Mitigating the impact of errors in travel time reporting on mode choice modelling

2017 ◽  
Vol 62 ◽  
pp. 236-246 ◽  
Author(s):  
Silvia F. Varotto ◽  
Aurélie Glerum ◽  
Amanda Stathopoulos ◽  
Michel Bierlaire ◽  
Giovanni Longo
Keyword(s):  
Travel Time ◽  
Mode Choice ◽  
Choice Modelling ◽  
The Impact

scholarly journals Do millennials value travel time differently because of productive multitasking? A revealed-preference study of Northern California commuters

2021 ◽  
Author(s):  
Aliaksandr Malokin ◽  
Giovanni Circella ◽  
Patricia L. Mokhtarian
Keyword(s):  
Older Adults ◽  
Young Adults ◽  
Willingness To Pay ◽  
Travel Time ◽  
Choice Model ◽  
Mode Choice ◽  
Revealed Preference ◽  
Northern California ◽  
Factors Affecting ◽  
The Impact

AbstractMillennials, the demographic cohort born in the last two decades of the twentieth century, are reported to adopt information and communication technologies (ICTs) in their everyday lives, including travel, to a greater extent than older generations. As ICT-driven travel-based multitasking influences travelers’ experience and satisfaction in various ways, millennials are expected to be affected at a greater scale. Still, to our knowledge, no previous studies have specifically focused on the impact of travel multitasking on travel behavior and the value of travel time (VOTT) of young adults. To address this gap, we use an original dataset collected among Northern California commuters (N = 2216) to analyze the magnitude and significance of individual and household-level factors affecting commute mode choice. We estimate a revealed-preference mode choice model and investigate the differences between millennials and older adults in the sample. Additionally, we conduct a sensitivity analysis to explore how incorporation of explanatory factors such as attitudes and propensity to multitask while traveling in mode choice models affects coefficient estimates, VOTT, and willingness to pay to use a laptop on the commute. Compared to non-millennials, the mode choice of millennials is found to be less affected by socio-economic characteristics and more strongly influenced by the activities performed while traveling. Young adults are found to have lower VOTT than older adults for both in-vehicle (15.0% less) and out-of-vehicle travel time (15.7% less), and higher willingness to pay (in time or money) to use a laptop, even after controlling for demographic traits, personal attitudes, and the propensity to multitask. This study contributes to better understanding the commuting behavior of millennials, and the factors affecting it, a topic of interest to transportation researchers, planners, and practitioners.

scholarly journals Travel mode choice preferences of urban commuters in Kuching City, Malaysia based on stated preference data

2018 ◽  
Vol 181 ◽  
pp. 02007
Author(s):  
Resdiansyah
Keyword(s):  
Travel Time ◽  
Public Transport ◽  
Public Transportation ◽  
Stated Preference ◽  
Mode Choice ◽  
Travel Behaviour ◽  
Transportation Systems ◽  
Choice Modelling ◽  
Public Transport System ◽  
Bus Services

One aspect of Kuching City that has not progressed in tandem with the rest of the city is the public transport system, which is relatively old and almost non-existent. Transport and City planners seem to be at their wit’s end in coming up with satisfactory solutions to Kuching’s public transportation woes. In current situation, many proposals, but none have proven workable. As a result, representative buses remain a rare sight on Kuching city’s roads. To achieve a sustainable public transport industry, the old buses need to be regenerated and replaced with modern buses. The objectives of the intended study are to explore the consumer’s travel behaviour by employing mode choice modelling. Consequently, a study was conducted in Kuching City Area by using stated preference technique, analysed and compiled by using SPSS.17 multiple linear regressions analysis. In this context, discrete choice analysis was used to examine the relationship between independent variables (travel time, waiting time, fares and comfort) and dependent variables (choice of respondent whether to consume old bus or choose new bus services). A total of 2000 respondents were interviewed. The findings showed that for the trips purpose, fares and comfortability were the primary factors that reflected the decision or behaviour of the respondents asked. It was discovered that there is a significant relationship between the choice of the respondents and comfortability. It also appeared that longer travel time did not affect for the traveler’s choice at this stage. Hence, the study suggests that the local authority and the bus operators should establish a “quality partnership” and working together in order to come out with a much better and appropriate transport policy and schemes for the existing public transportation systems, especially bus services.

scholarly journals How Does the Location of Transfer Affect Travellers and Their Choice of Travel Mode?—A Smart Spatial Analysis Approach

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4418
Author(s):  
Jason Chia ◽  
Jinwoo (Brian) Lee ◽  
Hoon Han
Keyword(s):  
Spatial Distribution ◽  
Travel Time ◽  
Data Transfer ◽  
Mode Choice ◽  
Choice Modelling ◽  
Location Factor ◽  
Explanatory Variables ◽  
Smart Card Data ◽  
Relative Transfer ◽  
Transit Routes

This study explores the relationship between the spatial distribution of relative transfer location (i.e., the location of the transfer point in relation to the trip origin and destination points) and the attractiveness of the transit service using smart card data. Transfer is an essential component of the transit trip that allows people to reach more destinations, but it is also the main factor that deters the smartness of the public transit. The literature quantifies the inconvenience of transfer in terms of extra travel time or cost incurred during transfer. Unlike this conventional approach, the new “transfer location” variable is formulated by mapping the spatial distribution of relative transfer locations on a homogeneous geocoordinate system. The clustering of transfer points is then quantified using grid-based hierarchical clustering. The transfer location factor is formulated as a new explanatory variable for mode choice modelling. This new variable is found to be statistically significant, and no correlation is observed with other explanatory variables, including transit travel time. These results imply that smart transit users may perceive the travel direction (to transfer) as important, in addition to the travel time factor, which would influence their mode choice. Travellers may disfavour even adjacent transfer locations depending on their relative location. The findings of this study will contribute to improving the understanding of transit user behaviour and impact of the smartness of transfer, assist smart transport planning and designing of new transit routes and services to enhance the transfer performance.

scholarly journals An Empirical Analysis of Mode Choice Decision for Utilitarian and Hedonic Trips: Evidence from Iran

2021 ◽  
Vol 13 (12) ◽  
pp. 6896
Author(s):  
Enayat Mirzaei ◽  
Dominique Mignot
Keyword(s):  
Built Environment ◽  
Mode Choice ◽  
Logistic Models ◽  
Strong Relationship ◽  
Choice Modelling ◽  
Travel Mode ◽  
Travel Mode Choice ◽  
Choice Decision ◽  
Using Data ◽  
The Impact

A sizeable body of literature reveals a strong relationship between mode choice and health status. Therefore, society would benefit from travel if transportation and urban planners motivated more individuals to satisfy their desire for travel by active transportation rather than motorized transportation. Despite rich existing literature about the relations between the built environment and travel, we still need to address some research gaps in explaining travel mode choice. As a shortcoming, identifying and measuring the primary motivations for trips, and then incorporating such motivations into travel mode choice modelling, has received less attention in previous research. In this regard the current paper follows two main goals. It aims to differentiate between trips by determining the main utility of travelers and then analyzes the impact of the built environment measurements and subjective attributes on mode choice decision. Using data from a survey of 515 participants who reside in Isfahan, Iran, we conducted a series of binary logistic models to explore how the built environment influences mode choice decisions for different trips, controlling for socio-economics and subjective attributes. The results show that the number of hedonic trips were sizably more than utilitarian trips. It was found that travel mode choice for utilitarian and hedonic trips is influenced by travel habits and subjective attitudes, but the built environment also matters. Specifically, two built environment characteristics, including density and diversity, can substitute walking/cycling for driving for utilitarian trips. In addition, car use for hedonic trips is not influenced by built environment measurements. It seems that the utility and desire of hedonic driving depends on mode of travel. It is concluded that driving and walking/biking for hedonic and utilitarian trips are not single behaviors and differentiating between trips according to their main utility and considering both objective and subjective attributes helps urban and transportation planners prescribe appropriate spatial and nonspatial strategies to encourage walking/biking.

The Impact of Zoning and Built Environment Characteristics on Transit, Biking, and Walking

2019 ◽  
Vol 11 (1) ◽  
pp. 108-129
Author(s):  
Andrew G. Mueller ◽  
Daniel J. Trujillo
Keyword(s):  
Land Use ◽  
Built Environment ◽  
Discrete Choice ◽  
Travel Behavior ◽  
Choice Model ◽  
Mode Choice ◽  
Land Use Regulation ◽  
Policy Action ◽  
Development Goals ◽  
The Impact

This study furthers existing research on the link between the built environment and travel behavior, particularly mode choice (auto, transit, biking, walking). While researchers have studied built environment characteristics and their impact on mode choice, none have attempted to measure the impact of zoning on travel behavior. By testing the impact of land use regulation in the form of zoning restrictions on travel behavior, this study expands the literature by incorporating an additional variable that can be changed through public policy action and may help cities promote sustainable real estate development goals. Using a unique, high-resolution travel survey dataset from Denver, Colorado, we develop a multinomial discrete choice model that addresses unobserved travel preferences by incorporating sociodemographic, built environment, and land use restriction variables. The results suggest that zoning can be tailored by cities to encourage reductions in auto usage, furthering sustainability goals in transportation.

scholarly journals A Study of Taxi Service Mode Choice Based on Evolutionary Game Theory

2019 ◽  
Vol 2019 ◽  
pp. 1-17
Author(s):  
Zhu Bai ◽  
Mingxia Huang ◽  
Shuai Bian ◽  
Huandong Wu
Keyword(s):  
Game Theory ◽  
Evolutionary Game Theory ◽  
Mode Choice ◽  
Evolutionary Game ◽  
Payoff Matrix ◽  
Game Model ◽  
Stable States ◽  
Taxi Service ◽  
Service Mode ◽  
The Impact

The emergence of online car-hailing service provides an innovative approach to vehicle booking but has negatively influenced the taxi industry in China. This paper modeled taxi service mode choice based on evolutionary game theory (EGT). The modes included the dispatching and online car-hailing modes. We constructed an EGT framework, including determining the strategies and the payoff matrix. We introduced different behaviors, including taxi company management, driver operation, and passenger choice. This allowed us to model the impact of these behaviors on the evolving process of service mode choice. The results show that adjustments in taxi company, driver, and passenger behaviors impact the evolutionary path and convergence speed of our evolutionary game model. However, it also reveals that, regardless of adjustments, the stable states in the game model remain unchanged. The conclusion provides a basis for studying taxi system operation and management.

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