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一种车载端为主的城市路网当前与未来速度查询方法

韩京宇 王彦之 陈进 晏鑫鑫 张怡婷

韩京宇, 王彦之, 陈进, 晏鑫鑫, 张怡婷. 一种车载端为主的城市路网当前与未来速度查询方法[J]. 电子与信息学报. doi: 10.11999/JEIT240102
引用本文: 韩京宇, 王彦之, 陈进, 晏鑫鑫, 张怡婷. 一种车载端为主的城市路网当前与未来速度查询方法[J]. 电子与信息学报. doi: 10.11999/JEIT240102
HAN Jingyu, WANG Yanzhi, CHEN Jin, YAN Xinxin, ZHANG Yiting. A Mobile-Side-Dominant Method for Querying Present and Future Velocity on Urban Roads[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240102
Citation: HAN Jingyu, WANG Yanzhi, CHEN Jin, YAN Xinxin, ZHANG Yiting. A Mobile-Side-Dominant Method for Querying Present and Future Velocity on Urban Roads[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240102

一种车载端为主的城市路网当前与未来速度查询方法

doi: 10.11999/JEIT240102
基金项目: 江苏省重点研发计划(BE2022065-5)
详细信息
    作者简介:

    韩京宇:男,教授,研究方向为空间时态数据库、大数据与机器学习

    王彦之:男,硕士生,研究方向为机器学习与数据挖掘

    陈进:男,硕士生,研究方向为数据库系统与数据挖掘

    晏鑫鑫:男,硕士生,研究方向为时空数据管理与数据挖掘

    张怡婷:女,副教授,研究方向为大数据管理与网络安全

    通讯作者:

    韩京宇 jyhan@njupt.edu.cn

  • 中图分类号: TN929.53; TP311.132

A Mobile-Side-Dominant Method for Querying Present and Future Velocity on Urban Roads

Funds: Jiangsu Provincial Key Research & Development Plan (BE2022065-5)
  • 摘要: 城市智能交通管理中经常查询路段的当前和未来交通速度,该文提出一种车载边缘为主(VED)的城市路段速度查询和预测方法:车载端在速度低于一定阈值时,与其它车载端交换收集到的数据,并在本地构建轻量级的当前和历史速度索引,以支持当前速度查询。为了用尽可能少的模型支持速度预测,提出根据路段拓扑同构将路网划分成若干路段等价类,根据周期性时窗和路段等价类将整个时空划分成若干模型等价类,同一个模型等价类的路段在给定时窗呈现相似的交通运行模式。针对每个模型等价类,车载端和数据中心配合进行联邦学习,训练长短期记忆模型并存储在车载端,以响应车载端对附近未来交通状况的查询。每个车载端本地索引数据、本地响应查询,避免了查询响应延迟和通信拥塞;数据保存在车载端,而非集中存放,避免了安全攻击导致的隐私泄漏。
  • 图  1  路网上车载车载端数据交换的示例

    图  2  路段z的进入与引出路段

    图  3  时空立方2-1-3-SH(z,5)中的2-3-IC(z,5)

    图  4  进入路段同构的推导示例

    图  5  zz'的进入路段示例

    图  6  模拟数据集上gc随η的变化

    图  7  Geolife数据集上gc随η的变化

    图  8  Geolife上时隙范围对当前查询精度的影响(当前路段)

    图  9  Geolife上路段范围对当前查询精度的影响(当前时隙)

    图  10  Geolife上LSTM的数量随mn同构值的变化

    图  11  Geolife上LSTM的数量随β的变化

    图  12  未来查询精度随mn的变化(k=6)

    图  13  未来查询精度随时隙数k的变化(m=n=2)

    图  14  VED和Trellis时空覆盖率的对比

    图  15  不同时空范围下当前查询精度的对比

    2  inSphere

     输入:路网$ \mathrm{D}\mathrm{N} $,进入同构参数$ m $,目标路段$ \mathrm{t}\mathrm{s}\mathrm{g} $
     输出:路段$ \mathrm{t}\mathrm{s}\mathrm{g} $的$ m $跳距内的进入路段
     (1) 初始化队列$ Q $并将$ \mathrm{t}\mathrm{s}\mathrm{g} $入队
     (2) $ \mathrm{v}\mathrm{i}\mathrm{s}\mathrm{i}\mathrm{t}\left(\mathrm{t}\mathrm{s}\mathrm{g}\right),\mathrm{ }\mathrm{r}\mathrm{e}\mathrm{t}\leftarrow \varnothing $
     (3) while $ Q $非空 do
     (4)  $ \mathrm{s}\mathrm{g}\leftarrow \mathrm{Q}.\mathrm{p}\mathrm{o}\mathrm{p}\left(\cdot\right) $, $ \mathrm{r}\mathrm{e}\mathrm{t}\leftarrow \mathrm{r}\mathrm{e}\mathrm{t}\cup \left\{\mathrm{s}\mathrm{g}\right\} $
     (5)  if $ \left|\mathrm{s}\mathrm{g}\right| < m $ then
     (6)   获取$ \mathrm{s}\mathrm{g} $的所有直接前驱并将它们送入队列$ Q $
     (7)  end
     (8) end
    下载: 导出CSV

    1  同构路段划分

     输入:路网$ \mathrm{D}\mathrm{N} $,同构参数$ m $和$ n $,特征标签集合$ L $
     输出:路段的同构分组
     (1) 将$ \mathrm{D}\mathrm{N} $的第1个路段$ \mathrm{s}\mathrm{g} $压入栈$ \mathrm{S}\mathrm{K} $中
     (2) while $ \mathrm{S}\mathrm{K} $非空 do
     (3)  $ \mathrm{s}\mathrm{g}\leftarrow \mathrm{S}\mathrm{K}.\mathrm{p}\mathrm{o}\mathrm{p}\left(\cdot\right) $
     (4)  if $ \mathrm{s}\mathrm{g} $未被处理过 then
     (5)     $ \mathrm{v}\mathrm{i}\mathrm{s}\mathrm{i}\mathrm{t}\left(\mathrm{s}\mathrm{g}\right) $
     (6)    $ \mathrm{s}\mathrm{g}\mathrm{的}\mathrm{前}\mathrm{驱}\mathrm{路}\mathrm{段}\mathrm{i}\mathrm{n}\mathrm{s}\mathrm{g}\mathrm{s}\leftarrow \mathrm{i}\mathrm{n}\mathrm{S}\mathrm{p}\mathrm{h}\mathrm{e}\mathrm{r}\mathrm{e}\left(\mathrm{D}\mathrm{N},\mathrm{s}\mathrm{g},m\right) $
     (7)    $ \mathrm{s}\mathrm{g}\mathrm{的}\mathrm{后}\mathrm{继}\mathrm{路}\mathrm{段}\mathrm{o}\mathrm{u}\mathrm{t}\mathrm{s}\mathrm{g}\mathrm{s}\leftarrow \mathrm{o}\mathrm{u}\mathrm{t}\mathrm{S}\mathrm{p}\mathrm{h}\mathrm{e}\mathrm{r}\mathrm{e}\left(\mathrm{D}\mathrm{N},\mathrm{s}\mathrm{g},n\right) $
     (8)    $ \mathrm{h}\mathrm{c}\leftarrow \mathrm{f}\mathrm{e}\mathrm{a}\mathrm{t}\mathrm{u}\mathrm{r}\mathrm{e}\mathrm{C}\mathrm{o}\mathrm{d}\mathrm{e}\left(\mathrm{i}\mathrm{n}\mathrm{s}\mathrm{g}\mathrm{s},\mathrm{o}\mathrm{u}\mathrm{t}\mathrm{s}\mathrm{g}\mathrm{s},L\right) $
     (9)    根据$ \mathrm{h}\mathrm{c} $将$ \mathrm{s}\mathrm{g} $归类
     (10) end
     (11) if $ \mathrm{s}\mathrm{g} $的邻接路段$ w $未被分类过 then
     (12)    push$ \left(w\right) $
     (13) end
     (14) else
     (15)    $ \mathrm{s}\mathrm{g}=\mathrm{S}\mathrm{K}.\mathrm{p}\mathrm{o}\mathrm{p}\left(\cdot\right) $
     (16) end
    下载: 导出CSV

    3  响应未来交通查询

     输入:车载端的LSTM模型,对未来交通的查询$ \mathrm{f}\mathrm{q}\left(\mathrm{r}\mathrm{s},\mathrm{t}\mathrm{s}\right) $,当前
     速度索引PVI,恢复矩阵$ \bf{A}\bf{V} $
     输出:对应的时空单元$ \mathrm{S}\mathrm{G}\left(\mathrm{r}\mathrm{s},\mathrm{t}\mathrm{s}\right) $的预测速度
     (1) $ \mathrm{l}\mathrm{s}\mathrm{t}\mathrm{m}\leftarrow \mathrm{车}\mathrm{载}\mathrm{端}\mathrm{对}\mathrm{应}\mathrm{于}\mathrm{S}\mathrm{G}\left(\mathrm{r}\mathrm{s},\mathrm{t}\mathrm{s}\right)\mathrm{的}\mathrm{L}\mathrm{S}\mathrm{T}\mathrm{M}\mathrm{模}\mathrm{型} $
     (2) $ \mathrm{s}\mathrm{h}\leftarrow \mathrm{P}\mathrm{V}\mathrm{I}\mathrm{中}\mathrm{对}\mathrm{应}\mathrm{于} $mn(k–1)–SH(rs,ts–1)时空范围的样本概况
     (3) 预测集$ \mathrm{p}\mathrm{v}\leftarrow \varnothing $
     (4) for $ \mathrm{c}\mathrm{l}\in \mathrm{s}\mathrm{h} $ do
     (5)  $ \mathrm{v}\mathrm{v}\leftarrow \mathrm{计}\mathrm{算}\mathrm{c}\mathrm{l}\mathrm{中}\mathrm{的}\mathrm{速}\mathrm{度} $
     (6)  if $ \mathrm{c}\mathrm{l} $ 为空 then
     (7)   $ \mathrm{v}\mathrm{v}\leftarrow \bf{A}\bf{V}\left[\mathrm{r}\mathrm{s},\mathrm{t}\mathrm{s}\right]\mathrm{中}\mathrm{的}\mathrm{数}\mathrm{据} $
     (8)  end
     (9)  $ \mathrm{将}\mathrm{v}\mathrm{v}\mathrm{加}\mathrm{入}\mathrm{p}\mathrm{v} $
     (10) end
     (11) $ \mathrm{r}\mathrm{e}\mathrm{t}\leftarrow \mathrm{l}\mathrm{s}\mathrm{t}\mathrm{m}\left(\mathrm{p}\mathrm{v}\right) $
     (12) return ret
    下载: 导出CSV
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出版历程
  • 收稿日期:  2024-02-26
  • 修回日期:  2024-06-11
  • 网络出版日期:  2024-06-24

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