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- Andersson, Angelica
(författare)
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Mode choice modelling of long-distance passenger transport based on mobile phone network data
- 2022
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Reliable forecasting models are needed to achieve the climate related goals in the face of increasing transport demand. Such models can predict the long-term behavioural response to policy interventions, including infrastructure investments, and thus provide valuable pre-dictions for decision makers. Contemporary forecasting models are mainly based on national travel surveys. Unfortunately, the response rates of such surveys have steadily declined, implying that the respondents become less representative of the whole population. A particular weakness is that it is likely that respondents with a high valuation of time are less willing to respond to surveys (because they have less time available for such), and therefore there is a high chance that they are underrepresented among the respondents. The valuation of time plays an important role for the cost benefit analyses of public policies including transport investments, and there is no reliable way of controlling for this uneven sampling of time preferences. Fortunately, there is simultaneously an increase in the number of signals sent between mobile phones and network antennae, and research has now reached the point where it is possible to determine not only the travel destination but also the travel mode based on mobile phone network antennae connections. The aim of this thesis is to investigate if and how mobile phone network data can be used to estimate transportation mode choice demand models that can be used for forecasting and planning. Key challenges with using this data source in the context of mode choice models are identified and met. The identified challenges include uncertainty in the choice variable, the difficulty to distinguish car and bus trips, and the lack of information about the trip purpose. In the first paper we propose three possible model formulations and analyse how the uncertainty in the choice outcome variable would play a role in the different model formulations. We also conclude that it is indeed possible to estimate mode choice demand models based on mobile phone network data, with good results in terms of behavioural interpretability and significance. In the second paper we estimate models using a nested logit structure to account for the difficulty in separating bus and car, and a latent class model specification to meet the challenge of having an unknown trip purpose.
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| 2. |
- Berry, Carl, 1994-
(författare)
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Income and Fuel Price Elasticities of Car Use
- 2022
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Understanding how car travel and ownership respond to income and fuel prices, and how that response varies between households is crucial for car use policies and forecasts. This thesis, consisting of two papers, aims to investigate this by estimating the intemporal income and fuel price elasticities of car use using micro registry panel data on all Swedish households from 1998 to 2018. In Paper I, the income and fuel price elasticities of vehicle kilometres travelled (VKT) is estimated for all Swedish households using a linear fixed effects model. In order to investigate how different groups respond, the elasticities are estimated by income group and municipality type. The effect of income and fuel prices on VKT is largest in the middle of the income distribution but is relatively stable across municipality types. The effect of fuel prices on VKT is largest in densely populated municipalities compared to rural municipalities. Moreover, it is shown that the income elasticity is underestimated if income variable is misspecified. Paper II utilises a discrete-continuous model accounting for the effect of income and fuel prices on car ownership. It is shown that income impacts car ownership and VKT conditional on car ownership of similar magnitude, while fuel prices primarily impact VKT conditional on car ownership. Furthermore, we also estimate the model on six partially overlapping sample periods and find that the income elasticity has decreased over time, while the absolute fuel price elasticity increased up until the early 2010s and decreased thereafter.
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