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当前公交车:准点晚点您

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从这里规划
Bike parking here74 places within 5 min · nearest: Rack for 1 bike, 步行 1 分钟Bike parking: OpenStreetMap, data as of 2026年6月1日. The walk is an estimate.
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Station details

Step-free route

目前无法确认通告的覆盖范围。下方保留的通告,其时间或来源数据可能未经确认。出行前,请向运营商核实。

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Buses from here

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In the station

  • Washroom nearby
  • Drinking water nearby

表现

服务运行情况 · 证据状态

Service at LANSDOWNE

Cancellations at this station

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.

Departure-board snapshot
40 listed departures · 10 live provider predictions

Server snapshot assembled 2026年11月4日 12:35; open Departures for a refreshed board. This is not a cancellation count.

Prediction agreement
67.2% 预测与时刻表相差在五分钟以内. 1,949 eligible provider predictions; arrivals not independently measured
本站公交车预测的可靠性

结论

本站公交车预测的可靠性

Early evidence: 6 of 20 weekdays with eligible final provider predictions. This updates hourly; more records will make the estimate steadier.

67.2% of final provider predictions within 5 minutes of the timetable, from 1,949 predictions over 6 weekdays. The lowest sampled hour is 17:00 at 50%.

Median predicted difference from the timetable: 3 min 晚点. At the 95th percentile: 15 min 晚点.

这是运营方对 OC Transpo 和 STO 车站常规公交到站的最终预测。实际到站情况没有经过独立核实。 快线 (200/500)、购物/社区线 (300)、活动线 (400) 和学校线 (600) 不在范围内,因为每一类都需要专门的衡量方法。 STO 的线路也已纳入,并按各自的类别分级:Rapibus 100、200、400 和 800 线计入,编号为 300 及以上的 STO 校车班次则不计入,与 OC Transpo 的 600 系列做法相同。每家运营方只按自己的服务来衡量,绝不与另一家比较。

We use the agency’s last prediction within ten minutes of each scheduled arrival. 6 weekdays with eligible predictions, 2026-10-28 to 2026-11-04. Within five minutes means the final prediction differs from the schedule by no more than five minutes.

Final provider predictions within five minutes of the timetable, by hour, 6 weekdays
  1. 00:00: 74.5% of final predictions within five minutes of the timetable, 47 predictions, typically 1.9 min late
  2. 01:00: 72.2% of final predictions within five minutes of the timetable, 36 predictions, typically 2 min late
  3. 02:00: not enough data
  4. 03:00: not enough data
  5. 04:00: not enough data
  6. 05:00: not enough data
  7. 06:00: 82.5% of final predictions within five minutes of the timetable, 57 predictions, typically 2.3 min late
  8. 07:00: 82.7% of final predictions within five minutes of the timetable, 110 predictions, typically 2 min late
  9. 08:00: 78.6% of final predictions within five minutes of the timetable, 140 predictions, typically 2.1 min late
  10. 09:00: 63.8% of final predictions within five minutes of the timetable, 138 predictions, typically 3.2 min late
  11. 10:00: 60.3% of final predictions within five minutes of the timetable, 126 predictions, typically 3.9 min late
  12. 11:00: 63.4% of final predictions within five minutes of the timetable, 131 predictions, typically 2.9 min late
  13. 12:00: 60% of final predictions within five minutes of the timetable, 110 predictions, typically 4 min late
  14. 13:00: 58.6% of final predictions within five minutes of the timetable, 116 predictions, typically 4.2 min late
  15. 14:00: 76.3% of final predictions within five minutes of the timetable, 93 predictions, typically 2.4 min late
  16. 15:00: 70.8% of final predictions within five minutes of the timetable, 106 predictions, typically 2.3 min late
  17. 16:00: 58.7% of final predictions within five minutes of the timetable, 104 predictions, typically 3.5 min late
  18. 17:00: 50% of final predictions within five minutes of the timetable, 126 predictions, typically 5 min late
  19. 18:00: 61.1% of final predictions within five minutes of the timetable, 131 predictions, typically 3.7 min late
  20. 19:00: 68.7% of final predictions within five minutes of the timetable, 99 predictions, typically 2.2 min late
  21. 20:00: 71.1% of final predictions within five minutes of the timetable, 76 predictions, typically 2.7 min late
  22. 21:00: 68.9% of final predictions within five minutes of the timetable, 61 predictions, typically 2.2 min late
  23. 22:00: 69.2% of final predictions within five minutes of the timetable, 52 predictions, typically 3 min late
  24. 23:00: 70.9% of final predictions within five minutes of the timetable, 55 predictions, typically 2.8 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
Findings
What时间已测量Scenario or next investigation
ProblemPredictions later than timetable09:00 to 11:003.5 min lateRunning time on the routes here
ProblemPredictions later than timetable12:00 to 14:004.1 min lateRunning time on the routes here
ProblemPredictions later than timetable16:00 to 19:004.1 min lateRunning time on the routes here
ProblemPredictions later than timetable22:003 min lateRunning time on the routes here
ProblemOne hour has a lower prediction match17:0050%Operations in that hour

How LANSDOWNE 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 20 route-hours. 0 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

60%

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

8of 20

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 20

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

3.8min

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: not measurable here

本网站记录的是某个站点每小时的延误中位数,没有百分位数,所以无法算出正常行程与糟糕行程之间的差距。这是我们自身测量方式的限制,不是对这个地方的结论。

Measurements

计算时间: · 方法: settled-arrivals-oc-sto-conventional-v5

Predictions later than timetable · 09:00 to 11:00
Median delay 3.5 min
Measured arrivals 264
准点 62.1%
Predictions later than timetable · 12:00 to 14:00
Median delay 4.1 min
Measured arrivals 226
准点 59.3%
Predictions later than timetable · 16:00 to 19:00
Median delay 4.1 min
Measured arrivals 361
准点 58.7%
Predictions later than timetable · 22:00
Median delay 3 min
Measured arrivals 52
准点 69.2%
One hour has a lower prediction match · 17:00
准点 50%
Other hours on time 69.2%
Measured arrivals 126
Station evidence and sources
评价或报告问题

Rider evidence

Community reports

Signals below are moderated community aggregates, not official operator notices or reliability scores.

You can report without signing in. Anonymous reports count a little less when we calculate public patterns. You can add an account after submitting.

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

当前车站时刻板,由导入的时刻表和每个班次可用的运营方预测汇总而成。

How it was produced

Platforms sharing the station stop code are grouped, scheduled trips are read from the current GTFS, and a live time is used only when the operator publishes a matching prediction.

数据日期

计算或汇总时间
样本
40 departures across 2 published platform records in the current four-hour board.
覆盖范围
10 departures have a published live prediction; 30 are timetable-only.

来源

请注意的局限

  • OC Transpo 在此处使用的数据源中不提供轨道交通的实时位置或预测,因此轨道交通时间仅为时刻表时间。
  • 该站点数据源没有发布完整的车站无障碍通道链、出入口或室内路径。
提出事实更正建议

Contains information licensed under the Open Government Licence – City of Ottawa.