Yuanbang Liu

dblp:412/9243 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Visualization and visual analytics · 100%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Smart cities and intelligent transportation · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Visualization and visual analytics
decision support
0.912025
TraSculptor: Visual Analytics for Enhanced Decision-Making in Road Traffic Planning · IEEE Trans. Vis. Comput. Graph. 2025
Visualization and visual analytics
visual analytics
0.912025
TraSculptor: Visual Analytics for Enhanced Decision-Making in Road Traffic Planning · IEEE Trans. Vis. Comput. Graph. 2025

Methods — techniques the papers use, named apart from their topics

road-state matrix · 1.7interactive road network modification · 1.7history tree · 1.7
YearPublicationVenuePosition
2025 TraSculptor: Visual Analytics for Enhanced Decision-Making in Road Traffic Planning
abstract
The design of urban road networks significantly influences traffic conditions, underscoring the importance of informed traffic planning. Traffic planning experts rely on specialized platforms to simulate traffic systems, assessing the efficacy of the road network across various states of modifications. Nevertheless, a prevailing issue persists: many existing traffic planning platforms exhibit inefficiencies in flexibly interacting with the road network's structure and attributes and intuitively comparing multiple states during the iterative planning process. This paper introduces TraSculptor, an interactive planning decision-making system. To develop TraSculptor, we identify and address two challenges: interactive modification of road networks and intuitive comparison of multiple network states. For the first challenge, we establish flexible interactions to enable experts to easily and directly modify the road network on the map. For the second challenge, we design a comparison view with a history tree of multiple states and a road-state matrix to facilitate intuitive comparison of road network states. To evaluate TraSculptor, we provided a usage scenario where the Braess's paradox was showcased, invited experts to perform a case study on the Sioux Falls network, and collected expert feedback through interviews.
Zikun Deng, Yuanbang Liu, Mingrui Zhu, Da Xiang, Zicheng Su, Qing-Long Lu, Tobias Schreck, Yi Cai 0001
IEEE Trans. Vis. Comput. Graph.2