Computational Process Modelling of Disaggregate Travel Behaviour

1997 ◽  
pp. 171-185 ◽  
Author(s):  
Mei-Po Kwan ◽  
Reginald G. Golledge
Keyword(s):  
Travel Behaviour ◽  
Process Modelling ◽  
Computational Process

Railway's Impacts on Modal Shift Potential Towards Intermodal Transportation: A Case Study in Lao PDR.

2020 ◽  
Vol 11 (1) ◽  
pp. 123-123
Author(s):  
Klairung Ponanan ◽  
Wachira Wichitphongsa
Keyword(s):  
Service Providers ◽  
Lao Pdr ◽  
Travel Behaviour ◽  
Silk Road ◽  
Transport Infrastructure ◽  
Chinese Government ◽  
Modal Shift ◽  
Long Distance ◽  
Silk Road Economic Belt ◽  
The Silk Road

Chinese government has developed transport infrastructure rapidly under Belt and Road Initiative (BRI) strategy. The BRI strategy is China's economic development strategies for expanding trade and cultural influence towards countries in western and eastern regions, including ASEAN. The development of BRI strategy is consists of two main components i.e., (i) the Silk Road Economic Belt, follows the historical overland Silk Road through Central Asia, Iran, Turkey and eventually to Europe, and (ii) the Maritime Silk Road, originates in the South China Sea, passing through the Malacca Strait, the Indian Ocean, and the Red Sea and extending into the Mediterranean Sea (Chris & Elizabeth, 2015). Due to the BRI strategy, more than 6000 trains made the journey from China to Europe in 2018, which is an increase of 72% compared to 2017. China has sent more than 11,000 freight trains to Europe and back since the BRI strategy was announced in 2013. Railway networks have been constructed under the BRI strategy for connecting 48 Chinese cities with 42 cities in Europe through Asia. There are many railway infrastructures under the BRI strategy. The China – Laos railway (Vientiane–Boten railway) is one of project under the Silk Road Economic Belt that has been developed for serving as a key infrastructure for the economic corridor between the two countries. In nearly future, this railway will be helped to boost trade, investment and tourism for Lao PDR. and south China's Guangxi Zhuang Autonomous Region. The Vientiane–Boten railway, especially transportation time will attract both travelers and Logistics Service Providers (LSP), which can be reduced time of journey compared with road mode. In this paper, modal shift potential of travelers and freight on Kunming-Bangkok Highway (R3A), AH2, AH8, AH9, AH10, AH12, AH13, and AH18 have been investigated by considering behavioral aspects of long distance travel. Keywords: Mode Split Model, Modal Shift, Vientiane–Boten railway, Travel Behaviour

scholarly journals The travel behaviour intentions of young people in the context of climate change

2010 ◽  
Vol 18 (2) ◽  
pp. 238-246 ◽  
Author(s):  
Tilly Line ◽  
Kiron Chatterjee ◽  
Glenn Lyons
Keyword(s):  
Climate Change ◽  
Young People ◽  
Travel Behaviour

scholarly journals An Approach to Data Transmission Process Modelling in Automated Power Accounting Systems

2021 ◽  
Vol 1791 (1) ◽  
pp. 012054
Author(s):  
A A Lyubchenko ◽  
E Y Kopytov ◽  
A G Malyutin ◽  
A A Bogdanov
Keyword(s):  
Data Transmission ◽  
Process Modelling ◽  
Accounting Systems ◽  
Transmission Process

scholarly journals Interactive effects between travel behaviour and COVID-19: a questionnaire study

2021 ◽  
Author(s):  
Jinbao Zhang ◽  
Jaeyoung Lee
Keyword(s):  
Early Stage ◽  
Travel Behaviour ◽  
Interactive Effects ◽  
Factors Affecting ◽  
Individual Level ◽  
Passenger Volume ◽  
Spatial Autoregressive ◽  
Railway Passenger ◽  
The Individual ◽  
And Control

Abstract This study has two main objectives: (i) to analyse the effect of travel characteristics on the spreading of disease, and (ii) to determine the effect of COVID-19 on travel behaviour at the individual level. First, the study analyses the effect of passenger volume and the proportions of different modes of travel on the spread of COVID-19 in the early stage. The developed spatial autoregressive model shows that total passenger volume and proportions of air and railway passenger volumes are positively associated with the cumulative confirmed cases. Second, a questionnaire is analysed to determine changes in travel behaviour after COVID-19. The results indicate that the number of total trips considerably decreased. Public transport usage decreased by 20.5%, while private car usage increased by 6.4%. Then the factors affecting the changes in travel behaviour are analysed by logit models. The findings reveal significant factors, including gender, occupation and travel restriction. It is expected that the findings from this study would be helpful for management and control of traffic during a pandemic.

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