2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE)最新文献_第3页

Validation of a virtual test environment for C2X communication under radio jamming conditions 无线电干扰条件下C2X通信虚拟测试环境的验证

2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE) Pub Date : 2019-11-01 DOI: 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

引用次数: 0

Object-based sensor model for virtual testing of ADAS/AD functions 基于对象的ADAS/AD功能虚拟测试传感器模型

2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE) Pub Date : 2019-11-01 DOI: 10.1109/ICCVE45908.2019.8965071

S. Muckenhuber, Hannes Holzer, Jonas Rübsam, G. Stettinger

{"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}

引用次数: 18

Development of a Scenario Simulation Platform to Support Autonomous Driving Verification 支持自动驾驶验证的场景仿真平台的开发

2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE) Pub Date : 2019-11-01 DOI: 10.1109/ICCVE45908.2019.8964914

Ch. Pilz, Gerald Steinbauer, Markus Schratter, D. Watzenig

引用次数: 11

A Software Architecture for the Dynamic Path Planning of an Autonomous Racecar at the Limits of Handling 极限操纵下自主赛车动态路径规划的软件体系结构

2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE) Pub Date : 2019-11-01 DOI: 10.1109/ICCVE45908.2019.8965238

Johannes Betz, A. Wischnewski, Alexander Heilmeier, Felix Nobis, Leonhard Hermansdorfer, Tim Stahl, T. Herrmann, M. Lienkamp

引用次数: 25

Cloud-Based Vehicle Ride-Height Control 基于云的车辆行驶高度控制

2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE) Pub Date : 2019-11-01 DOI: 10.1109/ICCVE45908.2019.8964864

Konstantin Riedl, Thomas Einmüller, Andreas Noll, Andreas Allgayer, D. Reitze, M. Lienkamp

{"title":"Cloud-Based Vehicle Ride-Height Control","authors":"Konstantin Riedl, Thomas Einmüller, Andreas Noll, Andreas Allgayer, D. Reitze, M. Lienkamp","doi":"10.1109/ICCVE45908.2019.8964864","DOIUrl":"https://doi.org/10.1109/ICCVE45908.2019.8964864","url":null,"abstract":"We present a novel approach for a cloud-based ride-height control for vehicles equipped with an air suspension. The objective of this approach is to improve both efficiency and comfort, especially on single obstacles, by including vehicle-to-vehicle or vehicle-to-infrastructure (V2X) information on the road ahead in the control algorithm. The focus of this paper is the methodology of data processing on a cloud backend and includes three steps: pre-processing, clustering and allocation of streets to the clusters. In the first step, the database is reduced to obstacles relevant for driving comfort. The second step is to find clusters with a high density of obstacles on a road condition map. Finally, the probability of hitting an obstacle is calculated for each road in the area of a cluster, taking the characteristics and the topology of the road network into account. Example data is used to proof the functionality of the method. The proposed method seems to be a suitable approach for big data applications and might improve a vehicle ride-height control with regard to comfort and efficiency.","PeriodicalId":384049,"journal":{"name":"2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE)","volume":"30 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":"125991248","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}

引用次数: 1

Proof of concept for Scenario-in-the-Loop (SciL) testing for autonomous vehicle technology 自动驾驶汽车技术场景在环(SciL)测试的概念验证

2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE) Pub Date : 2019-11-01 DOI: 10.1109/ICCVE45908.2019.8965086

Z. Szalay, Mátyás Szalai, B. Tóth, T. Tettamanti, V. Tihanyi

引用次数: 11

Fault-tolerant environmental perception architecture for robust automated driving 鲁棒自动驾驶的容错环境感知体系结构

2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE) Pub Date : 2019-11-01 DOI: 10.1109/ICCVE45908.2019.8965112

Stephanie Grubmüller, G. Stettinger, M. Sotelo, D. Watzenig

引用次数: 2

COPADRIVe - A Realistic Simulation Framework for Cooperative Autonomous Driving Applications COPADRIVe——协作式自动驾驶应用的现实仿真框架

2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE) Pub Date : 2019-11-01 DOI: 10.1109/ICCVE45908.2019.8965161

Bruno Vieira, Ricardo Severino, E. Filho, A. Koubâa, E. Tovar

引用次数: 11

Camera Vignetting Model and its Effects on Deep Neural Networks for Object Detection 摄像机渐晕模型及其对深度神经网络目标检测的影响

2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE) Pub Date : 2019-11-01 DOI: 10.1109/ICCVE45908.2019.8965233

Kmeid Saad, Stefan-Alexander Schneider

{"title":"Camera Vignetting Model and its Effects on Deep Neural Networks for Object Detection","authors":"Kmeid Saad, Stefan-Alexander Schneider","doi":"10.1109/ICCVE45908.2019.8965233","DOIUrl":"https://doi.org/10.1109/ICCVE45908.2019.8965233","url":null,"abstract":"In this paper, we describe a new approach for synthetic image augmentation and its advantages in training Deep Neural Networks (DNNs) for object classification and localization. To address the need for a significant amount of data when training DNNs, for image-based ADAS functions, our method relies on virtually generated scenarios augmented via a physics-based camera model. The camera model implements various optical effects on ideal-synthetic images. For the scope of this paper, we illustrate the performance differences associated with the vignetting effect when training DNNs with and without image augmentation. We show that training on images altered by our camera vignetting model yield to a better performance than using ideal-synthetic images, additionally we illustrate the relationship between the network's performance results and the implemented effect (vignetting in this case). For a start, our results open the possibility for using camera models for training neural networks on synthetic data and pave the way toward further investigations on significant optical and image sensor effects to be modeled/implemented for performance enhancement during the training process. The approach is conducted and evaluated by training a DNN for car detection using the Karlsruhe Institute of Technology and Toyota Technological Institute at Chicago (KITTI) and Virtual KITTI (VKITTI) datasets.","PeriodicalId":384049,"journal":{"name":"2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE)","volume":"2 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":"129815424","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}

引用次数: 5

Accuracy Evaluation of Camera-based Vehicle Localization 基于摄像头的车辆定位精度评价

2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE) Pub Date : 2019-11-01 DOI: 10.1109/ICCVE45908.2019.8965230

Kai Cordes, Norman Nolte, N. Meine, Hellward Broszio

引用次数: 5