In-vehicle Distributed Time-critical Data Stream Management System for Advanced Driver Assistance
In-vehicle Distributed Time-critical Data Stream Management System for Advanced Driver Assistance
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DOI：
10.2197/ipsjjip.25.107
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
Akihiro Yamaguchi;Yousuke Watanabe;Kenya Sato;Y. Nakamoto;Y. Ishikawa;S. Honda;H. Takada
中科院分区：
文献类型：
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作者：
Akihiro Yamaguchi;Yousuke Watanabe;Kenya Sato;Y. Nakamoto;Y. Ishikawa;S. Honda;H. Takada
：数据流管理系统 (DSMS) 适合以高输入速率和低延迟管理和处理连续数据。对于包括自动驾驶在内的高级驾驶员辅助，嵌入式系统使用各种车载传感器数据以及来自车辆外部的通信。因此，为此类系统开发的软件必须能够处理大量数据和复杂的处理。我们开发了一个使用 DSMS 集成和管理汽车嵌入式系统中数据的平台。然而，由于分布在嵌入式系统车载网络中的汽车数据处理对时间要求严格，并且必须可靠以降低传感器噪声，因此很难识别满足这些要求的传统 DSMS。为了应对这些新挑战，我们开发了汽车嵌入式 DSMS (AEDSMS)。在设计需要时间关键性的汽车系统时，该 AEDSMS 将高级查询预编译为可执行查询计划。数据流处理适当分布在车载网络中，同时还应用实时调度和传感器数据融合来满足时限并增强传感器数据的可靠性。本文的主要贡献如下：（1）我们对将 DSMS 引入汽车领域时所面临的挑战有了清晰的认识； (2) 我们提出了 AEDSMS 来应对这些挑战； (3) 我们在运行时评估 AEDSMS 以实现高级驾驶员辅助。
: Data stream management systems (DSMSs) are suitable for managing and processing continuous data at high input rates with low latency. For advanced driver assistance including autonomous driving, embedded systems use a variety of onboard sensor data with communications from outside the vehicle. Thus, the software developed for such systems must be able to handle large volumes of data and complex processing. We develop a platform that integrates and manages data in an automotive embedded system using a DSMS. However, because automotive data processing, which is distributed in in-vehicle networks of the embedded system, is time-critical and must be reliable to reduce sensor noise, it is di ffi cult to identify conventional DSMSs that meet these requirements. To address these new challenges, we develop an automotive embedded DSMS (AEDSMS). This AEDSMS precompiles high-level queries into executable query plans when designing automotive systems that demand time-criticality. Data stream processing is distributed in in-vehicle networks appropriately, where real-time scheduling and senor data fusion are also applied to meet deadlines and enhance the reliability of sensor data. The main contributions of this paper are as follows: (1) we establish a clear understanding of the challenges faced when introducing DSMSs into the automotive field; (2) we propose an AEDSMS to tackle these challenges; and (3) we evaluate the AEDSMS during run-time for advanced driver assistance.