Pub Date : 2019-11-01DOI: 10.1109/ICCVE45908.2019.8965076
Jasmina Zubaca, M. Stolz, D. Watzenig
This paper contributes to the challenging field of reliable vehicle tracking as a pivotal part of automated driving. The Kalman filter is an optimal state estimator based on the assumption of an accurate dynamical model and known noise statistic. In order to achieve a fast, robust and efficient vehicle state estimation in the omnipresence of model imperfections and measurement noise, a synergetic combination of the Kalman filter and H∞ filter is proposed, making optimal usage of their advantages. The performance of the filters and their combination is analyzed throughout a sensor data fusion example. Based on the determination of the position and velocity of a vehicle, the improvements, but also the limits of the different approaches are discussed. Additionally, the possibility to detect sensor faults such as time-varying offsets by augmenting the state-space model is explained.
{"title":"A Novel Tuning Approach of the H∞ Filter for Longitudinal Tracking of Automated Vehicles","authors":"Jasmina Zubaca, M. Stolz, D. Watzenig","doi":"10.1109/ICCVE45908.2019.8965076","DOIUrl":"https://doi.org/10.1109/ICCVE45908.2019.8965076","url":null,"abstract":"This paper contributes to the challenging field of reliable vehicle tracking as a pivotal part of automated driving. The Kalman filter is an optimal state estimator based on the assumption of an accurate dynamical model and known noise statistic. In order to achieve a fast, robust and efficient vehicle state estimation in the omnipresence of model imperfections and measurement noise, a synergetic combination of the Kalman filter and H∞ filter is proposed, making optimal usage of their advantages. The performance of the filters and their combination is analyzed throughout a sensor data fusion example. Based on the determination of the position and velocity of a vehicle, the improvements, but also the limits of the different approaches are discussed. Additionally, the possibility to detect sensor faults such as time-varying offsets by augmenting the state-space model is explained.","PeriodicalId":384049,"journal":{"name":"2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116278563","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 : 2019-11-01DOI: 10.1109/ICCVE45908.2019.8965169
Indrasen Raghupatruni, Thomas Goeppel, Muhammed Atak, Julien Bou, T. Huber
Automotive cyber-physical systems are constantly increasing in complexity, especially due to innovations like sophisticated advanced driver assistance features. The increase in system complexity, in turn, gives rise to complex distributed software which creates challenges for verification. Front-loading tests that are regularly performed in prototype vehicles or Hardware-in-the-Loop (HiL) to simulation and Software-in-the-Loop (SiL) environments can be used to validate design decisions and to significantly reduce overall development costs. Novel Automated Driving features, and the Open Context problem, however, move the challenge from the state-to-the-art to a knowledge problem (know-what instead of know-how). The ISO/PAS 21448:2019 for Safety of the Intended Functionality (SOTIF) acknowledges this change but no guidance is provided to the industry to making verification processes ready for operating vehicles in an Open Context environment that may require functional changes during the useful life of a vehicle. Since verification with HiL or vehicles will be all but impractical, in this paper we provide insights into the design of credible SiL environments that address functional and non-functional verification and validation concerns of software related automotive system in a continuous life-cycle. With the help of a use-case we demonstrate the significance of the novel approach compared to traditional automotive industry methods.
{"title":"Empirical Testing of Automotive Cyber-Physical Systems with Credible Software-in-the-Loop Environments","authors":"Indrasen Raghupatruni, Thomas Goeppel, Muhammed Atak, Julien Bou, T. Huber","doi":"10.1109/ICCVE45908.2019.8965169","DOIUrl":"https://doi.org/10.1109/ICCVE45908.2019.8965169","url":null,"abstract":"Automotive cyber-physical systems are constantly increasing in complexity, especially due to innovations like sophisticated advanced driver assistance features. The increase in system complexity, in turn, gives rise to complex distributed software which creates challenges for verification. Front-loading tests that are regularly performed in prototype vehicles or Hardware-in-the-Loop (HiL) to simulation and Software-in-the-Loop (SiL) environments can be used to validate design decisions and to significantly reduce overall development costs. Novel Automated Driving features, and the Open Context problem, however, move the challenge from the state-to-the-art to a knowledge problem (know-what instead of know-how). The ISO/PAS 21448:2019 for Safety of the Intended Functionality (SOTIF) acknowledges this change but no guidance is provided to the industry to making verification processes ready for operating vehicles in an Open Context environment that may require functional changes during the useful life of a vehicle. Since verification with HiL or vehicles will be all but impractical, in this paper we provide insights into the design of credible SiL environments that address functional and non-functional verification and validation concerns of software related automotive system in a continuous life-cycle. With the help of a use-case we demonstrate the significance of the novel approach compared to traditional automotive industry methods.","PeriodicalId":384049,"journal":{"name":"2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124594013","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 : 2019-11-01DOI: 10.1109/ICCVE45908.2019.8964945
Helmut Brunner, Xuelei Zhi, Matthias Mietschnig, Stephen Jones, Su Zhou, Gerald Steinbauer, M. Hirz
Based on a flexible prototype vehicle and object recognition algorithms from robotic science, the present research aims at new approaches in the development of autonomous driving vehicles. An advanced prototype vehicle, driven by four independent hub motors that provide maneuverability and driving function far beyond automotive standards, serves as the basis for investigations. Enhanced know-how from robotic disciplines comprises sensor technology, navigation algorithms and the autonomous vehicle control system. With the integrated research vehicle, several autonomous driving testing scenarios are carried out to enable comprehensive evaluation and potential assessment of different technologies and development approaches in view of future R&D activities. The study shows, that: A)4WID-4WIS (four wheel independent driving and four wheel independent steering) electric vehicle is much more flexible and efficient to achieve superior performance in aspect of dynamics and drive ability than traditional vehicles. B)Object recognition and path planning algorithms in the robotics science can be implemented in the development of autonomous driving techniques and have achieved convincing results. C)This research ensures a decoupling of the basic vehicle control from the overall robotic path planning and following system. A commonly defined interface enables the adaption of the overall control system to various vehicle types.
{"title":"Research on Autonomous Driving based on a Highly Flexible Prototype Vehicle","authors":"Helmut Brunner, Xuelei Zhi, Matthias Mietschnig, Stephen Jones, Su Zhou, Gerald Steinbauer, M. Hirz","doi":"10.1109/ICCVE45908.2019.8964945","DOIUrl":"https://doi.org/10.1109/ICCVE45908.2019.8964945","url":null,"abstract":"Based on a flexible prototype vehicle and object recognition algorithms from robotic science, the present research aims at new approaches in the development of autonomous driving vehicles. An advanced prototype vehicle, driven by four independent hub motors that provide maneuverability and driving function far beyond automotive standards, serves as the basis for investigations. Enhanced know-how from robotic disciplines comprises sensor technology, navigation algorithms and the autonomous vehicle control system. With the integrated research vehicle, several autonomous driving testing scenarios are carried out to enable comprehensive evaluation and potential assessment of different technologies and development approaches in view of future R&D activities. The study shows, that: A)4WID-4WIS (four wheel independent driving and four wheel independent steering) electric vehicle is much more flexible and efficient to achieve superior performance in aspect of dynamics and drive ability than traditional vehicles. B)Object recognition and path planning algorithms in the robotics science can be implemented in the development of autonomous driving techniques and have achieved convincing results. C)This research ensures a decoupling of the basic vehicle control from the overall robotic path planning and following system. A commonly defined interface enables the adaption of the overall control system to various vehicle types.","PeriodicalId":384049,"journal":{"name":"2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128331473","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 : 2019-11-01DOI: 10.1109/ICCVE45908.2019.8965171
T. Agliullin, V. Ivanov, M. Kaddari, Vincenzo Ricciardi, D. Savitski, K. Augsburg
This work is dedicated to brake-based stability control system for electric vehicles. The aim of the research is to compare four control methods: first-order sliding mode (FOSM), second-order sliding mode (SOSM), integral sliding mode (ISM), and variable-structure PI (VSPI). For this purpose, an evaluation methodology based on the weighted control performance index (WCPI) was developed. The comparative analysis is conducted with an experimentally validated vehicle model in IPG CarMaker® and MATLAB/Simulink co-simulation environment including high-fidelity vehicle subsystems' models.
{"title":"Sliding Mode Methods in Electric Vehicle Stability Control","authors":"T. Agliullin, V. Ivanov, M. Kaddari, Vincenzo Ricciardi, D. Savitski, K. Augsburg","doi":"10.1109/ICCVE45908.2019.8965171","DOIUrl":"https://doi.org/10.1109/ICCVE45908.2019.8965171","url":null,"abstract":"This work is dedicated to brake-based stability control system for electric vehicles. The aim of the research is to compare four control methods: first-order sliding mode (FOSM), second-order sliding mode (SOSM), integral sliding mode (ISM), and variable-structure PI (VSPI). For this purpose, an evaluation methodology based on the weighted control performance index (WCPI) was developed. The comparative analysis is conducted with an experimentally validated vehicle model in IPG CarMaker® and MATLAB/Simulink co-simulation environment including high-fidelity vehicle subsystems' models.","PeriodicalId":384049,"journal":{"name":"2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121687008","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 : 2019-11-01DOI: 10.1109/ICCVE45908.2019.8965226
A. Aksjonov, Halil Beglerovic, Michael Hartmann, Shriram C. Jugade, Cyrano Vaseur
Transportation systems are invariably burdened with dynamically changing environmental conditions and ill-defined human factor. To raise ground vehicle safety on a new supreme level and to boost autonomous vehicles development driver-vehicle-environment cooperation is inevitable. In this paper, an overview of several existing driver-vehicle-environment integration methods with purpose of vehicle safety enhancement are stressed. Five unique and fundamentally different solutions are proposed, which have common similarity: the solutions are accomplished with machine learning algorithms. The methods aim at modelling drivers' or vehicles' behaviour with reasonable prediction accuracy under various complex scenarios. All five solutions are developed in individual projects in a framework of a continuous interdisciplinary European network ITEAM. The aim of the paper is to underline significant benefit of man-machine-environment integration in vehicle safety systems by exploiting fairly received tremendous attention machine learning methods.
{"title":"On Driver-Vehicle-Environment Integration for Multi-Actuated Ground Vehicles Safety Advancement: An Overview of the Interdisciplinary Training Network in Multi-Actuated Ground Vehicles","authors":"A. Aksjonov, Halil Beglerovic, Michael Hartmann, Shriram C. Jugade, Cyrano Vaseur","doi":"10.1109/ICCVE45908.2019.8965226","DOIUrl":"https://doi.org/10.1109/ICCVE45908.2019.8965226","url":null,"abstract":"Transportation systems are invariably burdened with dynamically changing environmental conditions and ill-defined human factor. To raise ground vehicle safety on a new supreme level and to boost autonomous vehicles development driver-vehicle-environment cooperation is inevitable. In this paper, an overview of several existing driver-vehicle-environment integration methods with purpose of vehicle safety enhancement are stressed. Five unique and fundamentally different solutions are proposed, which have common similarity: the solutions are accomplished with machine learning algorithms. The methods aim at modelling drivers' or vehicles' behaviour with reasonable prediction accuracy under various complex scenarios. All five solutions are developed in individual projects in a framework of a continuous interdisciplinary European network ITEAM. The aim of the paper is to underline significant benefit of man-machine-environment integration in vehicle safety systems by exploiting fairly received tremendous attention machine learning methods.","PeriodicalId":384049,"journal":{"name":"2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131604609","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 : 2019-11-01DOI: 10.1109/ICCVE45908.2019.8965211
M. Nabhan, Marc Schoenauer, Y. Tourbier, H. Hage
Self-driving cars and advanced driver-assistance systems are perceived as a game-changer in the future of road transportation. However, their validation is mandatory before industrialization; testing every component should be assessed intensively in order to mitigate potential failures and avoid unwanted problems on the road. In order to cover all possible scenarios, virtual simulations are used to complement real-test driving and aid in the validation process. This paper focuses on the validation of the command law during realistic virtual simulations. Its aim is to detect the maximum amount of failures while exploring the input search space of the scenarios. A key industrial restriction, however, is to launch simulations as little as possible in order to minimize computing power needed. Thus, a reduced model based on a random forest model helps in decreasing the number of simulations launched. It accompanies the algorithm in detecting the maximum amount of faulty scenarios everywhere in the search space. The methodology is tested on a tracking vehicle use case, which produces highly effective results.
{"title":"Optimizing coverage of simulated driving scenarios for the autonomous vehicle","authors":"M. Nabhan, Marc Schoenauer, Y. Tourbier, H. Hage","doi":"10.1109/ICCVE45908.2019.8965211","DOIUrl":"https://doi.org/10.1109/ICCVE45908.2019.8965211","url":null,"abstract":"Self-driving cars and advanced driver-assistance systems are perceived as a game-changer in the future of road transportation. However, their validation is mandatory before industrialization; testing every component should be assessed intensively in order to mitigate potential failures and avoid unwanted problems on the road. In order to cover all possible scenarios, virtual simulations are used to complement real-test driving and aid in the validation process. This paper focuses on the validation of the command law during realistic virtual simulations. Its aim is to detect the maximum amount of failures while exploring the input search space of the scenarios. A key industrial restriction, however, is to launch simulations as little as possible in order to minimize computing power needed. Thus, a reduced model based on a random forest model helps in decreasing the number of simulations launched. It accompanies the algorithm in detecting the maximum amount of faulty scenarios everywhere in the search space. The methodology is tested on a tracking vehicle use case, which produces highly effective results.","PeriodicalId":384049,"journal":{"name":"2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123160769","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 : 2019-11-01DOI: 10.1109/ICCVE45908.2019.8965071
S. Muckenhuber, Hannes Holzer, Jonas Rübsam, G. Stettinger
A novel generic sensor model is introduced for testing and validation of ADAS/AD (Advanced Driver Assistance Systems/Autonomous Drive) functions. The model converts an incoming object list into a sensor specific object list and is suitable for all ADAS/AD perception sensors operating on object level. The field of view of the sensor is represented by a two dimensional polygon, that can be defined by a set of points. A simple ray-tracing method is applied to simulate coverage by objects. The model allows multiple range specifications for a single sensor depending on object type and classification capabilities. A look-up table is used to convert the object class definitions of the virtual environment into the class definitions of the considered sensor. Additional object parameters that are detected by the sensor may be included. False negative and false positive detections are generated by probabilistic functions. The parametrisation procedure of the sensor model is explained and depicted in an example using the data sheet of the Radar Continental ARS404. The model's capability to simulate a complete sensor set is demonstrated with the sensor set of the Renault Zoe that was used to collect the nuScenes data set. The sensor model is integrated into a virtual test-bed using Vires VTD and Open Simulation Interface.
{"title":"Object-based sensor model for virtual testing of ADAS/AD functions","authors":"S. Muckenhuber, Hannes Holzer, Jonas Rübsam, G. Stettinger","doi":"10.1109/ICCVE45908.2019.8965071","DOIUrl":"https://doi.org/10.1109/ICCVE45908.2019.8965071","url":null,"abstract":"A novel generic sensor model is introduced for testing and validation of ADAS/AD (Advanced Driver Assistance Systems/Autonomous Drive) functions. The model converts an incoming object list into a sensor specific object list and is suitable for all ADAS/AD perception sensors operating on object level. The field of view of the sensor is represented by a two dimensional polygon, that can be defined by a set of points. A simple ray-tracing method is applied to simulate coverage by objects. The model allows multiple range specifications for a single sensor depending on object type and classification capabilities. A look-up table is used to convert the object class definitions of the virtual environment into the class definitions of the considered sensor. Additional object parameters that are detected by the sensor may be included. False negative and false positive detections are generated by probabilistic functions. The parametrisation procedure of the sensor model is explained and depicted in an example using the data sheet of the Radar Continental ARS404. The model's capability to simulate a complete sensor set is demonstrated with the sensor set of the Renault Zoe that was used to collect the nuScenes data set. The sensor model is integrated into a virtual test-bed using Vires VTD and Open Simulation Interface.","PeriodicalId":384049,"journal":{"name":"2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131609826","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 : 2019-11-01DOI: 10.1109/ICCVE45908.2019.8964938
M. Tarkowski, Danny Behnecke, M. Mahmod, M. Rzymowski, L. Kulas, K. Nyka, M. Borawski, P. Kwapisiewicz, Wojciech Piechowski, G. Temme, S. Khan
In this paper, we propose a novel car-2-x communication security testing methodology in the physical layer of wireless systems. The approach is dedicated to automated testing of autonomous vehicles and it is essential for such complex systems operation, especially with regard to safety and security issues. It is based on scenario-driven testing in virtual and real test environments created from collected or simulated data. The presented approach is dedicated for reducing the time and costs of testing and generates a number of potential situations to examine the autonomous system behavior with regard to the wireless communication security. The conducted test results compare some exemplary scenarios, which involve 802.11p C2X communication in presence of intentional interferences, which are realized in different configurations: SiL, HiL and in-field measurements.
{"title":"Validation of a virtual test environment for C2X communication under radio jamming conditions","authors":"M. Tarkowski, Danny Behnecke, M. Mahmod, M. Rzymowski, L. Kulas, K. Nyka, M. Borawski, P. Kwapisiewicz, Wojciech Piechowski, G. Temme, S. Khan","doi":"10.1109/ICCVE45908.2019.8964938","DOIUrl":"https://doi.org/10.1109/ICCVE45908.2019.8964938","url":null,"abstract":"In this paper, we propose a novel car-2-x communication security testing methodology in the physical layer of wireless systems. The approach is dedicated to automated testing of autonomous vehicles and it is essential for such complex systems operation, especially with regard to safety and security issues. It is based on scenario-driven testing in virtual and real test environments created from collected or simulated data. The presented approach is dedicated for reducing the time and costs of testing and generates a number of potential situations to examine the autonomous system behavior with regard to the wireless communication security. The conducted test results compare some exemplary scenarios, which involve 802.11p C2X communication in presence of intentional interferences, which are realized in different configurations: SiL, HiL and in-field measurements.","PeriodicalId":384049,"journal":{"name":"2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133999953","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 : 2019-11-01DOI: 10.1109/ICCVE45908.2019.8965096
Yildirim Dülgar, M. Menth, H. Rehborn, Micha Koller
We study vehicle trajectories at the onset and existence of traffic congestion and reveal its microscopic features on separate highway lanes. Drone observations of microscopic data of moving vehicles have been made available on three-lane road segments of German highways. Based on these detailed empirical traffic data we reveal heterogeneity and complexity of congested traffic and discuss its consequences. E.g., to perform a safe and comfortable driving behavior by driver assistance systems or automated vehicles lane-level traffic states should be adapted. A congested and dense traffic state only on the left lane of a three-lane highway could be a serious danger. Moreover, we propose an empirical method to calculate local traffic densities that could be used to warn vehicles in advance about high preceding densities. We leverage that concept to study a local traffic jam and discuss its lane-level properties. We reveal the heterogeneity of high local density structures on separate highway lanes.
{"title":"Heterogeneity of Microscopic Congested Traffic Data Based on Drone Measurements","authors":"Yildirim Dülgar, M. Menth, H. Rehborn, Micha Koller","doi":"10.1109/ICCVE45908.2019.8965096","DOIUrl":"https://doi.org/10.1109/ICCVE45908.2019.8965096","url":null,"abstract":"We study vehicle trajectories at the onset and existence of traffic congestion and reveal its microscopic features on separate highway lanes. Drone observations of microscopic data of moving vehicles have been made available on three-lane road segments of German highways. Based on these detailed empirical traffic data we reveal heterogeneity and complexity of congested traffic and discuss its consequences. E.g., to perform a safe and comfortable driving behavior by driver assistance systems or automated vehicles lane-level traffic states should be adapted. A congested and dense traffic state only on the left lane of a three-lane highway could be a serious danger. Moreover, we propose an empirical method to calculate local traffic densities that could be used to warn vehicles in advance about high preceding densities. We leverage that concept to study a local traffic jam and discuss its lane-level properties. We reveal the heterogeneity of high local density structures on separate highway lanes.","PeriodicalId":384049,"journal":{"name":"2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123613379","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 : 2019-11-01DOI: 10.1109/ICCVE45908.2019.8965126
Sidney Körper, Roland Herberth, F. Gauterin, O. Bringmann
Data-driven technologies, such as predictive maintenance, become increasingly important to today's automotive industry due to advancements of connected cars and Over-the-Air technologies. A data source that has barely been used in the literature so far is diagnostic data, which is obtained by sending requests to the electronic control units of a vehicle. Diagnostic data can be collected cost-effectively and is already available on a large scale to car manufacturers today. However, the use of diagnostic data is associated with some difficulties. The set of measured variables differs greatly between different vehicles of the same type due to different configurations and therefore differences in the electronic control units. In this contribution, we show how diagnostic data can be harmonized for the use of data-driven modeling. An heuristic three-step procedure is introduced to identify similar measured variables. Finally, our approach is verified on a synthetic data set. Future data-driven technologies are able to use larger and more cost-efficient data sets this way.
{"title":"Harmonizing Heterogeneous Diagnostic Data of a Vehicle Fleet for Data-Driven Analytics","authors":"Sidney Körper, Roland Herberth, F. Gauterin, O. Bringmann","doi":"10.1109/ICCVE45908.2019.8965126","DOIUrl":"https://doi.org/10.1109/ICCVE45908.2019.8965126","url":null,"abstract":"Data-driven technologies, such as predictive maintenance, become increasingly important to today's automotive industry due to advancements of connected cars and Over-the-Air technologies. A data source that has barely been used in the literature so far is diagnostic data, which is obtained by sending requests to the electronic control units of a vehicle. Diagnostic data can be collected cost-effectively and is already available on a large scale to car manufacturers today. However, the use of diagnostic data is associated with some difficulties. The set of measured variables differs greatly between different vehicles of the same type due to different configurations and therefore differences in the electronic control units. In this contribution, we show how diagnostic data can be harmonized for the use of data-driven modeling. An heuristic three-step procedure is introduced to identify similar measured variables. Finally, our approach is verified on a synthetic data set. Future data-driven technologies are able to use larger and more cost-efficient data sets this way.","PeriodicalId":384049,"journal":{"name":"2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122331778","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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