2022 IEEE Intelligent Vehicles Symposium (IV)最新文献

On Integrating POMDP and Scenario MPC for Planning under Uncertainty – with Applications to Highway Driving 不确定条件下规划中POMDP和情景MPC的集成及其在公路行驶中的应用

2022 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2022-06-05 DOI: 10.1109/iv51971.2022.9827005

Carl Hynén Ulfsjöö, Daniel Axehill

引用次数: 5

Assuring Responsible Driving of Autonomous Vehicles 确保自动驾驶汽车的负责任驾驶

2022 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2022-06-05 DOI: 10.1109/IV51971.2022.9827122

H. Schöner

引用次数: 1

Spatial Optimization in Spatio-temporal Motion Planning 时空运动规划中的空间优化

2022 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2022-06-05 DOI: 10.1109/iv51971.2022.9827125

Weize Zhang, P. Yadmellat, Zhiwei Gao

引用次数: 0

Agent-Based Autonomous Vehicle Simulation with Hardware Emulation in the Loop 基于智能体的自动驾驶汽车硬件仿真

2022 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2022-06-05 DOI: 10.1109/iv51971.2022.9827215

Mattis Hoppe, J. C. Kirchhof, Evgeny Kusmenko, Changho Lee, Bernhard Rumpe

{"title":"Agent-Based Autonomous Vehicle Simulation with Hardware Emulation in the Loop","authors":"Mattis Hoppe, J. C. Kirchhof, Evgeny Kusmenko, Changho Lee, Bernhard Rumpe","doi":"10.1109/iv51971.2022.9827215","DOIUrl":"https://doi.org/10.1109/iv51971.2022.9827215","url":null,"abstract":"Agent-based simulation is an important testing tool for the development of autonomous vehicle software. Simulators enable engineers to test autonomous driving behavior in virtual environments, which is cheaper, faster, and safer than using a physical vehicle. An important aspect of autonomous driving software is its real-time capability, i.e. its ability to react to unforeseen events and new sensor inputs within a very short amount of time to prevent accidents. In this paper, we present a modular agent-based simulator architecture, which not only simulates the physical behavior of the vehicle, controlled by the software under test, but also its electrical/electronic (E/E) network. In particular, each ECU is simulated using a hardware emulator, which enables us to test the software as if it is run on the actual target hardware. Furthermore, the hardware emulator estimates the execution delays for the software under test, which enables more realistic approximations of the real behavior. In an evaluation example we analyze empirically how well the timing estimates reflect the reality. We show that modeling the memory hierarchy and instruction decoding has a crucial effect on the precision of this estimation.","PeriodicalId":184622,"journal":{"name":"2022 IEEE Intelligent Vehicles Symposium (IV)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127460880","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

Towards Collision-Free Probabilistic Pedestrian Motion Prediction for Autonomous Vehicles 自动驾驶汽车无碰撞概率行人运动预测研究

2022 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2022-06-05 DOI: 10.1109/iv51971.2022.9827397

Kunming Li, Mao Shan, Stuart Eiffert, Stewart Worrall, E. Nebot

{"title":"Towards Collision-Free Probabilistic Pedestrian Motion Prediction for Autonomous Vehicles","authors":"Kunming Li, Mao Shan, Stuart Eiffert, Stewart Worrall, E. Nebot","doi":"10.1109/iv51971.2022.9827397","DOIUrl":"https://doi.org/10.1109/iv51971.2022.9827397","url":null,"abstract":"Autonomous vehicle navigation in shared pedestrian environments requires the ability to predict future crowd motion as well as understand human behaviour. However, most existing methods predict pedestrian future motion without considering potential collisions within the crowd. Furthermore, most current predictive models are tested on datasets that assume full observability of the crowd by relying on a top-down view, which does not reflect the real-world use case of autonomous vehicles due to the inherent limitations of on-board sensors such as visual occlusion. Inspired by prior works, we propose a pedestrian motion prediction model trained via contrastive learning, improving prediction accuracy as well as forecasting collision-free trajectories. Additionally, we propose a method for implementing a predictor using a multi-pedestrian probabilistic tracker, which fuses multiple on-board sensors to track pedestrians in 3D space. Through comprehensive experiments on both aerial view and driving datasets collected in a real-world urban environment, we show that our proposed method improves on state of art methods with better prediction accuracy and more socially acceptable prediction trajectories.","PeriodicalId":184622,"journal":{"name":"2022 IEEE Intelligent Vehicles Symposium (IV)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125854133","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: 0

MCS Analysis for 5G-NR V2X Sidelink Broadcast Communication 5G-NR V2X旁链路广播通信的MCS分析

2022 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2022-06-05 DOI: 10.1109/iv51971.2022.9827311

Jin Yan, Jérôme Härri

引用次数: 1

User Experience Evaluation of SAE Level 3 Driving on a Test Track 测试轨道上SAE 3级驾驶的用户体验评估

2022 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2022-06-05 DOI: 10.1109/iv51971.2022.9827224

Philipp Wintersberger, Shadan Sadeghian Borojeni, Clemens Schartmüller, Anna-Katharina Frison, A. Riener

引用次数: 0

Improved Vanishing Point Accuracy by Integrating Vehicle Detection and Segmentation 结合车辆检测和分割提高消失点精度

2022 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2022-06-05 DOI: 10.1109/iv51971.2022.9827411

Fumiaki Sato, T. Koshizen

引用次数: 0

HD Lane Map Generation Based on Trail Map Aggregation 基于路径地图聚合的高清车道地图生成

2022 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2022-06-05 DOI: 10.1109/iv51971.2022.9827144

P. Colling, Dennis Müller, M. Rottmann

引用次数: 2

A Sequential Decision-theoretic Method for Detecting Mobile Robots Localization Failures 移动机器人定位故障检测的顺序决策方法

2022 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2022-06-05 DOI: 10.1109/iv51971.2022.9827393

Liangxu Sun, Meng-Zhuo Liu, Huayi Zhan, Yingie Wu

{"title":"A Sequential Decision-theoretic Method for Detecting Mobile Robots Localization Failures","authors":"Liangxu Sun, Meng-Zhuo Liu, Huayi Zhan, Yingie Wu","doi":"10.1109/iv51971.2022.9827393","DOIUrl":"https://doi.org/10.1109/iv51971.2022.9827393","url":null,"abstract":"Many methods in mobile robotics usually utilize current sensor measurement to evaluate the localization performance of robots, for example in scan matching and particle filter methods. This immediately detecting methodology tend to cause a problem that a well-localization robot obtains a poor sensor measurement, the robot may mistake momentary observation noise for a localization failure. In this paper, we propose a new robot localization fault detection method for resolving this problem. We model robot localization fault detection as a sequential decision-making problem, where the decision of detecting a localization failure is based on a long-term sensor measurements. We employ two parameters of false-positive and false-negative observation error probabilities, which can eliminate the influence of noisy observations. Further, the proposed method derives Bayesian update equations for the integration of a long-term observations and presents an analytic formula representing the belief function of the reliability of localization results. Experimental studies validate the effectiveness of the proposed method.","PeriodicalId":184622,"journal":{"name":"2022 IEEE Intelligent Vehicles Symposium (IV)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114182022","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: 0