2020 International Conference on Connected and Autonomous Driving (MetroCAD)最新文献_第2页

A Vision of Smart Traffic Infrastructure for Traditional, Connected, and Autonomous Vehicles 传统、联网和自动驾驶汽车的智能交通基础设施愿景

2020 International Conference on Connected and Autonomous Driving (MetroCAD) Pub Date : 2020-02-01 DOI: 10.1109/MetroCAD48866.2020.00008

S. Ranka, A. Rangarajan, L. Elefteriadou, Sivaramnakrishnan Srinivasan, Emmanuel Poasadas, Dan Hoffman, Raj Ponnulari, Jeremy Dilmore, Tom Byron

{"title":"A Vision of Smart Traffic Infrastructure for Traditional, Connected, and Autonomous Vehicles","authors":"S. Ranka, A. Rangarajan, L. Elefteriadou, Sivaramnakrishnan Srinivasan, Emmanuel Poasadas, Dan Hoffman, Raj Ponnulari, Jeremy Dilmore, Tom Byron","doi":"10.1109/MetroCAD48866.2020.00008","DOIUrl":"https://doi.org/10.1109/MetroCAD48866.2020.00008","url":null,"abstract":"This smart city traffic management approach seeks to use edge-based video-stream processing (using multicore and GPU processors) at intersections and in public vehicles (city buses, fire trucks, ambulances, school buses) to convert video data into space-time trajectories of individual vehicles and pedestrians that are transmitted to a cloud-based system. Key information is then synthesized in the cloud from them to create a real-time city-wide traffic palette. Real-time or offline processing both at the edge and the cloud will then be leveraged to optimize intersection operations, manage network traffic, identify near-collisions between various units of traffic, provide street parking information, and a host of other applications. Additional information such as weather and environment will also be leveraged. The use of edge-based real-time machine learning (ML) techniques and videostream processing has several significant advantages. (1) Because there is no need to store copious amounts of video (few minutes typically suffice for edge-based processing), it automatically addresses concerns of public agencies who do not want person-identifiable information to be stored for reasons of citizen privacy and legality. (2) The processing of the video stream at the edge will allow for the use of low bandwidth communication using wireline and wireless networks to a central system such as a cloud, resulting in a compressed and holistic picture of the entire city. (3) The real-time nature of processing enables a wide variety of novel transportation applications at the intersection, street, and system levels that were not possible hitherto, significantly impacting safety and mobility.","PeriodicalId":117440,"journal":{"name":"2020 International Conference on Connected and Autonomous Driving (MetroCAD)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122065727","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: 6

A Reliability Engineering Based Approach to Model Complex and Dynamic Autonomous Systems 基于可靠性工程的复杂动态自治系统建模方法

2020 International Conference on Connected and Autonomous Driving (MetroCAD) Pub Date : 2020-02-01 DOI: 10.1109/MetroCAD48866.2020.00020

T. Horeis, T. Kain, Julian-Steffen Müller, F. Plinke, J. Heinrich, Maximilian Wesche, Hendrik Decke

{"title":"A Reliability Engineering Based Approach to Model Complex and Dynamic Autonomous Systems","authors":"T. Horeis, T. Kain, Julian-Steffen Müller, F. Plinke, J. Heinrich, Maximilian Wesche, Hendrik Decke","doi":"10.1109/MetroCAD48866.2020.00020","DOIUrl":"https://doi.org/10.1109/MetroCAD48866.2020.00020","url":null,"abstract":"The development of system architectures, fulfilling a diverse set of technical and economic requirements, is known to be a challenging task when designing a new vehicle. The demands particularly concerning the system’s reliability, availability, and safety, are, however, remarkably increasing when glancing towards full vehicle autonomy, since this level of automatization excludes any takeover actions by passengers. To satisfy the requirements, a fail-operational system design that includes several fallback paths is required. Since classical approaches, which require adding fallback paths with various redundant and segregated components, contradict the harsh cost constraints prevailing in the automotive sector, further use of those approaches is not desirable. Hence, various new concepts are developed to dissolve this contradiction, i.e., reducing the number of hardware and software components, while on the other hand, keeping the level of reliability high. The problem, though, is that the systems resulting from applying those concepts are highly complex and can not be sufficiently analyzed with today’s tools regarding the availability, safety, and reliability of the system. Therefore, in this paper, we introduce AT-CARS (Analyzing Tool for Complex, Autonomous, and Reliable Systems), a tool capable of analyzing various complex systems architectures designed for autonomous vehicles. Our tool aims to support system engineers responsible for determining suitable system architectures that fulfill the expected safety requirements while satisfying the monetary conditions by providing measurements concerning availability, safety, and reliability. Those parameters are determined by a state-based Monte Carlo simulation, which supports dynamic failure management procedures.","PeriodicalId":117440,"journal":{"name":"2020 International Conference on Connected and Autonomous Driving (MetroCAD)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131171789","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: 3

Accurate Object Detection in Smart Transportation Using Multiple Cameras 基于多摄像头的智能交通目标精确检测

2020 International Conference on Connected and Autonomous Driving (MetroCAD) Pub Date : 2020-02-01 DOI: 10.1109/MetroCAD48866.2020.00011

Zhinan Qiao, Andrew Sansom, M. McGuire, Andrew Kalaani, Xu Ma, Qing Yang, Song Fu

引用次数: 0

MetroCAD 2020 Committees

2020 International Conference on Connected and Autonomous Driving (MetroCAD) Pub Date : 2020-02-01 DOI: 10.1109/metrocad48866.2020.00006

引用次数: 0

MetroCAD 2020 Breaker Page MetroCAD 2020断路器页面

2020 International Conference on Connected and Autonomous Driving (MetroCAD) Pub Date : 2020-02-01 DOI: 10.1109/metrocad48866.2020.00003

引用次数: 0

Cyber-Human-Physical Heterogeneous Traffic Systems for Enhanced Safety 提高安全性的网络-人-物理异构交通系统

2020 International Conference on Connected and Autonomous Driving (MetroCAD) Pub Date : 2020-02-01 DOI: 10.1109/MetroCAD48866.2020.00024

Yunyi Jia, B. Ayalew

引用次数: 0

MetroCAD 2020 Opinion

2020 International Conference on Connected and Autonomous Driving (MetroCAD) Pub Date : 2020-02-01 DOI: 10.1109/metrocad48866.2020.00005

引用次数: 0

MetroCAD 2020 Index MetroCAD 2019指数

2020 International Conference on Connected and Autonomous Driving (MetroCAD) Pub Date : 2020-02-01 DOI: 10.1109/metrocad48866.2020.00023

引用次数: 0

2D Map Estimation via Teacher-Forcing Unsupervised Learning 基于教师强迫无监督学习的二维地图估计

2020 International Conference on Connected and Autonomous Driving (MetroCAD) Pub Date : 2020-02-01 DOI: 10.1109/MetroCAD48866.2020.00022

Zhiliu Yang, Chen Liu

引用次数: 0

An intelligent driving simulation platform: architecture, implementation and application 一种智能驾驶仿真平台:架构、实现与应用

2020 International Conference on Connected and Autonomous Driving (MetroCAD) Pub Date : 2020-02-01 DOI: 10.1109/MetroCAD48866.2020.00019

Yongling Sun, Xiaosong Yang, Hai Xiao, H. Feng

{"title":"An intelligent driving simulation platform: architecture, implementation and application","authors":"Yongling Sun, Xiaosong Yang, Hai Xiao, H. Feng","doi":"10.1109/MetroCAD48866.2020.00019","DOIUrl":"https://doi.org/10.1109/MetroCAD48866.2020.00019","url":null,"abstract":"with the fast-growing advancements in highly automated driving technologies, cost-effective evaluation and validation of functional modules and full-stack driving system have become great challenges for automakers prior to the release of new intelligent vehicle models. Simulation based on high-fidelity rendering and physics engine has been widely used as a powerful tool to develop self-driving systems. From an OEM perspective, a flexible, extensible, and scalable virtual platform is proposed to integrate individual functional modules, support typical scenario libraries, and evaluate single functional algorithm or an entire domain controller system for rapid algorithm iterations and high-efficiency system testing. The platform demonstrates that a stand-alone machine can support up to 32-channel simulations in parallel depending on system resources, a semi-automatic method is introduced to generate a couple of scenarios based on map data and standard road network format, and typical perception algorithms are visualized and evaluated. In addition, such evaluation system can be deployed to the cloud to support large-scale simulations and testing automation.","PeriodicalId":117440,"journal":{"name":"2020 International Conference on Connected and Autonomous Driving (MetroCAD)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123140151","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