An Assessment of The Effect of Contraflow Bus Lane on Rider Ship

Author: 張學孔 Shyue Koong Chang

陳信雄 Hsin-Hsiung Chen

From: Transportation Planning JournalVol.26 No.3

September 1997PP.577~592

指導教授：任維廉

葉家銘 Luke Yeh

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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

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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

Conclusion3

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

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Introduction

Two contraflow bus lane implemented since 1990.

Connect the old CBD(western area) to new developing area(eastern area).

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Contraflow Bus Lane

汽機車混合車道

汽機車混合車道

反向公車專用道

一般單向車道

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Problem For Time Dependent Data

Overestimated/Underestimated the effect of new method

- National Income

- Population

- Congestion

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Problem For Time Dependent Data

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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 periodbased 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).

Data Analysis

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37 57

Forecasting

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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

ARIMA:

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Forecasting

“Significant effect of the contraflow bus lane”

Forecast result for daily/monthly ridership

Forecasting – The Fisher Sign Test

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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

Forecasting

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Weakness of conventional method – the effect may be underestimated

Conclusions and Recommendations

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• 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

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“Thanks for listening.”