1. An Assessment of The Effect of Contraflow Bus Lane on Rider Ship 指導教授：任維廉 葉家銘 Luke Yeh 1

2. Who am I ? 交大運輸與物流管理學系 四年級 France Business School – Poitiers Campus 交換學生 葉家銘, Luke Yeh What I love – 音樂、電影、籃球 、爵士鼓、圍棋 2

3. Outline  介紹 Introduction  資料時間相依問題 Problem for Time Dependent Data  干預分析 Intervention Analysis  資料分析 Data Analysis  預測 Forecasting  結論 Conclusion 3

4. Introduction 2.2 million trips per day, buses as people’s important commuting mode in Taipei metropolitan area. Taipei is facing serious traffic congestion problem. Transportation Planning System 4

5. Introduction Two contraflow bus lane implemented since 1990. Connect the old CBD(western area) to new developing area(eastern area). 5

6. Contraflow Bus Lane 汽機車混合車 道 反向 公車專用道 一般單向車道 6

7. Problem For Time Dependent Data Overestimated/Underestimated the effect of new method - National Income - Population - Congestion 7

8. Problem For Time Dependent Data 8

9. Intervention Analysis Step 1- Obtain the data before occurrence of event (B1,B2….Bn) Step 2- Assume the event will not occur and forecast for the next m period based on B1…..Bn (An+1,An+2….An+m) Step 3- Obtain the actual time series data (Cn+1…Cn+m) Step 4- Compare the two time series data from step 2 and 3. A change to a procedure, or law, or policy, etc. that is intended to change the values of the series. We want to estimate how much the intervention has changed the series (if at all).

10. Data Analysis 10 37 57

11. Forecasting 11 The Box-Jenkins ARIMA time series model is very useful for forecasting series of ridership. ACF – Autocorrelation Function PACF – Partial Autocorrelation Function Preliminary Process – Diagnosing, identification, Estimation, Forecasting Preliminary Process – Diagnosing, identification, Estimation, Forecasting ARIMA:

12. 12 Forecasting “Significant effect of the contraflow bus lane” Forecast result for daily/monthly ridership

13. Forecasting – The Fisher Sign Test 13 Data before March 1992 under 0.05 significance level Data before July 1993 under 0.15 significance level After the contraflow bus lane is implemented, the bus ridership has significantly increased

14. Forecasting 14 Weakness of conventional method – the effect may be underestimated

15. Conclusions and Recommendations 15 Ridership of bus lane increased about 28.9% after the contraflow bus lane is implemented. The conventional method neglecting the time variation may underestimate the ridership. The increase on ridership may become steady Travel speed, service frequency, and operating cost warrant further analysis

16. 16 “Thanks for listening.”