How will electric vehicles affect traffic congestion and energy consumption: an integrated modelling approach

被引:3
作者
Grigorev, Artur [1 ]
Mao, Tuo [1 ]
Berry, Adam [1 ]
Tan, Joachim
Purushothaman, Loki [1 ]
Mihaita, Adriana-Simona [1 ]
机构
[1] Univ Technol Sydney, Fac Engn & IT, Sch Comp Sci, 61 Broadway, Ultimo, NSW, Australia
来源
2021 IEEE INTELLIGENT TRANSPORTATION SYSTEMS CONFERENCE (ITSC) | 2021年
关键词
electric vehicles; traffic simulation modelling; queue modelling; recharging scenario evaluation; fast charge impact modelling; CHARGING INFRASTRUCTURE; DEMAND;
D O I
10.1109/ITSC48978.2021.9564561
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper explores the impact of electric vehicles (EVs) on traffic congestion and energy consumption by proposing an integrated bi-level framework comprising of: a) a dynamic micro-scale traffic simulation suitable for modelling current and hypothetical traffic and charging demand scenarios and b) a queue model for capturing the impact of fast charging station use, informed by traffic flows, travel distances, availability of charging infrastructure and estimated vehicle battery state of charge. To the best of our knowledge, this paper represents the first integrated analysis of potential traffic congestion and energy infrastructure impacts linked to EV uptake, based on real traffic flows and the placement and design of existing fast-charging infrastructure. Results showcase that the integrated queue-energy-transport modelling framework can predict correctly the limitations of the EV infrastructure as well as the traffic congestion evolution. The modelling approach identifies concrete pain points to be addressed in both traffic and energy management and planning.
引用
收藏
页码:1635 / 1642
页数:8
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