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On the movement simulations of electric vehicles : A behavioral model-based approach
Xu, Yueru Zheng, Yuan Yang, Ying
Xu, Yueru
Zheng, Yuan
Yang, Ying
Author
Abstract
Electric vehicles (EVs) are deemed to be a solution for reducing air pollution and greenhouse gas emissions. As a result, the market share has increased exponentially in recent years. Despite their distinct vehicle dynamics and characteristics, movement simulation models dedicated to EVs are yet to be developed. In this research, a micro-traffic flow model for EVs by considering their unique acceleration/deceleration characteristics is proposed to represent and simulate the movements of EVs in traffic flow, especially in congested traffic. Car-following pairs where second car is an EV were collected from Longpan mid road, Nanjing, China in March 2019 for model calibration and verification. The results show that the proposed EV behavior model outperforms traditional behavior models for both timid and aggressive drivers. In assessing the predictive power of the movement simulation models, we compare their performance for collected car-following pairs. The R-squared values indicate that the performance of the EV behavior model is similar to that of the asymmetric behavior model under free-flow conditions, but substantially better for congested scenarios. With this model, we can better understand and reproduce the trajectories and energy consumption of EVs in complex traffic flow scenarios, and especially in congested traffic.
Keywords
car-following model, congested traffic, electric vehicle behavior, movement simulation
Date
2021
Type
Journal article
Journal
Applied Energy
Book
Volume
283
Issue
Page Range
1-11
Article Number
Article 116356
ACU Department
School of Behavioural and Health Sciences
Faculty of Health Sciences
Faculty of Health Sciences
Relation URI
Source URL
Event URL
Open Access Status
License
All rights reserved
File Access
Controlled