Optimization of on-street parking layout based on transport-energy integration

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.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2026-07-24
DOI
https://doi.org/10.1038/s41598-026-62806-7
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimization of on-street parking layout based on transport-energy integration

Tianzheng Wei, Yi Yuan, Han Bai, Jian Lü et al.
Scientific Reports
Electric Vehicles and Infrastructure
article

Optimization of on-street parking layout based on transport-energy integration

Tianzheng Wei, Yi Yuan, Han Bai, Jian Lü, Liang Zhao, Xiuguang Wang
article en

Abstract

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.

Scientific Reports
Shandong Jiaotong University (CN)
Natural Science Foundation of Shandong Province
Openalex Percentile: Top 15%
Electric Vehicles and Infrastructure
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Optimization of on-street parking layout based on transport-energy integration — Tianzheng Wei, Yi Yuan, et al. · Scientific Reports (2026) | TGRS Research Map | TGRS