A route analysis of metro-bikeshare users using smart card data

Liu, Yang; Ji, Yanjie; Feng, Tao; Shi, Zhuangbin

doi:10.1016/j.tbs.2021.09.006

Cited by 17 publications

(13 citation statements)

References 21 publications

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“…Furthermore, in the study of risk factors of pedestrians crossing illegally, whether the crosswalk facilities are reasonable or not directly influenced the comfort of pedestrians using these facilities, thus indirectly influencing the risk of pedestrians crossing the street illegally. The traffic state at signal intersections usually directly affects the crossable gap for pedestrians [ 39 , 42 ], and the built environment around the intersection determines the composition of the pedestrian crossing group [ 7 , 43 ]. We selected traffic conditions, the built environment, and crosswalk facilities of crosswalks as the main categories of our investigation.…”

Section: Methodsmentioning

confidence: 99%

A Geographical and Temporal Risk Evaluation Method for Red-Light Violations by Pedestrians at Signalized Intersections: Analysis and Results of Suzhou, China

Xing

Zhang

Cheng

et al. 2022

IJERPH

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Red-light violations of pedestrians crossing at signal intersections is one of the key factors in pedestrian traffic accidents. Even though there are various studies on pedestrian behavior and pedestrian traffic conflicts, few focus on the risk of different crosswalks for the violating pedestrian group. Due to the spatio-temporal nature of violation risk, this study proposes a geographical and temporal risk evaluation method for pedestrian red-light violations, which combines actual survey and video acquisition. First, in the geographical-based risk evaluation, the pedestrian violation rate at signal intersections is investigated by Pearson correlation analysis to extract the significant influencing factors from traffic conditions, built environment, and crosswalk facilities. Second, in the temporal-based risk evaluation, the survival analysis method is developed to quantify the risk of pedestrian violation in different scenarios as time passes by. Finally, this study selects 16 typical signalized intersections in Suzhou, China, with 881 pedestrian crosswalk violations from a total size of 4586 pedestrians as survey cases. Results indicate that crossing distance, traffic volume on the crosswalk, red-light time, and crosswalk-type variables all contribute to the effect of pedestrian violation from a geographical perspective, and the installation of waiting refuge islands has the most significant impact. From the temporal perspective, the increases in red-light time, number of lanes, and traffic volume have a mitigating effect on the violations with pedestrian waiting time increases. This study aims to provide a development-oriented path by proposing an analytical framework that reconsiders geographical and temporal risk factors of violation. The findings could help transport planners understand the effect of pedestrian violation-related traffic risk and develop operational measures and crosswalk design schemes for controlling pedestrian violations occurring in local communities.

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Section: Methodsmentioning

confidence: 99%

A Geographical and Temporal Risk Evaluation Method for Red-Light Violations by Pedestrians at Signalized Intersections: Analysis and Results of Suzhou, China

Xing

Zhang

Cheng

et al. 2022

IJERPH

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“…However, SCAFC is collecting not only the revenue, but also the information that comes with each payment such as the date and time of each entry, boarding and exiting locations, transit route number, fare concession of the payment, etc. All those data are advancing the related analysis in transit, as well as creating new orientation in the field such as Origin-Destination (OD) estimation (Hussain et al 2021;Seaborn et al, 2009;Trépanier et al, 2007), route choice analysis (Arriagada et al, 2022;Lee et al, 2022;Liu et al, 2022), supply and demand modelling Wang et al, 2015), fare change impact analysis (Wang et al, 2015), and equity analysis (Dixit et al, 2021).…”

Section: Smart Card Data Utilization In Public Transportationmentioning

confidence: 99%

“…One of the popular topics for strategic studies is route choice analysis (Arriagada et al, 2022;Lee et al, 2022;Liu et al, 2022). In Seoul, South Korea, Lee et al (2022) explored route preferences of subway passengers using smart cards and train log data.…”

Section: Smart Card Data Utilization In Public Transportationmentioning

confidence: 99%

“…Also, allowed wait time and walking time to be integrated into the analysis, and the researchers found waiting time was relatively more burdensome for the aggregated strategy class. Meanwhile, in Nanjing, China, metro and shared bike smart card data were combined and analyzed for the spatiotemporal characteristics of the combined travel routes (Liu et al, 2022). The authors found that young people tend to be occasional users of this combined mode, while elders were metro-bikeshare commuters.…”

Section: Smart Card Data Utilization In Public Transportationmentioning

confidence: 99%

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Toronto Transit Commission and COVID-19: Statistical and Spatial Analysis of Ridership Changes During the Pandemic

2024

Preprint

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<p>The COVID-19 pandemic is an unprecedented event that has shifted travel patterns. The Toronto Transit Commission witnessed a significant ridership drop and subsequent fluctuations during the pandemic. This exploratory research investigates ridership changes using statistical and spatial analysis over different intervals based on changes in government-imposed restrictions. Ridership increased with the lifting of restrictions, while mixed ridership trends were observed during the intermittent lockdown periods. On the spatial side, relatively high degrees of homogeneity in ridership changes were discovered for census tracts with subway service, and census tracts along subway lines showed heterogeneity. For trips that end downtown, the ridership was cut in half compared to pre-pandemic levels and demonstrated similar change patterns to the trips ending elsewhere. Lastly, some socioeconomic and demographic factors were found to be the driving factors with spatial inherency for positive ridership change using geographic weighted regression models.</p>

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“…Clustering analysis algorithm is an important research topic based on data mining. Data mining refers to the ability to mine and discover valuable, meaningful, and implicit potential knowledge or rules from a large amount of data in order to give decision support to the problems provided by users [ 30 ].…”

Section: Clustering Analysis Algorithmmentioning

confidence: 99%

Analysis of the Intelligent Tourism Route Planning Scheme Based on the Cluster Analysis Algorithm

Lou

2022

Computational Intelligence and Neuroscience

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In view of the problems of the traditional cluster analysis algorithm such as strong dependence on the initial cluster center, the traditional k-means cluster analysis algorithm is improved and the experiment proves that the improved algorithm has a better clustering effect; in view of the problems of the traditional tourism route planning, the improved k-means cluster analysis algorithm is applied to the intelligent tourism route planning scheme design and an intelligent tourism planning scheme based on the cluster analysis algorithm is proposed; the tourists’ preference metric is fully considered, and the experimental results show that the scheme has certain reasonableness and reference value.

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A route analysis of metro-bikeshare users using smart card data

Cited by 17 publications

References 21 publications

A Geographical and Temporal Risk Evaluation Method for Red-Light Violations by Pedestrians at Signalized Intersections: Analysis and Results of Suzhou, China

A Geographical and Temporal Risk Evaluation Method for Red-Light Violations by Pedestrians at Signalized Intersections: Analysis and Results of Suzhou, China

Toronto Transit Commission and COVID-19: Statistical and Spatial Analysis of Ridership Changes During the Pandemic

Analysis of the Intelligent Tourism Route Planning Scheme Based on the Cluster Analysis Algorithm

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