms before the actual press. This indicates the potential of applying this approach to predict and mitigate pedal errors in real-world driving.
{"title":"Pedal error prediction by driver foot gesture analysis: A vision-based inquiry","authors":"Cuong Tran, A. Doshi, M. Trivedi","doi":"10.1109/IVS.2011.5940548","DOIUrl":"https://doi.org/10.1109/IVS.2011.5940548","url":null,"abstract":"Pedal errors have been reported as a cause of fatal traffic accidents. However it is not well understood why and when these pedal errors happen as well as how to mitigate them. In this paper, we study pedal error events in a real-world stop-and-go driving experiment, in which we quantitatively analyze foot behavior with measurements from embedded vehicle sensors (e.g. brake or acceleration pedal state) as well as a video input looking at the driver's foot. Our analysis shows some initial insights in factors influencing pedal errors (beside other possible causes like driver age, gender, and driver workload), including Sequential Effects and Cue Modality. We also develop a new vision-based approach for driver foot behavior analysis and use it to predict brake and acceleration pedal presses. Experimental results over twelve different subjects show that the proposed approach correctly detects pedal misapplications approximately 200ms before the actual press. This indicates the potential of applying this approach to predict and mitigate pedal errors in real-world driving.","PeriodicalId":117811,"journal":{"name":"2011 IEEE Intelligent Vehicles Symposium (IV)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125213853","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 : 2011-06-05DOI: 10.1109/IVS.2011.5940424
Florian Homm, N. Kaempchen, Darius Burschka
The knowledge about lanes and the exact position on the road is fundamental for many advanced driver assistance systems. In this paper, a novel iterative histogram based approach with occupancy grids for the detection of multiple lanes is proposed. In highway scenarios, our approach is highly suitable to determine the correct number of all existing lanes on the road. Additionally, the output of the laserscannner based lane detection is fused with a production-available vision based system. It is shown that both sensor systems perfectly complement each other to increase the robustness of a lane tracking system. The achieved accuracy of the fusion system, the laserscannner and video based system is evaluated with a highly accurate DGPS to investigate the performance with respect to lateral vehicle control applications.
{"title":"Fusion of laserscannner and video based lanemarking detection for robust lateral vehicle control and lane change maneuvers","authors":"Florian Homm, N. Kaempchen, Darius Burschka","doi":"10.1109/IVS.2011.5940424","DOIUrl":"https://doi.org/10.1109/IVS.2011.5940424","url":null,"abstract":"The knowledge about lanes and the exact position on the road is fundamental for many advanced driver assistance systems. In this paper, a novel iterative histogram based approach with occupancy grids for the detection of multiple lanes is proposed. In highway scenarios, our approach is highly suitable to determine the correct number of all existing lanes on the road. Additionally, the output of the laserscannner based lane detection is fused with a production-available vision based system. It is shown that both sensor systems perfectly complement each other to increase the robustness of a lane tracking system. The achieved accuracy of the fusion system, the laserscannner and video based system is evaluated with a highly accurate DGPS to investigate the performance with respect to lateral vehicle control applications.","PeriodicalId":117811,"journal":{"name":"2011 IEEE Intelligent Vehicles Symposium (IV)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116627617","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 : 2011-06-05DOI: 10.1109/IVS.2011.5940546
S. Lovegrove, A. Davison, J. Guzman
As an increasing number of automatic safety and navigation features are added to modern vehicles, the crucial job of providing real-time localisation is predominantly performed by a single sensor, GPS, despite its well-known failings, particularly in urban environments. Various attempts have been made to supplement GPS to improve localisation performance, but these usually require additional specialised and expensive sensors. Offering increased value to vehicle OEMs, we show that it is possible to use just the video stream from a rear parking camera to produce smooth and locally accurate visual odometry in real-time. We use an efficient whole image alignment approach based on ESM, taking account of both the difficulties and advantages of the fact that a parking camera views only the road surface directly behind a vehicle. Visual odometry is complementary to GPS in offering localisation information at 30Hz which is smooth and highly accurate locally whilst GPS is course but offers absolute measurements. We demonstrate our system in a large scale experiment covering real urban driving. We also present real-time fusion of our visual estimation with automotive GPS to generate a commodity-cost localisation solution which is smooth, accurate and drift free in global coordinates.
{"title":"Accurate visual odometry from a rear parking camera","authors":"S. Lovegrove, A. Davison, J. Guzman","doi":"10.1109/IVS.2011.5940546","DOIUrl":"https://doi.org/10.1109/IVS.2011.5940546","url":null,"abstract":"As an increasing number of automatic safety and navigation features are added to modern vehicles, the crucial job of providing real-time localisation is predominantly performed by a single sensor, GPS, despite its well-known failings, particularly in urban environments. Various attempts have been made to supplement GPS to improve localisation performance, but these usually require additional specialised and expensive sensors. Offering increased value to vehicle OEMs, we show that it is possible to use just the video stream from a rear parking camera to produce smooth and locally accurate visual odometry in real-time. We use an efficient whole image alignment approach based on ESM, taking account of both the difficulties and advantages of the fact that a parking camera views only the road surface directly behind a vehicle. Visual odometry is complementary to GPS in offering localisation information at 30Hz which is smooth and highly accurate locally whilst GPS is course but offers absolute measurements. We demonstrate our system in a large scale experiment covering real urban driving. We also present real-time fusion of our visual estimation with automotive GPS to generate a commodity-cost localisation solution which is smooth, accurate and drift free in global coordinates.","PeriodicalId":117811,"journal":{"name":"2011 IEEE Intelligent Vehicles Symposium (IV)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121114245","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 : 2011-06-05DOI: 10.1109/IVS.2011.5940469
Dennis Müller, J. Pauli, M. Meuter, Lali Ghosh, Stefan Müller-Schneiders
This paper presents an automotive video and radar data fusion framework that can be used as a preliminary stage of an automatic cruise control or collision mitigation by braking system. The fusion framework finds the optimal assignment of radar and camera target reports and provides improved state estimates for the fused targets. A sophisticated critical path selection is presented and used in the critical target selection module that aims to select the most relevant target. This module is capable of identifying targets that cut into the ego lane or cut out from the ego lane and incorporate that into the final target selection. The selected target is then compared to a state of the art algorithm within the radar sensor. Additional test drives were made to evaluate the performance of the new algorithm. Due to its low computational effort and the sensor independent design the presented algorithm is suitable to be used in the automotive embedded environment.
{"title":"A generic video and radar data fusion system for improved target selection","authors":"Dennis Müller, J. Pauli, M. Meuter, Lali Ghosh, Stefan Müller-Schneiders","doi":"10.1109/IVS.2011.5940469","DOIUrl":"https://doi.org/10.1109/IVS.2011.5940469","url":null,"abstract":"This paper presents an automotive video and radar data fusion framework that can be used as a preliminary stage of an automatic cruise control or collision mitigation by braking system. The fusion framework finds the optimal assignment of radar and camera target reports and provides improved state estimates for the fused targets. A sophisticated critical path selection is presented and used in the critical target selection module that aims to select the most relevant target. This module is capable of identifying targets that cut into the ego lane or cut out from the ego lane and incorporate that into the final target selection. The selected target is then compared to a state of the art algorithm within the radar sensor. Additional test drives were made to evaluate the performance of the new algorithm. Due to its low computational effort and the sensor independent design the presented algorithm is suitable to be used in the automotive embedded environment.","PeriodicalId":117811,"journal":{"name":"2011 IEEE Intelligent Vehicles Symposium (IV)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121240378","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 : 2011-06-05DOI: 10.1109/IVS.2011.5940431
M. Maile, F. Ahmed-Zaid, Sue Bai, L. Caminiti, P. Mudalige, Michael Peredo, Z. Popovic
Crashes in intersections caused by a violation of traffic signals or stop signs amount to a significant portion of all vehicle crashes. The percentage of fatal crashes that occur at intersections remains constant over the years at nearly 22% of all crashes [1]. Vehicle-to Infrastructure (V2I) communications is a powerful technology that can address some of these crash scenarios. In order for tV2I based vehicle safety systems to be tested for correct functionality, and Field Operational Test FOT) readiness, Objective Test Procedures (OTP) have to be adopted. The Vehicle Safety Communications 2 (VSC- Consortium developed a Cooperative Intersection Collision Avoidance System - Violations (CICAS-V) and, in cooperation with the Research and Innovative Technology Administration's Intelligent Transportation Systems Joint Program Office and Of the National Highway Traffic Safety Administration (NHTSA) the United States Department of Transportation (USDOT). Using cooperatively developed OTP the performance of the CICAS-V was tested to determine if the system could be driven by naïve drivers on open roads. The CICAS-V was tested against all the OTP and successfully passed every test.
{"title":"Objective testing of a cooperative intersection collision avoidance system for traffic signal and stop sign violation","authors":"M. Maile, F. Ahmed-Zaid, Sue Bai, L. Caminiti, P. Mudalige, Michael Peredo, Z. Popovic","doi":"10.1109/IVS.2011.5940431","DOIUrl":"https://doi.org/10.1109/IVS.2011.5940431","url":null,"abstract":"Crashes in intersections caused by a violation of traffic signals or stop signs amount to a significant portion of all vehicle crashes. The percentage of fatal crashes that occur at intersections remains constant over the years at nearly 22% of all crashes [1]. Vehicle-to Infrastructure (V2I) communications is a powerful technology that can address some of these crash scenarios. In order for tV2I based vehicle safety systems to be tested for correct functionality, and Field Operational Test FOT) readiness, Objective Test Procedures (OTP) have to be adopted. The Vehicle Safety Communications 2 (VSC- Consortium developed a Cooperative Intersection Collision Avoidance System - Violations (CICAS-V) and, in cooperation with the Research and Innovative Technology Administration's Intelligent Transportation Systems Joint Program Office and Of the National Highway Traffic Safety Administration (NHTSA) the United States Department of Transportation (USDOT). Using cooperatively developed OTP the performance of the CICAS-V was tested to determine if the system could be driven by naïve drivers on open roads. The CICAS-V was tested against all the OTP and successfully passed every test.","PeriodicalId":117811,"journal":{"name":"2011 IEEE Intelligent Vehicles Symposium (IV)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126127631","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 : 2011-06-05DOI: 10.1109/IVS.2011.5940464
P. Angkititrakul, C. Miyajima, K. Takeda
In this paper, we present our recently developed stochastic driver-behavior model based on Gaussian mixture model (GMM) framework. The proposed driver-behavior modeling is employed to anticipate car-following behavior in terms of pedal control operations in response to the observable driving signals, such as the own vehicle velocity and the following distance to the leading vehicle. In addition, the proposed driver modeling allows adaptation scheme to enhance the model capability to better represent particular driving characteristics of interest (i.e., individual driving style) from the observed driving data themselves. Validation and comparison of the proposed driver-behavior models on realistic car-following data of several drivers showed the promising results. Furthermore, the adapted driver models showed consistent improvement over the unadapted driver models in both short-term and long-term predictions.
{"title":"Modeling and adaptation of stochastic driver-behavior model with application to car following","authors":"P. Angkititrakul, C. Miyajima, K. Takeda","doi":"10.1109/IVS.2011.5940464","DOIUrl":"https://doi.org/10.1109/IVS.2011.5940464","url":null,"abstract":"In this paper, we present our recently developed stochastic driver-behavior model based on Gaussian mixture model (GMM) framework. The proposed driver-behavior modeling is employed to anticipate car-following behavior in terms of pedal control operations in response to the observable driving signals, such as the own vehicle velocity and the following distance to the leading vehicle. In addition, the proposed driver modeling allows adaptation scheme to enhance the model capability to better represent particular driving characteristics of interest (i.e., individual driving style) from the observed driving data themselves. Validation and comparison of the proposed driver-behavior models on realistic car-following data of several drivers showed the promising results. Furthermore, the adapted driver models showed consistent improvement over the unadapted driver models in both short-term and long-term predictions.","PeriodicalId":117811,"journal":{"name":"2011 IEEE Intelligent Vehicles Symposium (IV)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125578603","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 : 2011-06-05DOI: 10.1109/IVS.2011.5940413
S. Vasantha Kumar, L. Vanajakshi, S. Subramanian
Travel time is one of the most preferred traffic information by a wide variety of travelers. Travel time information provided through variable message signs at the roadside could be viewed as a traffic management strategy designed to encourage drivers to take an alternate route. At the same time, it could also be viewed as a traveler information service designed to ensure that the driver has the best available information based on which they can make travel decisions. In an Intelligent Transportation Systems (ITS) context, both the Advanced Traveler Information Systems (ATIS) and the Advance Traffic Management Systems (ATMS) rely on accurate travel time prediction along arterials or freeways. In India, currently there is no permanent system of active test vehicles or license plate matching techniques to measure stream travel time in urban arterials. However, the public transit vehicles are being equipped with Global Positioning System (GPS) devices in major metropolitan cities of India for providing the bus arrival time information at bus stops. However, equipping private vehicles with GPS to enable the stream travel time measurement is difficult due to the requirement of public participation. The use of the GPS equipped buses as probe vehicles and estimating the stream travel time is a possible solution to this problem. The use of public transit as probes for travel time estimation offers advantages like frequent trips during peak hours, wide range network coverage, etc. However, the travel time characteristics of public transit buses are influenced by the transit characteristics like frequent acceleration, deceleration and stops due to bus stops besides their physical characteristics. Also, the sample size of public transit is less when compared to the total vehicle population. Thus mapping the bus travel time to stream travel time is a real challenge and this difficulty is more complex in traffic conditions like in India with its heterogeneity and lack of lane discipline. As a pilot study, a model based approach using the Kalman filtering technique to predict stream travel time from public transit is carried out in the present study. Since it is only a pilot study, only twowheeled vehicles have been considered as they constitute a major proportion in the study area. The prediction scheme is corroborated using field data collected by carrying GPS units in two-wheelers traveling along with the buses under consideration. The travel time estimates from the model were compared with the manually observed travel times and the results are encouraging.
{"title":"A model based approach to predict stream travel time using public transit as probes","authors":"S. Vasantha Kumar, L. Vanajakshi, S. Subramanian","doi":"10.1109/IVS.2011.5940413","DOIUrl":"https://doi.org/10.1109/IVS.2011.5940413","url":null,"abstract":"Travel time is one of the most preferred traffic information by a wide variety of travelers. Travel time information provided through variable message signs at the roadside could be viewed as a traffic management strategy designed to encourage drivers to take an alternate route. At the same time, it could also be viewed as a traveler information service designed to ensure that the driver has the best available information based on which they can make travel decisions. In an Intelligent Transportation Systems (ITS) context, both the Advanced Traveler Information Systems (ATIS) and the Advance Traffic Management Systems (ATMS) rely on accurate travel time prediction along arterials or freeways. In India, currently there is no permanent system of active test vehicles or license plate matching techniques to measure stream travel time in urban arterials. However, the public transit vehicles are being equipped with Global Positioning System (GPS) devices in major metropolitan cities of India for providing the bus arrival time information at bus stops. However, equipping private vehicles with GPS to enable the stream travel time measurement is difficult due to the requirement of public participation. The use of the GPS equipped buses as probe vehicles and estimating the stream travel time is a possible solution to this problem. The use of public transit as probes for travel time estimation offers advantages like frequent trips during peak hours, wide range network coverage, etc. However, the travel time characteristics of public transit buses are influenced by the transit characteristics like frequent acceleration, deceleration and stops due to bus stops besides their physical characteristics. Also, the sample size of public transit is less when compared to the total vehicle population. Thus mapping the bus travel time to stream travel time is a real challenge and this difficulty is more complex in traffic conditions like in India with its heterogeneity and lack of lane discipline. As a pilot study, a model based approach using the Kalman filtering technique to predict stream travel time from public transit is carried out in the present study. Since it is only a pilot study, only twowheeled vehicles have been considered as they constitute a major proportion in the study area. The prediction scheme is corroborated using field data collected by carrying GPS units in two-wheelers traveling along with the buses under consideration. The travel time estimates from the model were compared with the manually observed travel times and the results are encouraging.","PeriodicalId":117811,"journal":{"name":"2011 IEEE Intelligent Vehicles Symposium (IV)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126737381","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 : 2011-06-05DOI: 10.1109/IVS.2011.5940536
Frederik Sarholz, J. Klappstein, Fabian Diewald, J. Dickmann, B. Radig
This work presents three different quality functions for road course estimation using an imaging radar sensor. The quality functions work on gridmap data. A gridmap integrates each measurement in chronological order. Range estimation is found out to be necessary on country roads and a solution is introduced. All quality functions are evaluated using a huge set of data consisting of highways and country roads. The driven trajectory is taken as ground truth for the evaluation. The results show that on highways the quality functions perform nearly equal. However on country roads there are differences. The huge error reduction achieved by the range estimation is pointed out. At the end the quality function performing best is determined.
{"title":"Evaluation of different quality functions for road course estimation using imaging radar","authors":"Frederik Sarholz, J. Klappstein, Fabian Diewald, J. Dickmann, B. Radig","doi":"10.1109/IVS.2011.5940536","DOIUrl":"https://doi.org/10.1109/IVS.2011.5940536","url":null,"abstract":"This work presents three different quality functions for road course estimation using an imaging radar sensor. The quality functions work on gridmap data. A gridmap integrates each measurement in chronological order. Range estimation is found out to be necessary on country roads and a solution is introduced. All quality functions are evaluated using a huge set of data consisting of highways and country roads. The driven trajectory is taken as ground truth for the evaluation. The results show that on highways the quality functions perform nearly equal. However on country roads there are differences. The huge error reduction achieved by the range estimation is pointed out. At the end the quality function performing best is determined.","PeriodicalId":117811,"journal":{"name":"2011 IEEE Intelligent Vehicles Symposium (IV)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115182826","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 : 2011-06-05DOI: 10.1109/IVS.2011.5940463
M. Munz, K. Dietmayer
In this contribution, we present an overview of modeling techniques for sensory existence evidence using the Dempster Shafer Theory of Evidence (DST). Several modeling aspects are examined. The purpose of this approach is to enhance the detection performance of a sensor fusion system in terms of detection rate versus false alarm rate. An integrated state and existence estimation algorithm is used which directly incorporates the DST-based sensory information. The advantages of this algorithm are evaluated using a sensor fusion and tracking system based on a large database of real-world sensor data.
{"title":"Using Dempster-Shafer-based modeling of object existence evidence in sensor fusion systems for advanced driver assistance systems","authors":"M. Munz, K. Dietmayer","doi":"10.1109/IVS.2011.5940463","DOIUrl":"https://doi.org/10.1109/IVS.2011.5940463","url":null,"abstract":"In this contribution, we present an overview of modeling techniques for sensory existence evidence using the Dempster Shafer Theory of Evidence (DST). Several modeling aspects are examined. The purpose of this approach is to enhance the detection performance of a sensor fusion system in terms of detection rate versus false alarm rate. An integrated state and existence estimation algorithm is used which directly incorporates the DST-based sensory information. The advantages of this algorithm are evaluated using a sensor fusion and tracking system based on a large database of real-world sensor data.","PeriodicalId":117811,"journal":{"name":"2011 IEEE Intelligent Vehicles Symposium (IV)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115327391","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 : 2011-06-05DOI: 10.1109/IVS.2011.5940437
S. Geyer, Stefan Hakuli, H. Winner, Benjamin Franz, M. Kauer
Conduct-by-Wire (CbW) is a research project which breaks away from today's vehicle guidance by shifting the vehicle control task from a stabilization level to a conducting level. Instead of continuous stabilization on a designated trajectory - using the conventional control elements for manual steering, braking and accelerating - a Conduct-by-Wire vehicle is controlled by means of maneuver commands. By keeping the driver in the loop, the vehicle guidance is cooperatively shared between the driver and the automation. This article introduces an approach for the analysis of realizable automation levels and the design of a cooperative system behavior depending on the interaction concept between the human driver and the automation. Following a top-down approach, different driving scenarios are systematically analyzed as to the information needs that occur. This approach builds the basis for assessing the technical feasibility of a maneuver-based vehicle guidance concept based on the Conduct-by-Wire principle.
{"title":"Development of a cooperative system behavior for a highly automated vehicle guidance concept based on the Conduct-by-Wire principle","authors":"S. Geyer, Stefan Hakuli, H. Winner, Benjamin Franz, M. Kauer","doi":"10.1109/IVS.2011.5940437","DOIUrl":"https://doi.org/10.1109/IVS.2011.5940437","url":null,"abstract":"Conduct-by-Wire (CbW) is a research project which breaks away from today's vehicle guidance by shifting the vehicle control task from a stabilization level to a conducting level. Instead of continuous stabilization on a designated trajectory - using the conventional control elements for manual steering, braking and accelerating - a Conduct-by-Wire vehicle is controlled by means of maneuver commands. By keeping the driver in the loop, the vehicle guidance is cooperatively shared between the driver and the automation. This article introduces an approach for the analysis of realizable automation levels and the design of a cooperative system behavior depending on the interaction concept between the human driver and the automation. Following a top-down approach, different driving scenarios are systematically analyzed as to the information needs that occur. This approach builds the basis for assessing the technical feasibility of a maneuver-based vehicle guidance concept based on the Conduct-by-Wire principle.","PeriodicalId":117811,"journal":{"name":"2011 IEEE Intelligent Vehicles Symposium (IV)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122028351","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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