China Safety Science Journal ›› 2024, Vol. 34 ›› Issue (7): 178-185.doi: 10.16265/j.cnki.issn1003-3033.2024.07.0153
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HU Zhenghua1(), ZHOU Jibiao2,3, GUO Xu1, MA Changxi4
Received:
2024-01-15
Revised:
2024-04-16
Online:
2024-07-28
Published:
2025-01-28
CLC Number:
HU Zhenghua, ZHOU Jibiao, GUO Xu, MA Changxi. Allocation of traffic police resources based on queuing theory[J]. China Safety Science Journal, 2024, 34(7): 178-185.
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URL: http://www.cssjj.com.cn/EN/10.16265/j.cnki.issn1003-3033.2024.07.0153
Table 1
Index names and their interpretations
类目 | 变量名 | 含义 |
---|---|---|
索引 | S | 网格(即交警中队的管辖区域) |
I | 网格的总数 | |
i | 网格S的索引 | |
J | 时间窗内网格Si总共发生的 交通事故数量 | |
j | 在网格Si内发生事故的索引 | |
k | 在网格Si内派遣警员的索引 | |
参数 | 网格Si需要派遣的警员数 | |
网格Si内发生的第j起事故 | ||
L | 警员当前所在的位置 | |
/(km·h-1) | 警员的平均行驶速度 | |
P(A,B)/km | 地点A与B之间的最短路径 | |
第k个警员在网格Si内累 计处理的交通事故数 | ||
N+ | 非零自然数集合 | |
Q | 需要处理的交通事故队列 | |
T/h | 处理一起事故的平均时间 | |
T(M)/h | 处理“物损事故”所需的时间 | |
T(C)/h | 处理“伤亡事故”所需的时间 | |
T( ,k)/h | 网格Si内第k个警员处理完第c 起事故还需要的时间 |
Table 3
Comparision of traffic police dispatch plans between queuing theory and traditional model
序 号 | 发生时间 | 出警的警 员编号 | 所属 网格 | 出行距离/m | 到达时间 | 结束时间 | 等待时间 | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
(a) | (b) | (a) | (b) | (a) | (b) | (a) | (b) | (a) | (b) | ||||||||
1 | 7:10:00 | 1 | 1 | 网格1 | 899 | 899 | 7:11:04 | 7:11:04 | 7:31:04 | 7:31:04 | 0:01:04 | 0:01:04 | |||||
2 | 7:20:00 | 2 | 2 | 网格1 | 7 075 | 7 075 | 7:28:29 | 7:28:29 | 7:38:29 | 7:38:29 | 0:08:29 | 0:08:29 | |||||
3 | 7:24:00 | 3 | 3 | 网格1 | 2 633 | 2 633 | 7:27:09 | 7:27:09 | 7:37:09 | 7:37:09 | 0:03:09 | 0:03:09 | |||||
4 | 7:38:00 | 6 | 7 | 网格4 | 6 336 | 6 336 | 7:45:36 | 7:45:36 | 7:55:36 | 7:55:36 | 0:07:36 | 0:07:36 | |||||
5 | 7:49:00 | 8 | 9 | 网格3 | 2 441 | 2 441 | 7:51:55 | 7:51:55 | 8:01:55 | 8:01:55 | 0:02:55 | 0:02:55 | |||||
6 | 8:00:00 | 4 | 5 | 网格2 | 6 487 | 6 487 | 8:07:47 | 8:07:47 | 8:17:47 | 8:17:47 | 0:07:47 | 0:07:47 | |||||
7 | 8:01:00 | 9 | 10 | 网格3 | 2 895 | 2 895 | 8:04:28 | 8:04:28 | 8:14:28 | 8:14:28 | 0:03:28 | 0:03:28 | |||||
8 | 8:04:00 | 6 | 8 | 网格4 | 3 226 | 5 852 | 8:07:52 | 8:11:01 | 8:17:52 | 8:21:01 | 0:03:52 | 0:07:01 | |||||
9 | 8:04:00 | 8 | 11 | 网格3 | 2 602 | 3 312 | 8:07:07 | 8:07:58 | 8:17:07 | 8:17:58 | 0:03:07 | 0:03:58 | |||||
10 | 8:10:00 | 5 | 6 | 网格5 | 4 651 | 4 651 | 8:15:35 | 8:15:35 | 8:25:35 | 8:25:35 | 0:05:35 | 0:05:35 | |||||
11 | 8:15:00 | 9 | 9 | 网格3 | 4 860 | 3 630 | 8:20:50 | 8:19:21 | 8:30:50 | 8:29:21 | 0:05:50 | 0:04:21 | |||||
12 | 8:20:00 | 8 | 10 | 网格3 | 2 338 | 3 410 | 8:22:48 | 8:24:05 | 8:32:48 | 8:34:05 | 0:02:48 | 0:04:05 | |||||
13 | 8:22:00 | 1 | 1 | 网格1 | 5 955 | 5 635 | 8:29:09 | 8:28:45 | 8:39:09 | 8:38:45 | 0:07:09 | 0:06:45 | |||||
14 | 8:24:00 | 6 | 7 | 网格4 | 1 106 | 5 479 | 8:25:19 | 8:30:34 | 8:45:19 | 8:50:34 | 0:01:19 | 0:06:34 | |||||
15 | 8:30:00 | 2 | 2 | 网格1 | 4 945 | 2 633 | 8:35:56 | 8:33:09 | 8:45:56 | 8:43:09 | 0:05:56 | 0:03:09 | |||||
16 | 8:32:00 | 9 | 11 | 网格3 | 7 494 | 4 116 | 8:40:59 | 8:36:56 | 8:50:59 | 8:46:56 | 0:08:59 | 0:04:56 | |||||
17 | 8:35:00 | 7 | 8 | 网格4 | 4 504 | 4 504 | 8:40:24 | 8:40:24 | 8:50:24 | 8:50:24 | 0:05:24 | 0:05:24 | |||||
18 | 8:36:00 | 3 | 3 | 网格1 | 3 920 | 4 781 | 8:40:42 | 8:41:44 | 8:50:42 | 8:51:44 | 0:04:42 | 0:05:44 | |||||
19 | 8:40:00 | 1 | 4 | 网格1 | 4 213 | 1 633 | 8:45:03 | 8:41:57 | 8:55:03 | 8:51:57 | 0:05:03 | 0:01:57 | |||||
20 | 8:40:00 | 4 | 5 | 网格2 | 15 | 6 503 | 8:40:01 | 8:47:48 | 8:50:01 | 8:57:48 | 0:00:01 | 0:07:48 | |||||
21 | 8:46:00 | 5 | 6 | 网格5 | 1 850 | 5 353 | 8:48:13 | 8:52:25 | 8:58:13 | 9:02:25 | 0:02:13 | 0:06:25 | |||||
— | 出行总 路程 | 80 445 | 90 258 | — | 平均等 待时间 | 0:04:36 | 0:05:09 | ||||||||||
提升占 比/% | — | 10.87 | 提升占 比/% | — | 10.68 |
[1] |
唐炉亮, 阚子涵, 任畅, 等. 利用GPS轨迹的转向级交通拥堵精细分析[J]. 测绘学报, 2019, 48(1): 75-85.
doi: 10.11947/j.AGCS.2019.20170448 |
doi: 10.11947/j.AGCS.2019.20170448 |
|
[2] |
姬浩, 王永东, 李佩, 等. 事故车辆影响下的城市三车道道路交通流仿真[J]. 中国安全科学学报, 2021, 31(3): 112-120.
doi: 10.16265/j.cnki.issn1003-3033.2021.03.016 |
doi: 10.16265/j.cnki.issn1003-3033.2021.03.016 |
|
[3] |
|
[4] |
|
[5] |
杨洋, 王文慧, 吴先宇, 等. 高速公路非常规交通事故研究综述[J]. 应用基础与工程科学学报, 2024, 32(3): 601-626.
|
|
|
[6] |
王婷婷. 智慧交通背景下成都市公共出行服务的问题与对策研究[D]. 成都: 电子科技大学, 2022.
|
|
|
[7] |
王启超. 当前警务改革背景下辅警管理研究[D]. 济南: 山东大学, 2022.
|
|
|
[8] |
|
[9] |
|
[10] |
李志恒, 赵宁宇, 谭墍元. 考虑信号灯影响的交通警力巡逻模型研究[J]. 交通运输系统工程与信息, 2015, 15(4): 118-122,128.
|
|
|
[11] |
|
[12] |
胡子峰, 陈洋, 郑秀娟, 等. 空地异构机器人系统协作巡逻路径规划方法[J]. 控制理论与应用, 2022, 39(1): 48-58.
|
|
|
[13] |
doi: 10.1080/01605682.2018.1434401 |
[14] |
|
[15] |
|
[16] |
胡立伟, 吕一帆, 赵雪亭, 等. 基于数据驱动的交通事故伤害程度影响因素及其耦合关系研究[J]. 交通运输系统工程与信息, 2022, 22(5): 117-124,134.
|
|
|
[17] |
缪明月, 曹玉锋, 李强, 等. 大数据背景下道路交通应急警力资源科学配置的路径与方法[J]. 中国人民公安大学学报:自然科学版, 2022, 28(4): 39-46.
|
|
|
[18] |
杨文臣, 周燕宁, 田毕江, 等. 基于聚类分析和SVM的二级公路交通事故严重度预测[J]. 中国安全科学学报, 2022, 32(5): 163-169.
doi: 10.16265/j.cnki.issn1003-3033.2022.05.1263 |
doi: 10.16265/j.cnki.issn1003-3033.2022.05.1263 |
|
[19] |
|
[20] |
|
[21] |
|
[22] |
|
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