Analyzes EV charging behavior and optimizes parking layout, suggesting enhanced user satisfaction with less infrastructure cost.
The rapid growth in electric vehicle (EV) ownership has intensified the linkage between urban parking shortages and charging infrastructure constraints, rendering conventional parking-only layout frameworks inadequate. Therefore, this study proposes integrating EV charging demand into on-street parking layout optimization from a Transport-Energy Integration (TEI) perspective. First, a Stated Preference (SP) survey was conducted to analyze user charging choice behavior, and a Logit model was developed to quantify the effects of factors such as remaining battery level, walking distance, charging price, and parking discounts on charging probability. Second, a multi-objective on-street parking layout optimization model was constructed, aiming to maximize parking and charging demand satisfaction rates while minimizing parking facility construction costs and road segment saturation. Finally, a hybrid NSGA-II-AHA algorithm is developed to address the local convergence trap inherent in the standard NSGA-II algorithm. A case study conducted in Laicheng District, Jinan, demonstrates that the optimized layout fully satisfies parking demand (100%) and increases the charging demand satisfaction rate from 59% to 97%, highlighting the practicality and effectiveness of the proposed framework.
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Bai et al. (2026) studied this question.
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