BVis: urban traffic visual analysis based on bus sparse trajectories

Pei, Wenqi; Wu, Yadong; Wang, Song; Xiao, Lili; Jiang, Hongyu; Qayoom, Abdul

doi:10.1007/s12650-018-0489-z

Cited by 13 publications

(7 citation statements)

References 11 publications

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“…The OD connections are hard to perceive due to the data abstraction, aggregation, or the high level of detail. Pei et al (Pei et al, 2018) suggested an urban traffic visual analysis based on bus sparse trajectories to explore multiple attributes in trajectory data and display an overview of massive data. Based on a statistical view of small multiples, Zhu et al (Zhu et al, 2020) designed a multi-view combination visualization approach to depicting the spatial and temporal distribution of trajectory data.…”

Section: Related Workmentioning

confidence: 99%

Multi-attribute interactive visualization of three-dimensional trajectory sets

He¹,

Chen²,

Technology-Beijing³

2021

KJS publishes peer-review articles in Mathematics, Computer Sci

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Rapidly advancing location-awareness technologies and services have collected and stored massive amounts of moving object trajectory data with attribute information that involves various degrees of spatial scales, timescales, and levels of complexity. Unfortunately, interesting behaviors regarding combinations of attributes are scarcely extracted from datasets. Further, trajectories are typically dependent on the environment of three-dimensional space, and another issue of interest to us is to preserve spatial-location visualization while guaranteeing the description of temporal information. Therefore, we developed a novel analytics tool that combines visual and interactive components to enable a dynamic visualization of three-dimensional trajectory multi-attribute behaviors. Under the context of spatiotemporal analysis, this approach integrates multiple attributes into one view to efficiently explore the attribute visualization problem of multi-attribute combination without over-plotting. To assess the feasibility of our solution, we visualized and analyzed multi-attribute information of moving object trajectories using a real mining truck dataset as a case study.

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Section: Related Workmentioning

confidence: 99%

Multi-attribute interactive visualization of three-dimensional trajectory sets

He¹,

Chen²,

Technology-Beijing³

2021

KJS publishes peer-review articles in Mathematics, Computer Sci

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“…Pei et al (2018) proposed a visual analysis system named BVis to analyze the urban traffic that applies large-scale actual sparse public transportation datasets [8]. The BVis system covers 4 modules of bus data visualization: first, the cleansing and mapping of sparse trajectory data; second, the analysis of global traffic conditions and sectional traffic modes; third, the bus station congestion mode analysis of bus station using parking time; and forth, the analysis of the importance of bus stations in complicated public transportation networks.…”

Section: Literature Reviewmentioning

confidence: 99%

Countermeasure Study of Urban Traffic Improvement Based on the Internet of Things

Wang

Sheng

et al. 2020

IEEE Access

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In order to reduce the fluctuations of traffic flow and the impacts of traffic flow fluctuations, thereby increasing the level of service of roads and constructing the Internet of Things-based traffic system, based on the various causes of traffic flow fluctuations, the countermeasures were taken, such as the optimization of lanes, the management of intersections, the improvement and perfection of slow-vehicle lanes and bus stops, the timely renewal of traffic signs and marks, the rational arrangements of road operations, and the removal of visual obstacles, etc. The research results showed that these countermeasures could effectively reduce the hidden peril of accidents and improve the road capacity, thereby improving the level of service of roads, which provided a theoretical foundation and basis for road engineering design and traffic management. It can be seen that improving urban traffic through rational management and control measures can effectively improve the level of service of urban traffic. INDEX TERMS Urban road, traffic flow fluctuation, level of service, countermeasure.

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“…The intelligent transport system (ITS) mainly focus on promoting the public transportation system by utilizing various advanced technologies. The bus passengers are being attracted to get some real‐time information about busses like time of arrival, availability of seats, and the present location of busses 2 . The busses are one of the most important components of urban public transport like cabs and subways.…”

Section: Introductionmentioning

confidence: 99%

“…The bus passengers are being attracted to get some realtime information about busses like time of arrival, availability of seats, and the present location of busses. 2 The busses are one of the most important components of urban public transport like cabs and subways. The static stopping and parking area of busses are the most important features, which help to investigate traffic conditions, improve the architecture of bus stations, examine the passenger flow, and so on.…”

Section: Introductionmentioning

confidence: 99%