Factors Influencing to Travel Behavior on Transport Mode Choice

The paper aims to build a hybrid personalized multicriteria model in the Indian transportation industry to identify the most feasible transport mode suitable for commuters’ customized preferences. A hybrid multicriterion model, i.e., Fuzzy Analytical Hierarchy Process (AHP), was used to compute the criteria weights, which were subsequently analyzed by three approaches, namely, Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Fuzzy TOPSIS, Evaluation Based on Distance from Average Solution (EDA), and Interpretive Ranking Process (IRP). The case of an Indian metropolitan city, Hyderabad, is taken to illustrate the proposed approach. The paper highlights the following transport modes: metropolitan train (unconventional mode) and conventional modes such as the car, public bus transport, and bikes for Hyderabad. Furthermore, sensitivity analysis is performed to identify the consistency in ranking with variation in weights, and the Ensemble Ranking and transportation experts validate the rankings.

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“…Madhuwanthi et al [37] analyze the travel behavior of Srilankan citizens. Multinomial Factor Analysis is implemented.…”

Section: Existing Research On Vehicle Alternative Selectionmentioning

confidence: 99%

An Intelligent Framework for Analyzing the Feasible Modes of Transportation in Metropolitan Cities: A Hybrid Multicriteria Approach

Srivastava

Zhang

Eachempati

et al. 2021

Journal of Advanced Transportation

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“…Furthermore, in Australia, customers' one-way cost is a significant factor in influencing the perceived satisfaction with train fares [3]. Some factors like income and vehicle ownership also found to be significant in influencing the mode choice behaviour in Srilanka [4]. The preference heterogeneity of mode choice in Australia was partially explained by the intercity differences, user group status, income, and trip purposes [5] In Indonesia, some studies have developed the travel mode choice model between bus and train.…”

Section: Introductionmentioning

confidence: 98%

Mode Choice Modelling Between Bus and Train Under the New Normal Condition

Kriswardhana¹,

Hasanuddin²,

Muntsari³

2021

Civense

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The passenger movements were limited by the government policies that made new system decisions, namely large-scale social distancing policies. However, over time several regions in Indonesia have begun to end large-scale social distancing called new normal. The new normal condition has undoubtedly changed the pattern of mode choice of the passenger. Little attention has been paid to the travel mode choice under the new normal condition. Therefore, this study aims to understand the travel mode choice model of train and bus, especially in the new normal era. The primary data was collected using the stated preference online-based survey. This study performed a Binomial-Logit-Difference model. From the modelling result, 89% of the passenger will choose the bus if the train's travel fare is IDR 160,000 higher. The probability value will be equal when the ticket fare of the bus is IDR 25,000 higher than train’s travel cost. It indicates that people choose the bus mode because of the travel cost factor. Directions for the future study are presented

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“…The study of road users' behaviour has direct implications for a number of issues: it is used in road safety, where human factors are a major contributor to traffic accidents (Rothengatter, 1997); policy making aimed at improving transport infrastructures (Cadar et al, 2017;Hood et al, 2011;Leao et al, 2017;Melson et al, 2014); and the study of how travel mode choices affect traffic congestion (Madhuwanthi et al, 2016;Chen et al, 2018) and climate change (Hook, 2007).…”

Section: Introductionmentioning

confidence: 99%

Cycling in virtual reality: modelling behaviour in an immersive environment

Bogacz

Hess

Choudhury

et al. 2020

Transportation Letters

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Nowadays, immersive technologies are gaining popularity as a research tool in transport as they allow for a more dynamic approach to the exploration of road users' behaviour providing at the same time full control over interventions. Nevertheless, their ecological validity is still to be established and therefore their use in the mathematical modelling of human behaviour in a transport setting has been scarce. In the present study, we aim to fill this gap by conducting a comparative study of cycling behaviour where both non-immersive and immersive presentation methods are used in a virtual reality setting. We then develop discrete choice models using the collected data. The results confirm our hypothesis that participants behave differently when shown a choice scenario in non-immersive and immersive settings.In particular, cycling in an immersive setting is characterised by a higher degree of engagement, i.e. more action switches. To gain a more complete understanding of the processes underlying interactions in immersive environments, we also captured neural activity (using electroencephalography recordings) during task performance. We focussed on oscillations in the alpha (α) band, a neural signature often associated with the filtering (gating) of sensory information. We found increased suppression in this signal in response to the immersive condition relative to the non-immersive. These results complement the behavioural findings and indicate that immersive environments may increase levels of taskengagement.

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Factors Influencing to Travel Behavior on Transport Mode Choice

Cited by 43 publications

References 4 publications

An Intelligent Framework for Analyzing the Feasible Modes of Transportation in Metropolitan Cities: A Hybrid Multicriteria Approach

An Intelligent Framework for Analyzing the Feasible Modes of Transportation in Metropolitan Cities: A Hybrid Multicriteria Approach

Mode Choice Modelling Between Bus and Train Under the New Normal Condition

Cycling in virtual reality: modelling behaviour in an immersive environment

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