demonstration

RODGEN: an interactive interface for road network generation

Authors:

Claudia Perez Martinez,

Panagiotis Bouros,

Theodoros ChondrogiannisAuthors Info & Claims

SIGSPATIAL '22: Proceedings of the 30th International Conference on Advances in Geographic Information Systems

Article No.: 54, Pages 1 - 4

https://doi.org/10.1145/3557915.3560989

Published: 22 November 2022 Publication History

Abstract

We present RODGEN, an interactive, graphical user interface for generating road networks that adopts the growth-based model. The first step in the generation process is to construct the backbone of the network by either choosing between a grid-based and a ring-based predefined topology or allowing the users to define a custom one. The backbone divides the space into a number of areas, called neighborhoods. The user can populate neighborhoods either by importing existing road networks or adding roads by hand. Besides generating road networks, our interface also provides a platform for analysis. For this purpose, we employ a general-purpose graph analytics library, which allows the users to compute graph statistics, perform connectivity analysis and execute basic routing tasks.

References

[1]

Albert-Laszlo Barabasi and Reka Albert. 1999. Emergence of Scaling in Random Networks. Science 286, 5439 (1999), 509--512.

[2]

Jan Benes, Alexander Wilkie, and Jaroslav Krivánek. 2014. Procedural Modelling of Urban Road Networks. Comput. Graph. Forum 33, 6 (2014), 132--142.

Digital Library

[3]

Guoning Chen, Gregory Esch, Peter Wonka, Pascal Müller, and Eugene Zhang. 2008. Interactive procedural street modeling. ACM Trans. Graph. 27, 3 (2008).

Digital Library

[4]

Paul Erdos and Alfred Renyi. 1960. On the evolution of random graphs. Publ. Math. Inst. Hungary. Acad. Sci. 5 (1960), 17--61.

[5]

Robert Geisberger, Peter Sanders, Dominik Schultes, and Daniel Delling. 2008. Contraction Hierarchies: Faster and Simpler Hierarchical Routing in Road Networks. In WEA. 319--333.

Digital Library

[6]

Stefan Hartmann, Michael Weinmann, Raoul Wessel, and Reinhard Klein. 2017. StreetGAN: Towards Road Network Synthesis with Generative Adversarial Networks. In WSCG. 133--142.

[7]

George Kelly and Hugh McCabe. 2007. Citygen: An Interactive System for Procedural City Generation. In GDTW. 8--16.

[8]

Lin Ziwen Kelvin and Anand Bhojan. 2020. Procedural Generation of Roads with Conditional Generative Adversarial Networks. In ACM SIGGRAPH. 12:1--12:2.

[9]

Jon M. Kleinberg, Ravi Kumar, Prabhakar Raghavan, Sridhar Rajagopalan, and Andrew Tomkins. 1999. The Web as a Graph: Measurements, Models, and Methods. In COCOON. 1--17.

[10]

Jure Leskovec, Deepayan Chakrabarti, Jon M. Kleinberg, and Christos Faloutsos. 2005. Realistic, Mathematically Tractable Graph Generation and Evolution, Using Kronecker Multiplication. In PKDD. 133--145.

[11]

Takashi Owaki and Takashi Machida. 2020. RoadNetGAN: Generating Road Networks in Planar Graph Representation. In ICONIP. 535--543.

[12]

Yoav I. H. Parish and Pascal Müller. 2001. Procedural modeling of cities. In ACM SIGGRAPH. 301--308.

[13]

Przemyslaw Prusinkiewicz and Aristid Lindenmayer. 1990. The algorithmic beauty of plants. Springer.

[14]

Lars Ruthotto and Eldad Haber. 2021. An Introduction to Deep Generative Modeling. CoRR abs/2103.05180 (2021). https://arxiv.org/abs/2103.05180

[15]

Dimitris Sacharidis and Panagiotis Bouros. 2013. Routing directions: keeping it fast and simple. In ACM SIGSPATIAL. 164--173.

[16]

Kaveh Shahabi and John P. Wilson. 2014. CASPER: Intelligent capacity-aware evacuation routing. Comput. Environ. Urban Syst. 46 (2014), 12--24.

[17]

Philippe Y. R. Sohouenou, Panayotis Christidis, Aris Christodoulou, Luis A. C. Neves, and Davide Lo Presti. 2020. Using a random road graph model to understand road networks robustness to link failures. Int. J. Crit. Infrastructure Prot. 29 (2020), 100353.

[18]

Duncan J. Watts and Steven H. Strogatz. 1998. Collective dynamics of 'small-world' networks. Nature 393, 6684 (1998), 440--442.

[19]

Huichu Zhang, Siyuan Feng, Chang Liu, Yaoyao Ding, Yichen Zhu, Zihan Zhou, Weinan Zhang, Yong Yu, Haiming Jin, and Zhenhui Li. 2019. CityFlow: A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario. In ACM WWW. 3620--3624.

Cited By

Barati HYazici AAlmotahari A(2024)Graph Neural Networks Model to Generate Transportation Test NetworksTransportation Research Record: Journal of the Transportation Research Board10.1177/03611981241233569Online publication date: 28-Mar-2024
https://doi.org/10.1177/03611981241233569

Index Terms

RODGEN: an interactive interface for road network generation
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms
      1. Graphical user interfaces
  2. Visualization
    1. Visualization techniques
      1. Graph drawings
2. Information systems
  1. Information systems applications
    1. Spatial-temporal systems
      1. Geographic information systems

Recommendations

Towards virtualization of user interfaces based on UsiXML
Web3D '05: Proceedings of the tenth international conference on 3D Web technology

A model-based approach is presented for structuring a development process of virtual user interfaces based on UsiXML, a XML-compliant User Interface Description Language. UsiXML provides a Concrete User Interface description that remains independent ...
Transportable Applications Environment (TAE) Plus user interface designer WorkBench
CHI '92: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

TAE Plus was built at NASA's Goddard Space Flight Center to support the building of GUI user interfaces for highly interactive applications, such as realtime processing systems and scientific analysis system. TAE Plus is designed as a productivity tool ...
Design issues related to pie menus for 5-way joysticks
Mobility '07: Proceedings of the 4th international conference on mobile technology, applications, and systems and the 1st international symposium on Computer human interaction in mobile technology

Although linear textual menus are a widely adopted solution in the mobile phone user interfaces, alternatives that would take smaller amount of screen real estate exist, e.g. toolbars and pie menus. Pie menus also provide access to functions with fewer ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

SIGSPATIAL '22: Proceedings of the 30th International Conference on Advances in Geographic Information Systems

November 2022

806 pages

ISBN:9781450395298

DOI:10.1145/3557915

General Chairs:
Matthias Renz
Kiel University, Germany
,
Mohamed Sarwat
Wherobots Inc. / Arizona State University

Copyright © 2022 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Sponsors

SIGSPATIAL: ACM Special Interest Group on Spatial Information

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 November 2022

Check for updates

Author Tags

Qualifiers

Demonstration

Funding Sources

Deutsche Forschungsgemeinschaft (DFG)

Conference

SIGSPATIAL '22

Sponsor:

SIGSPATIAL

SIGSPATIAL '22: The 30th International Conference on Advances in Geographic Information Systems

November 1 - 4, 2022

Washington, Seattle

Acceptance Rates

Overall Acceptance Rate 257 of 1,238 submissions, 21%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

1
Total Citations
View Citations
111
Total Downloads

Downloads (Last 12 months)30
Downloads (Last 6 weeks)1

Reflects downloads up to 05 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Barati HYazici AAlmotahari A(2024)Graph Neural Networks Model to Generate Transportation Test NetworksTransportation Research Record: Journal of the Transportation Research Board10.1177/03611981241233569Online publication date: 28-Mar-2024
https://doi.org/10.1177/03611981241233569

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten