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A study of on integrated intercity travel demand model

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  • Yao, Enjian
  • Morikawa, Takayuki

Abstract

It is well reported that induced travel is an important component of travel demand. With improved transportation conditions, short run effects (e.g., route switches, mode switches, changes of destination, and new trip generation) and long term effects (e.g., change in household auto ownership, and spatial reallocation of activities) will be observed. This paper aims to develop an integrated intercity travel demand modelling system suitable for substantial changes in service level. The model utilizes combined estimation across multiple data sources such as SP, RP and aggregate data. This integrated intercity travel demand modelling system is characterized by an explicit intercity travel behavioural framework and its ability to capture induced travel. Intercity travel decisions are represented by a nested model structure, and an accessibility measure is introduced to capture short term induced travel. The paper also sketches a way to estimate induced travel resulting from long term changes (spatial reallocation of activities). As a case study, an integrated model including trip generation, destination choice, mode choice, and route choice is presented for an intercity high speed rail project planned in Japan, and short term induced travel elasticities with respect to travel cost, travel time, and etc. are also presented.

Suggested Citation

  • Yao, Enjian & Morikawa, Takayuki, 2005. "A study of on integrated intercity travel demand model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(4), pages 367-381, May.
    • Handle: RePEc:eee:transa:v:39:y:2005:i:4:p:367-381
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    References listed on IDEAS

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    1. Kitamura, Ryuichi & Fujii, Satoshi & Pas, Eric I., 1997. "Time-use data, analysis and modeling: toward the next generation of transportation planning methodologies," Transport Policy, Elsevier, vol. 4(4), pages 225-235, October.
    2. Noland, Robert B., 2001. "Relationships between highway capacity and induced vehicle travel," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(1), pages 47-72, January.
    3. Robert Noland & William Cowart, 2000. "Analysis of Metropolitan Highway Capacity and the growth in vehicle miles of travel," Transportation, Springer, vol. 27(4), pages 363-390, December.
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