|
|
|
| Research on the Forming Mechanism and Technical Prediction Framework of the IPF of HSR |
| YAO Ming1, LI Feng2 |
| 1. China Railway Eryuan Engineering Group Co. Ltd, Chengdu, Sichuan 610031, China; 2. Tongji University, Shanghai200092, China |
|
|
|
|
Abstract Research purposes: In recent years, the economic accessibility models are usually applied in the predictions of the Induced Passenger Flow of the High Speed Railway (IPF of HSR) in referring to foreign evidential data .But the results cannot usually represent the actual induced passenger flow, and the consequent errors usually exceed. Based on the analyses of the concept, mechanism, characteristics, growth periods of IPF of HSR, this paper put forward the overall prediction framework of IPF of HSR respectively, in order to develop a set of methods and models both reasonable and feasible for the predictions of IPF of HSR.
Conclusions: The IPF of HSR should be classified as Short-term Induced Economic Passenger Flow from various potential trip demand (SIPF) and Long-term Induced Passenger Flow from growth (LIPF).The depends mainly on old and new potential trip demand, and the LIPF on the induced ecomic-growth of various SIPF cities along the corridor. The growing process of IPF of HSR includes the beginning term with rapid growth, medium term with stable growth, and final term with converging growth. It can be descriped as a S-shape logistic curve and should be forcasted by means of respective methods and models for SIPF and LIPF. In this paper, the prediction framework which combines tranditional prediction methods and MD models is put forward for SIPF, and another one based on economic accessibility models and the stable value-traffic ratio models is put forward for LIPF. (4) The research results can be used in the development of prediction software for IPF of HSR.
|
|
Received: 17 July 2013
|
|
|
|
|
|
[1] 高旭敏. 高速铁路客流量预测研究. 系统工程,1994,15(5):68-72.
Gao Xumin. A Predicting Research on the Passenger-flow in High-speed Railway [J]. Systems Engineering,1994(5):68-72.
[2] 刘娜. 客运专线客流预测理论及实际应用[D]. 北京:北京交通大学，2006.
Liu Na. Theory Study on Passenger Flow Forecasting of the Passenger Special Line and Its Application[D]. Beijing: Beijing Jiaotong University, 2006.
[3] 何静. 京津客运专线短期客流预测研究[D]. 北京:北京交通大学, 2006.
He Jing. Research on Short Term Prediction of Passenger Flow for Beijing-Tianjin Passenger only Line [D]. Beijing: Beijing Jiaotong University,2006.
[4] 任民. 铁路客运专线运量预测方法研究[J]. 铁道工程学报,2008(5):89-96.
Ren Min. Study on Method of the Predicting the Traffic Volume of Railway Passenger Dedicated Line[J]. Journal of Railway Engineering Society, 2008 (5):89-86.
[5] 李倩. 基于路网的高速铁路客流预测方法研究[D]. 北京:北京交通大学, 2011.
Li Qian. Research on Passenger Forecasting Method of High-speed Railway Based on Road Network[D]. Beijing: Beijing Jiaotong University,2011.
[6] 王伟. 铁路客运专线客流量预测的探讨[J]. 铁道运营技术, 2009(2):43-45.
Wang Wei. Discuss on the Volume Forecasting of the Railway Passenger Dedicated Line[J]. Railway Operation Technology,2009(2):43-45.
[7] PETER J. HILLS. What is Induced Traffic[J]. Transportation,1996(23):5-16.
[8] 宋雪梅, 蒋阳升, 云亮. MD模型的计算方法研究[J]. 交通运输工程与信息学报，2010(2):67-70.
Song Xuemei, Jiang Yangsheng, Yun Liang. Study on the Calculation Method of MD Forecast Model[J]. Journal of Transportation Engineering and Information, 2010(2):67-70.
[9] Reid Ewing, Allan Lichtenstein Induced Traffic and Induced Develop[C]. Prepared for the Chester County Planning Commission, 2002.
|
|
|
|
2014, Vol. 31 
