Ward 7 · Ottawa · Councillor: Theresa Kavanagh
Bay
Bay: 75.5% of predictions within five minutes.
- 五分钟内
- 75.5%
- 选区内的站点
- 288
- 途经的路线
- 37
- 已取消的班次
- 尚未提供
- 尚未按选区统计
最慢的地方
- 80% 及以上 13
- 60 至 80% 7
- 低于 60% 0
- 数据太少 17
途经该选区的线路,按预测误差在五分钟内的占比排列。每条线路的结果涵盖整条线路。
本选区内的线路
| 线路 | 5 分钟内 | 已取消 | 拥挤程度 |
|---|---|---|---|
| 11 | 63.9% | 未公布 | 未公布 |
| 51 | 65.7% | 未公布 | 未公布 |
| 81 | 70.4% | 未公布 | 未公布 |
| 57 | 73.3% | 未公布 | 未公布 |
| 73 | 76.0% | 未公布 | 未公布 |
| 62 | 76.1% | 未公布 | 未公布 |
| 158 | 77.4% | 未公布 | 未公布 |
| 85 | 81.3% | 未公布 | 未公布 |
Cancellations and crowding are not published per route yet. 17 routes with too little data or a different service purpose are left out.
所有线路及其来源一页简报
本选区的可打印摘要，供市议会和社区会议使用。内容包括相同的数字、通俗易懂的方法说明和注明日期的来源。
What can be verified in Bay?
包括到站预测、已导入的时刻表和列车通知。每项都会显示各自的来源。
提供方预测一致性
75.5%
的合格预测与时刻表相差不超过五分钟
- 对比情况
- Rank 15 of 22 · median 78.4%
服务情况,依据已导入的时刻表
- 辖区站点的预定行程
- 尚未提供
- 线路
- 37
- 铁路线路
- 0
此边界内的当前服务
此边界内的实时公交车在“地图”标签页上。
预测指标、时刻表清单和方法
服务运行情况 · 证据状态
本选区站点的取消次数
Not publishableNo zero or missed trip is inferred when exact stop calls cannot be published.
本选区内站点的预测
75.5% within five minutes of the timetable across 471,805 eligible final provider predictions and 20 weekdays. These are not verified physical arrivals.
Predictions do not prove physical arrival.
需要检查的路线
数据时段不可用如有,这些是为该选区服务的线路的全线车辆位置匹配结果。它们不能确定漏掉的行程是否在此选区内,也不能证明行程已取消。每次比较都使用同一线路和同一时段的预定行程。
所关联的公交线路没有可比较的全线路位置记录。
Scheduled calls, sources and limits
37 routes · 288 stops. 这是时刻表清单，不是已提供的行程。
本选区站点的取消次数
Local count unavailable
The exact stop-call lookup did not finish within this page’s time budget. No zero, cancellation, or missed call is inferred.
结论
What would fix transit here
Worked out from the routes that serve this ward. Each item names the route, when it happens, and what would change it.
13 of 20 show repeated provider predictions later than the timetable, consistent with a possible scheduled running-time shortfall. A scheduler should test that scenario against operations; labour, fleet, recovery and transfer impacts are not established here.
Worst here: route 11, predictions later than timetable 11:00 to 22:00, 3.8 min late.
Best here: route 67, predictions consistently close to timetable, 95%.
20 of 20 routes here had something measurable to report.
- 00:00: 90.3% of final predictions within five minutes of the timetable, 16,902 predictions, typically 0.7 min late
- 01:00: 90.4% of final predictions within five minutes of the timetable, 6,738 predictions, typically 0.7 min late
- 02:00: 83.7% of final predictions within five minutes of the timetable, 4,520 predictions, typically 0.9 min late
- 03:00: 91.3% of final predictions within five minutes of the timetable, 2,715 predictions, typically 0.1 min late
- 04:00: 93.8% of final predictions within five minutes of the timetable, 6,703 predictions, typically 0.4 min late
- 05:00: 90.6% of final predictions within five minutes of the timetable, 17,395 predictions, typically 1.1 min late
- 06:00: 89.5% of final predictions within five minutes of the timetable, 39,029 predictions, typically 1.1 min late
- 07:00: 84.1% of final predictions within five minutes of the timetable, 51,445 predictions, typically 1.4 min late
- 08:00: 77.2% of final predictions within five minutes of the timetable, 54,341 predictions, typically 1.9 min late
- 09:00: 79.6% of final predictions within five minutes of the timetable, 53,595 predictions, typically 1.7 min late
- 10:00: 83% of final predictions within five minutes of the timetable, 53,953 predictions, typically 1.3 min late
- 11:00: 81.9% of final predictions within five minutes of the timetable, 53,140 predictions, typically 1.6 min late
- 12:00: 81% of final predictions within five minutes of the timetable, 53,424 predictions, typically 1.8 min late
- 13:00: 79.1% of final predictions within five minutes of the timetable, 52,652 predictions, typically 1.7 min late
- 14:00: 80.1% of final predictions within five minutes of the timetable, 54,215 predictions, typically 1.6 min late
- 15:00: 73.1% of final predictions within five minutes of the timetable, 56,788 predictions, typically 2.2 min late
- 16:00: 66.5% of final predictions within five minutes of the timetable, 59,589 predictions, typically 2.9 min late
- 17:00: 66.4% of final predictions within five minutes of the timetable, 59,409 predictions, typically 3 min late
- 18:00: 74.1% of final predictions within five minutes of the timetable, 55,090 predictions, typically 2.1 min late
- 19:00: 79.3% of final predictions within five minutes of the timetable, 45,797 predictions, typically 1.8 min late
- 20:00: 81% of final predictions within five minutes of the timetable, 41,276 predictions, typically 1.8 min late
- 21:00: 82.7% of final predictions within five minutes of the timetable, 38,763 predictions, typically 1.7 min late
- 22:00: 82.6% of final predictions within five minutes of the timetable, 33,041 predictions, typically 1.5 min late
- 23:00: 85.9% of final predictions within five minutes of the timetable, 25,383 predictions, typically 1.2 min late
- 90% or more of predictions within five minutes
- 80 to 90% of predictions within five minutes
- under 80% of predictions within five minutes
- not enough data
| What | 时间 | 已测量 | Scenario or next investigation |
|---|---|---|---|
| ProblemPredictions later than timetable11518157627473828758666015313 routes | 11:00 to 22:00 … 05:00 | 3.8 min late … 4.5 min late | More running time |
| ProblemWide prediction spread111 routes | 18:00 to 20:00 | 24.9 min swing | Operations, not the timetable |
| StrengthPredictions consistently close to timetable671532 routes | 05:00 to 22:00 · 08:00, 10:00, 11:00, 12:00, 13:00, 14:00, 15:00, 16:00, 17:00, 18:00, 19:00 | 95% · 98% | Keep what works |
| ProblemOne hour has a lower prediction match5774628287735860669 routes | 16:00 … 18:00 | 48% … 54% | Operations, not the timetable |
| StrengthObserved-position lower bound75116357586760731536615811 routes | All measured hours | 100% | Keep what works |
| CaveatCoverage gap8862748587615181829 routes | All measured hours | 99% … 100% | More observation, not a service change |
How BAY is doing
这些指标把反复出现的延误与运营方到达预测的波动区分开来。它们可为规划人员和运营人员提供可探讨的问题，但不能确定原因，也不能证明公共汽车何时到达。每个数字都显示其线路时段样本。
Measured over 371 route-hours. 8 more were observed too thinly to count, and are excluded rather than assumed good.
排班
如果多次出现预测晚点，可能说明时刻表值得检查。在决定是否调整运行时间之前，请先查看实际到达和发车记录。
- 谁能解决
- 服务规划人员
- 费用
- 在车队、人力、恢复和换乘的影响测试完成之前，成本暂不可知。
与时刻表接近的预测
86.8%
线路小时中，符合条件的到站预测中位数早于实际不到一分钟，且晚于实际不到三分钟。
多次预计晚点的线路时段
49of 371
路线小时数：符合条件的到达预测中位数至少晚点三分钟。请对照实际运营记录检查运行时间。
有提前预测的线路小时数
0of 371
线路-小时中，符合条件的到站预测中位数至少提前一分钟的部分。这并不能证明公交车提前发车。
典型预测延误
3.6min
在被标记的线路时段中，预测延误的典型中位数。这不是可直接加到时刻表上的经过验证的数值。
运营
到站预测差异很大，需要进行运营审查。交通状况、调度、上车和时刻表设计都可能有影响。仅凭这些预测，无法确定原因或解决办法。
- 谁能解决
- 运营部门，通常还有道路本身
- 费用
- 在查明运营原因并确定补救办法之前，费用暂不可用。
预测间隔低于二十分钟
99.5%
第95百分位的合格预测值比中位数晚不到二十分钟的线路-小时。
预测误差大的线路时段
2of 371
第95百分位的合格预测比中位数晚至少二十分钟的线路时段。需要调查原因。
典型预测偏差
24.9min
在被标记的线路时段中,第 95 百分位符合条件的预计值与中位数之间的典型差距。
服务情况,依据已导入的时刻表
本选区的按时刻表公共交通、服务商预测与时刻表的一致程度,以及公共服务。
提供方预测一致性
75.5% of eligible provider predictions were within five minutes of the timetable. 356,001 of 471,805 settled trip-stop predictions at stops inside this ward matched that range across 20 weekdays with feed evidence, from 2026年10月1日 to 2026年11月2日. These are provider predictions, not independently observed arrivals.
3 partial-capture days not counted.
- 五分钟内的预测
- 356,001
- 符合条件的班次站点预测
- 471,805
- 已观察天数
- 20 weekdays
对比情况
Ranked 15 of 22 measured wards. 2.9 points below the city median of 78.4%.
Highest: ward 22 at 84.9%. Lowest: ward 21 at 60.3%.
只有数据达到发布标准的选区才会参与排名。每个选区使用相同的时间范围和相同的方法。
哪些线路需要进一步审查
20 of the 37 routes serving this ward have enough provider-prediction evidence to compare. Lowest timetable agreement first.
- 11Open route 63.9%五分钟内的预测
179,770 eligible predictions across the whole route
- 51Open route 65.7%五分钟内的预测
95,833 eligible predictions across the whole route
- 81Open route 70.4%五分钟内的预测
146,796 eligible predictions across the whole route
- 57Open route 73.3%五分钟内的预测
101,177 eligible predictions across the whole route
- 73Open route 76.0%五分钟内的预测
39,090 eligible predictions across the whole route
- 62Open route 76.1%五分钟内的预测
87,300 eligible predictions across the whole route
- 158Open route 77.4%五分钟内的预测
177 eligible predictions across the whole route
- 85Open route 81.3%五分钟内的预测
211,284 eligible predictions across the whole route
- 74Open route 83.3%五分钟内的预测
83,104 eligible predictions across the whole route
- 88Open route 83.6%五分钟内的预测
164,195 eligible predictions across the whole route
17 more routes here are not ranked: school, express, shopper or event service, whose schedule result does not compare the same way.
需要调查的车辆可见性
需要调查的车辆可见性
当前摘要使用七天的数据。对于每条路线，您也可以打开昨天、最近 7 天或最近 30 天的数据，查看日期、预定班次、被排除的数据缺口，以及每个观察到的公共车辆编号。没有记录不能证明车辆故障，也不能证明是运营方的决定。
可见度摘要暂时无法使用。下方的路线链接仍可使用。
服务该选区的线路
37 scheduled routesMap & current service
Current service inside this boundary
Scheduled lines, stops, and observed buses share one map. Select a route or vehicle for details.
Evidence & sources
Imported municipal polygon · 33 boundary vertices · City of Ottawa ward boundaries · imported 2026年8月4日
Public amenity record for this ward
公共洗手间和饮用水
Choose a category to check which location details are available.公共洗手间（市政数据） 13
公开的选区快照只发布了该选区的数量,没有发布各个具体地点。我们没有编造任何地点。
饮用水（市政府数据） 6
公开的选区快照只发布了该选区的数量,没有发布各个具体地点。我们没有编造任何地点。
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Evidence included with the draft
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- https://otranspo.ca/zh-Hans/city/wards/7
- Sources and time
- Sources and time: open the linked report for its source records and published or imported timestamps.
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评价或报告问题
Rider evidence
Community reports
Signals below are moderated community aggregates, not official operator notices or reliability scores.
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Report a specific problem
- Graffiti
- Cleanliness
- Lighting
- Snow or ice
- Washroom unavailable
- Water unavailable
- Accessibility barrier
- Other issue
Emergency: call 9-1-1. Check official OC Transpo or STO notices before travelling.
公共事务数据简报
本选区报告背后的身份信息、边界、联系方式、服务范围和数据日期,汇集在一起,方便引用本页时不丢失相关说明。
- 市
- 安大略省渥太华市
- 地理单位
- Official City of Ottawa municipal ward 7: BAY
- 边界和版本时间
- City ward layer · effective 未公布 · imported 2026年8月4日
- 官方市政联系方式
- 相关的预定服务
- 37 public route records with a stop inside this boundary · operators: OC Transpo
- 公交数据的年份
- Timetable import: 未公布 · reliability window: 2026年10月1日 – 2026年11月2日
选区边界、线路清单、目的地列表、人口数量或就业人数只能提供城市背景。这些数值单独都无法衡量乘客需求、家庭出行影响、换乘或每日到访人数。
渥太华的选区是市政选区。它们不是加蒂诺的选区。两种边界体系的结果不能互换。
本页的佐证数据打开定义、方法、来源、日期、覆盖范围和已知限制。
这里显示的内容
按选区列出的清单，包括预定的公交服务、公共洗手间、饮水点，以及选区内站点符合条件的 OC Transpo 最终运营方预测。
How it was produced
Current imported records are assigned by point-in-polygon to the sourced ward boundary. Reliability uses one eligible final provider prediction per trip, stop, and service date in the latest 28 completed service days. Within five minutes is measured against the timetable, not a physical arrival. Publication requires 20 weekdays with prediction evidence and 500 eligible predictions.
数据日期
- 已导入
- 计算或汇总时间
- 样本
- 471,805 eligible settled provider predictions across 20 weekdays with prediction evidence support the reliability result.
- 方法或数据版本
- ward-counts-v1 + ward-stop-settled-arrivals-purpose-aware-v3
- 来源校验和
- ward-reliability:0257ab089f8990b6297bdce0603ab38161c582bdb034f494f14772610df3dd5d
来源
请注意的局限
- 数量只反映边界内已发布的设施清单，不代表服务质量，也不代表每个地址都能使用。
- 可靠性涵盖 OC Transpo 提供方在按地理位置划分的站点给出的最终预测。实际到达情况没有被独立测量。轨道交通以及没有合格预测数据的行程不包含在内。
- 无法获得的数量会保持为无法获得。不会改成零。
我们如何测量
对于选区内各站点的每个班次、站点和服务日期，我们保留 OC Transpo 最后一条符合条件的预测，并与时刻表对比。两者相差不超过五分钟时，计为五分钟以内。这不代表实际到达。
统计时段为最近 28 个已完成的运营日。只有在有 20 个工作日的预测数据和 500 条合格预测时，才会公布结果。路线结果涵盖整条路线，而不只是选区内的部分。
Read the full methodContains information licensed under the Open Government Licence – City of Ottawa.