4.7 Article

Agent-based modelling approach for autonomous vehicle influence on countries? welfare

期刊

JOURNAL OF CLEANER PRODUCTION
卷 374, 期 -, 页码 -

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ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2022.134008

关键词

Autonomous vehicles; Agent -based modelling; Welfare; Public safety

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The transition from conventional to self-driving vehicles is important for reducing transportation costs, improving road safety, and decreasing environmental pollution. This research assesses the impact of household welfare on the development of autonomous vehicles and provides policy recommendations for promoting their adoption.
The inevitable transition from conventional to self-driving vehicles is a large-scale process involving a series of interactions and related to major challenges for human society. Autonomous vehicles (AVs) considered as a future of road transport, have the potential to significantly reduce transport costs, improve road safety by significantly reducing road accidents and fatalities, make vehicles more environmentally friendly, reduce the travel time and increase the number of passengers. Taking into account all the benefits of AVs, the rapid development of AVs in all countries is becoming a very important factor. This research considers the assessment of the households welfare influence on the development of AVs. To ensure realistic future scenarios modelling was supported by empirical data. The obtained modelling results made it possible to predict a significant reduction in traffic accidents and environmental pollution, and to consider some policy recommendations to promote the development and a broader range introduction of AVs. The method of agent-based modelling was used to develop the market penetration simulation, which allowed quantifying consumer motives and opportunities in choosing AVs, the development trends of AVs, and providing policy recommendations not only for aggregated country level situations, but for households and individuals as well. The proposed model and results may be useful for planners and researchers working on long-term solutions related to safer and less polluting AVs and predicting purchasing behaviour of households.

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