The group identifies societal challenges in the transport systems toward sustainable futures and analyses options for sustainable transport including alternative fuels, electric and autonomous technology, and innovative mobility solution. The sustainability challenges the group focuses on are climate change and energy consumption while taking into account other factors such as economic, political, technical and behavioral aspects. The group is multidisciplinary and has a history of working closely with industry partners, a broad range of stakeholder groups and academics. The research methods the group utilises are both qualitative and quantitative, including system modeling tools such as optimization, simulation, and agent-based modeling; mixed method approaches such as econometrics combined with interviews; surveys, big data analytics, lifecycle analysis, etc.
The group is actively engaging in the following research areas:
System modeling of transport futures
The transport system needs to change if we are going to solve the challenges of reducing greenhouse gases emissions and its dependence on fossil resources. We use system models to capture, analyze and understand the critical relationships of the transport sector and its linkages to the entire energy system, and its impact on the environment. For example, we analyse the consequences of major trends such as an increased electrification, automation, and vehicle sharing on the overall energy system. We also study the design of policy measures in order to analyze the (cost) effectiveness of various policies and the potential negative side effects. This research is interdisciplinary involving theories and methods from economics, engineering, and environmental systems analysis.
This research focuses on the user perspective of mobility demand and options. Through interdisciplinary studies we assess new mobility options such as electric vehicles, shared mobility and the introduction of autonomous vehicles. We analyse aspects such as demand changes, environmental performance, economic viability and user acceptance. Our methods range from econometrics, optimization, and statistical analysis to surveys, interviews and logging of vehicle movements.
Long distance travel
For many high-income countries, the climate impact from long distance travel is as large as from the daily short distance travel. Our research includes methodologies for measuring GHG emissions from air travel. We are also interested in understanding how a future transport system for long distance travel in line with the climate target could look like, e.g. the potential for night trains, biofuels, digital meetings and alternative vacationing habits. Another research focus is policy analyses, e.g. regarding the public acceptance for various policy instruments.
Big data in transport
This research is organized around two big ideas: 1) explore the potential expressive analysis of the continuous and large amounts of information sensed in today’s digital environments can boost the understanding of human mobility patterns; 2) enhance access data and knowledge to citizens, stakeholders and researchers to improve their ability to utilize live information that will help achieve social, economic and environmental sustainability in the future transportation. By joining expertise from different disciplines (transport, machine learning, artificial intelligence, computer science and complex systems) and leveraging big data and state-of-the-art analytics, this research aims to significantly advance state-of-the-art mobility applications. This research has broad implications for many disciplines including public health, energy, complex systems and urban planning.
Sonia Yeh, Daniel Johansson, Frances Sprei, Sten Karlsson, Jörgen Larsson, Jonas Nässén
Masnadi, M. S.;
El-Houjeiri, H. M.; Schunack,
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Koomey, J.; Przesmitzki, S.; Azevedo, I. L.; Bi, X. T.;
Duffy, J. E.; Heath, G. A.; Keoleian, G. A.; McGlade, C.;
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Niklas Jakobsson, Till Gnann, Patrick
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in Sweden and Germany, Transportation Research Part C: Emerging Technologies,
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