230.548 People
Kouwenhoven, Marco
in Cooperation with on an Cooperation-Score of 37%
Topics
- data collection
- data
- logistics
- road
- travel
- travel time
- stated preference
- income
- survey
- rural area
- cost benefit analysis
- financing
- value of time
- neural network
- choice model
- Monte Carlo method
- reliability
- forecasting model
- highway traffic
- highway transportation
- economics
- medical treatment
- standard deviation
- vehicle occupant
- passenger
- bus
- port
- airport
- gasoline
- passenger transportation
- questionnaire
- travel cost
- household
- costs
- education
- parking
- developed country
- service station
- bus stop
- garage
- interviewing
- recruiting
- parking garage
- freight transportation
- commodity
- shipment
- freight traffic
- public transit
- perception
- comfort
- infrastructure
- maintenance
- railroad train
- automatic control
- crowd
- ridership
- modernization
- urban mobility
- investment
- headway
- crossheading
- bus route
- rolling stock
- bus line
- traffic model
- waiting time
- shortage
- local transportation plan
- profit
- face
- pilot study
- automobile ownership
- automobile
- ownership
- road pricing
- specification
- price
- traveler
- fee
- consumer
- taxation
- government
- variable costs
- fixed costs
- operating costs
- sales tax
- motorcycle
- modeling
- commuter
- aircraft
- passenger volume
- simulation
- driver
- high speed train
- validation
- forecasting
- synthetic
- hub
- market
- bottleneck
- constraint
- chemical element
- coalition
- transportation mode
- accessibility
- flight path
- air route
- low-cost airline
- database
- logit
- airport runway
- market share
- level of service
- time series
- airport capacity
- watershed
- passenger demand
- river basin
- catchment area
- long range planning
- econometric model
- show 91 more
Publications
- 2022Can repeated surveys reveal the variation of the value of travel time over time?
- 2021An artificial neural network based method to uncover the value-of-travel-time distributioncitations
- 2016Forecasting travel time reliability in road transport: A new model for the Netherlands
- 2015De waarde van betrouwbare reistijden in personenverkeer en –vervoer in Nederland
- 2014New values of time and reliability in passenger transport in The Netherlandscitations
- 2014New SP-values of time and reliability for freight transport in the Netherlandscitations
- 2013On the value of crowding in public transport for Île-de-Francecitations
- 2009A pilot study into the perception of unreliability of travel times using in-depth interviewscitations
- 2009The impact of fixed and variable costs on household car ownershipcitations
- 2007Modeling of motorcycle ownership and commuter usage: A UK studycitations
- 2005The airport Network and Catchment area Competition Model - A comprehensive airport demand forecasting system using a partially observed database
Places of action
document
An artificial neural network based method to uncover the value-of-travel-time distribution
Abstract
This study proposes a novel Artificial Neural Network (ANN) based method to derive the Value-of-Travel-Time (VTT) distribution. The strength of this method is that it is possible to uncover the VTT distribution (and its moments) without making assumptions about the shape of the distribution or the error terms, while being able to incorporate covariates and taking the panel nature of stated choice data into account. To assess how well the proposed ANN-based method works in terms of being able to recover the VTT distribution, we first conduct a series of Monte Carlo experiments. After having demonstrated that the method works on Monte Carlo data, we apply the method to data from the 2009 Norwegian VTT study. Finally, we extensively cross-validate our method by comparing it with a series of state-of-the-art discrete choice models and nonparametric methods. Based on the promising results we have obtained, we believe that there is a place for ANN-based methods in future VTT studies.
Topics
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