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Transit Stop: CTA Tracker.

Transit Stop: CTA Tracker.

Kramer Concepts, LLC

Navigation免费v9.43
App Store
评分

4.6

31,866 条评分

星级

★★★★★

最近更新

2025年12月9日

发布日期

2011年1月20日

更新内容

v9.43

Fixed an issue where when a trip is cancelled ,the arrival times were showing as negative.

应用信息

开发者
Kramer Concepts, LLC
分类
Navigation
价格
免费
版本
9.43
App ID
414569920

简介

Transit Stop: CTA Tracker gives you quick and easy access to bus and train (‘L’) arrival time estimates for your favorite Chicago Transit Authority (CTA) stop. ------------ Features Include: ~ Apple Watch integration - view estimated arrival times for the stops you've saved on your wrist! ~ Estimated Bus & Train Arrival Times - Includes arrival time estimates in minutes (e.g. 4 minutes) and time (e.g. 12:14pm) along with the route name, bus ID or train run number, distance to stop, direction of travel, destination and a time stamp when the estimated arrival times were last refreshed. ~ Location Map - In addition to the list of estimated arrival times you can view bus and trains locations and route patterns on a map. ~ Individual Vehicle Tracking - View estimated arrival times for upcoming stops for specific bus or train vehicles by tapping the row of the estimated arrival time of interest. ~ Save Stops - Ability to save the stops you use everyday for quick and easy access while you're on the go. ~ View Multiple Routes - Toggle the estimated arrival times to display only your selected route or you can view all the routes that service a particular stop. ~ CTA Service Alerts – View CTA route service alerts for whichever bus route or train line you're tracking. ~ Refresh – Estimated arrival times can be manually refreshed giving you the flexibility to update the arrival times exactly when you need them. ~ Real Time Tracking Data - Bus routes, train lines, stops and estimated arrival times are all provided directly from the CTA bus and train tracking systems. ------------ Transit Stop is not affiliated with the CTA.

下载量预测

专业 · 预览

预估总下载量

2.4M1.6M4.6M
保守估计乐观估计

9K

低 / 月

13K

预估 / 月

24K

高 / 月

基于31,866 条评分
假设评分率1.4%
应用年龄186 个月

基于评分数量 ÷ 类别评分率估算,实际下载量误差可达 ±50%,与 Sensor Tower 方法一致。