Impact of Electronic Road Pricing (ERP) Changes on Transport Modal Choice

Background: In a world where every municipality is pursuing the goals of more sustainable mobility, bicycles play a fundamental role in getting rid of private cars and travelling by an eco-friendly mode of transport. Additionally, private and shared bikes can be used as a feeder transit system, solving the problem of the first- and last-mile trips. Thanks to GIS (Geographic Information System) software, it is possible to evaluate the effectiveness of such a sustainable means of transport in future users’ modal choice. Methods: Running an accessibility analysis of cycling and rail transport services, the potential mobility demand attracted by these services and the possible multimodality between bicycle and rail transport systems can be assessed. Moreover, thanks to a modal choice model calibrated for high school students, it could be verified if students will be really motivated to adopt this solution for their home-to-school trips. Results: The GIS-based analysis showed that almost half of the active population in the study area might potentially abandon the use of their private car in favour of a bike and its combination with public transport systems; furthermore, the percentage of the students of one high school of Palermo, the Einstein High School, sharply increases from 1.5% up to 10.1%, thanks also to the combination with the rail transport service. Conclusions: The GIS-based methodology shows that multimodal transport can be an effective way to pursue a more sustainable mobility in cities and efficiently connect suburbs with low-frequent public transport services to the main public transport nodes.

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Lexicographic Multi-Objective Road Pricing Optimization Considering Land Use and Transportation Effects

European Journal of Operational Research ◽

10.1016/j.ejor.2021.05.048 ◽

2021 ◽

Author(s):

Shaopeng Zhong ◽

Yu Jiang ◽

Otto Anker Nielsen

Keyword(s):

Land Use ◽

Road Pricing ◽

Multi Objective ◽

Pricing Optimization

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A socio-psychological modal choice approach to modelling mobility and energy demand for electric vehicles

Energy Informatics ◽

10.1186/s42162-020-00123-7 ◽

2020 ◽

Vol 3 (S1) ◽

Author(s):

Khoa Nguyen ◽

René Schumann

Keyword(s):

Energy Demand ◽

Supply And Demand ◽

Stochastic Approach ◽

Social Characteristics ◽

Limited Information ◽

Demand Model ◽

Modal Choice ◽

Charging Infrastructure ◽

Human Decision ◽

Electro Mobility

Abstract The development of efficient electric vehicle (EV) charging infrastructure requires modelling of consumer demand at an appropriate level of detail. Since only limited information about real customers is available, most simulations employ a stochastic approach by combining known or estimated business features (e.g. arrival and departure time, requested amount of energy) with random variations. However, these models in many cases do not include factors that deal with the social characteristics of EV users, while others do not emphasise on the economic elements. In this work, we introduced a more detailed demand model employing a modal choice simulation framework based on Triandis’ Theory of Interpersonal Behaviour, which can be calibrated by empirical data and is capable of combining a diverse number of determinants in human decision-making. By applying this model on Switzerland mobility domain, an analysis on three of the most popular EV incentives from both supply and demand sides is provided, which aims for a better understanding of electro-mobility systems by relating its causes and effects.

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