High-speed railway and other transportations of attracted radius location by passenger travel cost model

2021 ◽  
Vol 14 (10) ◽  
Author(s):  
Yanli Li ◽  
Lifen Li ◽  
Lijun Li
Author(s):  
Kavita Sardana ◽  
John C. Bergstrom ◽  
J. M. Bowker

Abstract We estimate a travel cost model for the George Washington & Jefferson National Forests using an On-Site Latent Class Poisson Model. We show that the constraints of ad-hoc truncation and homogenous preferences significantly impact consumer surplus estimates derived from the on-site travel cost model. By relaxing the constraints, we show that more than one class of visitors with unique preferences exists in the population. The resulting demand functions, price responsive behaviors, and consumer surplus estimates reflect differences across these classes of visitors. With heterogeneous preferences, a group of ‘local residents’ exists with a probability of 8% and, on average take 113 visits.


2020 ◽  
Vol 20 (2) ◽  
pp. 7
Author(s):  
Waldemar Mercado ◽  
Felipe Vásquez Lavín ◽  
Karina Ubillus ◽  
Carlos Enrique Orihuela

<div data-canvas-width="450.13143999999994">The aim was to determine the importance of the biodiversity on the decision to visit six Natural Parks of Peru. For this, a sample of tourists and the discrete travel cost model are used to estimate the demand of multiple places with different attributes. The results confirm that the probability of choice depends on the access routes, the biodiversity, the distance, and the cost of the trip. The effect of the biodiversity is less important than that of access routes. A conservation policy that considers these attributes will be key for the management of the biodiversity.</div>


2019 ◽  
Vol 11 (24) ◽  
pp. 6996
Author(s):  
Shuo Zhao ◽  
Xiwei Mi ◽  
Zhenyi Li

Train stop planning provides appropriate service for travel demand and stations and plays a significant role in railway operation. This paper formulates stop planning from the point of view of direct travel between origin-destination (O-D) stations and proposes an analytical method to theoretically derive optimal service frequencies for O-D demand on different levels. Considering different O-D demand characteristics and train service types, we introduce the concept of stop probability to present the mathematical formulation for stop planning with the objective of minimizing per capita travel time, which is solved by an iterative algorithm combined with local search. The resulting optimal stop probabilities can be used to calculate the required service frequency for each train type serving different demand categories. Numerical examples, based on three real-life high-speed railway lines, demonstrate the validity of the proposed method. The proposed approach provides a more flexible and practical way for stop planning that explicitly takes into account the importance of different stations and passenger travel characteristics.


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