Optimizing urban bus network based on spatial matching patterns for sustainable transportation: A case study in Harbin, China DOI Creative Commons

Boya Gao,

Jie Liu

PLoS ONE, Journal Year: 2024, Volume and Issue: 19(10), P. e0312803 - e0312803

Published: Oct. 28, 2024

The rapid economic development and accelerating urbanization have led to a significant mismatch between the urban bus network allocation population flow. Therefore, this paper investigates challenge by exploring intricate relationship flow dynamics, traffic congestion conditions, efficient of resources. In response, two key indexes were introduced based on spatial matching patterns assess network: Population-Bus Match Index evaluates degree supply demand, Population-Congestion utilization saturation. Additionally, distinct optimization strategies been proposed enhance network. first strategy considers network’s current status, while second aspires an idealized scenario. Subsequently, potential contributions each station in reducing CO 2 emission reduction after implementing are quantified. Utilizing case study focused Harbin, methods validated. findings unveil substantial misalignment demand within during peak periods, with nearly half stations experiencing disparity Comparative experiments across different reveal that significantly outperforms first, but has higher contribution. results provide decision-makers environmentally oriented vantage point for discerning selection leave valuable insights areas confronting transportation challenges.

Language: Английский

Discovering impacts of built environment on transit ridership in the post-COVID era: Policy intervention and nonlinear dynamics DOI Creative Commons
Zhe Ding, Enhui Chen, Jing Teng

et al.

International Journal of Transportation Science and Technology, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 1, 2025

Language: Английский

Citations

0
Impact of the “Class B Infectious Disease Class B Management” Policy on the Passenger Volume of Urban Rail Transit: A Nationwide Interrupted Time Series Study DOI Open Access

Mengchen Yang,

Yusong Zhu,

Xiang Ji

et al.

Sustainability, Journal Year: 2025, Volume and Issue: 17(6), P. 2365 - 2365

Published: March 7, 2025

Between 2019 and 2022, passenger volume on China’s urban rail transit system sharply declined due to strict COVID-19 control measures. On 8 January 2023, China implemented the “Class B infectious disease Class management” policy, marking a significant shift towards more relaxed approach epidemic control. The main objective of this study is evaluate immediate lasting effects policy volume. We used interrupted time series (ITS), combined with quasi-Poisson regression models counterfactual analysis, analyze monthly operation data covering period from 2021 June 2024 for 42 cities. Our analysis shows that, relative expected trend without any intervention, average increased by approximately 101.34% after policy’s implementation, observed in 41 cities 33 concludes that has generally promoted nationwide recovery volume, although heterogeneity across This result indicates reduction travel restrictions restoration public safety, resulting relaxation prevention measures, contributed overall transit. not only provides innovative methodological insights but also offers valuable guidance developing effective planning strategies operational measures post-pandemic era.

Language: Английский

Citations

0
A dynamic assessment of greenspace exposure from a time and age perspective: comparing lockdown and non-lockdown periods DOI Creative Commons

Xiaoxu Yin,

Yimeng Song, Lijun Zhang

et al.

Ecosystem Health and Sustainability, Journal Year: 2024, Volume and Issue: 10

Published: Jan. 1, 2024

Urban greenspace has a profound impact on public health by purifying the air, blocking bacteria, and creating activity venues. Due to people’s different position, exposure age groups changes at various times. In this study, we combined NDVI (normalized difference vegetation index) GVI (green view green indices with mobile signaling big data evaluate of 3 in Shanghai A dynamic assessment model for been adopted study. April 2021 2022 were selected as study periods, representing non-lockdown period lockdown period, respectively. The results indicate that slightly during period. During lockdown, 31 50, 51, above was higher than non-lockdown. However, people aged 0 30 is lower 51 other group. Whether it under or not, from 8:00 17:00, showed value hours. fluctuates steadily 6:00 24:00. This enriches evaluation dimensions urban exposure.

Language: Английский

Citations

0
Optimizing urban bus network based on spatial matching patterns for sustainable transportation: A case study in Harbin, China DOI Creative Commons

Boya Gao,

Jie Liu

PLoS ONE, Journal Year: 2024, Volume and Issue: 19(10), P. e0312803 - e0312803

Published: Oct. 28, 2024

The rapid economic development and accelerating urbanization have led to a significant mismatch between the urban bus network allocation population flow. Therefore, this paper investigates challenge by exploring intricate relationship flow dynamics, traffic congestion conditions, efficient of resources. In response, two key indexes were introduced based on spatial matching patterns assess network: Population-Bus Match Index evaluates degree supply demand, Population-Congestion utilization saturation. Additionally, distinct optimization strategies been proposed enhance network. first strategy considers network’s current status, while second aspires an idealized scenario. Subsequently, potential contributions each station in reducing CO 2 emission reduction after implementing are quantified. Utilizing case study focused Harbin, methods validated. findings unveil substantial misalignment demand within during peak periods, with nearly half stations experiencing disparity Comparative experiments across different reveal that significantly outperforms first, but has higher contribution. results provide decision-makers environmentally oriented vantage point for discerning selection leave valuable insights areas confronting transportation challenges.

Language: Английский

Citations

0