Evaluating the choice behaviour of high-speed rail passengers in Italy: a latent class structure with alternative kernel models to the Multinomial Logit

Tinessa, Fiore; Simonelli, Fulvio; Marzano, Vittorio; Buonocore, Ciro

doi:10.1109/eeeic/icpseurope49358.2020.9160556

Cited by 4 publications

(3 citation statements)

References 26 publications

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“…This heterogeneous perception variance in the Weibit model is more reasonable than the fixed and identical variance of all routes in the Logit model, because travelers on longer routes have larger perception variances than those on shorter routes in reality (Sheffi, 1985). Some recent empirical studies have verified the above advantage of the Weibit model over the Logit model in various travel choice problems (Kurauchi and Ido, 2017;Li et al, 2020;Tinessa et al, 2020).…”

Section: Review Of Some Basics Of the Weibit Modelmentioning

confidence: 86%

Static congestion pricing considering the cumulative impact of day-to-day dynamics with Weibit adjustment process

Chen

2021

Transportmetrica B: Transport Dynamics

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Static pricing is currently the most prevalent form of congestion pricing. Most existing methods for static pricing design use equilibrium-based indices as the optimization objective function. However, in reality, the equilibrium may not be reached within the toll planning horizon, and thus equilibriumbased pricing schemes might be ineffective in alleviating traffic congestion. To address this issue, this paper proposes a new method for the optimal static congestion pricing design. Specifically, we propose a new measure called cumulative network performance (CNP) as the optimization objective function. The CNP measure explicitly considers the fluctuation in network performance over the toll planning horizon, instead of only focusing on the performance at the equilibrium state. To capture the effect of static congestion pricing on CNP, we introduce a day-to-day dynamic model with the Weibit-based route flow adjustment, which can overcome the drawbacks of the user equilibrium or Logit-based route-choice criterion that are used in most current day-to-day dynamic models. Numerical experiments are conducted to show the effectiveness and advantages of the toll scheme resulting from the proposed method.

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Section: Review Of Some Basics Of the Weibit Modelmentioning

confidence: 86%

Static congestion pricing considering the cumulative impact of day-to-day dynamics with Weibit adjustment process

Chen

2021

Transportmetrica B: Transport Dynamics

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“…To analyse the competition for the forthcoming Jakarta-Surabaya HSR line, binomial logit model was used by Nurhidayat et al [11] based on the data collected by conducting a survey. Tinessa et.al [12] used a multinomial logit model to study mode choice in Italy in the presence of HSR. Future competition between HSR and air transportation in Iran on the Tehran-Isfahan route was forecasted by conducting surveys and developing a logit model by Danapour et al [13].…”

Section: Literature Reviewmentioning

confidence: 99%

Forecasting High-Speed Railway Demand in the Absence of Air Competition – A Case Study

Tilenoie

Sameni

Habibian

2022

Promet

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The main competitor of air transportation is High-Speed Railway (HSR). However, in an oil-exporting country with low fuel prices and strong car dependence, HSR can face fierce competition with private cars and even buses. There is little previous research that forecast modal share in this situation. The case study of this research is the Tehran-Hamedan route in Iran that has high travel demand due to several historical and economic reasons and in the absence of air transportation, building the HSR in this route attracted foreign investment. To analyse the travel behaviour of passengers after the introduction of HSR, 409 stated and revealed preferences were collected in a self-designed questionnaire. Multinomial logit (MNL) model and mixed logit (ML) model were developed and modal share of each mode of transportation were forecasted up to 2045. HSR modal share is compared with other routes of the world to see the impact of air competition. The overall modal share of railway in this route is estimated to reach 64%, which is close to the average of major HSR routes globally (around 60%). Therefore, private cars can be a fierce competitor for HSR when there is no air link on the route and fuel is rather cheap.

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“…Previous studies have analyzed the preference for high-speed rail services by segmented travel time (waiting time, in-vehicle time, and transfer time) or by considering attitudinal factors ( 3 – 6 ). In addition, there are cases of analyzing groups that prefer high-speed rail services by latent class models ( 7 – 9 ). However, since the above studies do not consider the user’s current travel behavior, there is a limit to explaining the mode shifting effect.…”

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confidence: 99%

Investigation of the Policy Effect of High-Speed Metropolitan Rail Service in Seoul Through Latent Class Modeling Analysis of Stated Preference Survey

Yun

Jeong

Kong

et al. 2023

Transportation Research Record: Journal of the Transportation R

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The sprawl of megacities is increasing the need to improve public transit services to cover longer distances in shorter times than current services. High-speed metropolitan rail services have been introduced to satisfy the needs of passengers and are expected to alleviate the transportation problems caused by urban sprawl. However, the effectiveness of public transit demand inducement policies, which have been employed in various ways in South Korea, has been questioned. Thus, agencies responsible for high-speed metropolitan rail services should also evaluate whether such policies will work properly. The achievement of the policy can be evaluated as sufficiently inducing the demand of the target group, and investigated through the residence information and the current travel behavior. This study investigates the current travel behavior of users to be replaced when a new high-speed metropolitan rail service is introduced and directly analyzes the travel mode shifting effect. While previous studies focused on increasing the applicability to general services by classifying groups based on personal attributes, this study focuses on evaluating detailed policy achievements for specific services. We apply a latent class modeling approach using stated preference survey data for group classification. In particular, by employing the user’s current travel behavior as a class membership attribute, the characteristics of potential passengers of the high-speed metropolitan rail service are analyzed. The estimation results suggest that current travel behavior significantly classifies high-speed rail passengers. In addition, the policy achievement was investigated in detail by region and operation time, and several additional policy directions are presented to satisfy the policy goals.

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Evaluating the choice behaviour of high-speed rail passengers in Italy: a latent class structure with alternative kernel models to the Multinomial Logit

Cited by 4 publications

References 26 publications

Static congestion pricing considering the cumulative impact of day-to-day dynamics with Weibit adjustment process

Static congestion pricing considering the cumulative impact of day-to-day dynamics with Weibit adjustment process

Forecasting High-Speed Railway Demand in the Absence of Air Competition – A Case Study

Investigation of the Policy Effect of High-Speed Metropolitan Rail Service in Seoul Through Latent Class Modeling Analysis of Stated Preference Survey

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