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Pengfei Zhou, Yuanqing Zheng, Mo Li -twohsien

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Presentation on theme: "Pengfei Zhou, Yuanqing Zheng, Mo Li -twohsien"— Presentation transcript:

1 Pengfei Zhou, Yuanqing Zheng, Mo Li -twohsien 2012.9.3
How Long to Wait?: Predicting Bus Arrival Time with Mobile Phone based Participatory Sensing Pengfei Zhou, Yuanqing Zheng, Mo Li -twohsien

2 Outline Introduction System design Evaluation Limitations Conclusion

3 Introduction Who will pay for this? $$$$$$$$$$$$
Why travelers do not like to travel by bus? Excessively long waiting time Existing methods to predict arrival time Timetable ( operating hours, time intervals, etc.) Special location tracking devices on buses Who will pay for this? $$$$$$$$$$$$

4 Objective Crowd-participated approach Energy friendly Sharing users
Querying users Backend server Energy friendly Microphone, accelerometer Mobile Phone

5 Main idea Map the bus routes to a space featured by sequences of nearby cellular towers

6 Challenges Bus Detection Bus Classification Information Assembling

7 System Design

8 Pre-processing Celltower Data
Top-3 strongest cell towers 300 meters apart

9 Example

10 Bus Detection Audio detection : short beep audio response
Peak at 1 kHz and 3kHz

11 Bus Detection Sliding window, size: 32 samples
Empirical threshold: three standard deviation

12 Bus Detection Accelerometer detection Bus v.s. Rapid train

13 Bus Detection Threshold Small: trains will be misdetected as buses
Big: miss detection of actual buses

14 Bus Classification Cell tower sequence matching
Smith-Waterman algorithm If ui = Cw ∈ Sj , ui and Sj are matching with each other, and mismatching otherwise

15 Bus Classification 𝑓 𝑠 𝑤 = 0.5 𝑤− w: rank of signal strenth penalty cost for mismatches : -0.5

16 Overlapped route Survey 50 bus route Range of cell tower:
meters threshold of celltower sequence length : 7

17 Cell tower Sequence Concatenation

18 Arrival Time Prediction

19 Evaluation

20 Experimental Methodology
Mobile phones Samsung Galaxy S2 i9100 HTC Desire Experiment environment 4 campus shuttle bus routes 2 SBS transit bus route 179 and 241

21 Bus Detection Performance

22 Bus vs. MRT Train False detection: Driving along straight routes late during night time

23 Bus Classification Performance

24 Arrival Time Prediction

25 Arrival Time Prediction

26 System Overhead Battery lifetime

27 Limitation and On-going Work
Alternative reference points Number of passengers First few bus stops Overlapped routes

28 Conclusion Present a crowd-participated bus arrival time prediction system using commodity mobile phones. Evaluate the system through a prototype system deployed on the Android platform with two types of mobile phones.

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