IWCTS 2018

11th International Workshop on Computational Transportation Science (IWCTS 2018)

Overview

The 11th International Workshop on Computational Transportation Science (IWCTS 2018) is particularly timely given the prominence of connected automated vehicles technologies in the global auto industry’s near-term growth strategies, of big data analytics and unprecedented access to sensing data of mobility, and of integration of this analytics into the optimization of mobility and transport. These developments are deeply computational. We will build upon the success of previous workshops to continue to focus on connectivity, protocols, computation, knowledge discovery, and technology aspects of transportation systems while welcoming research papers in computer science, transportation science, urban and regional planning, the automotive arena, civil engineering, robotics, geography, geo-informatics, and other related disciplines. We will be organizing a panel alongside paper presentations / keynote. We seek to invite eminent people from industry, academia, and laboratories.

Purpose

Computational methods for Transportation Science are the drivers for intelligent transportation systems, and thus essence for a sustainable future of cities with regard to urban mobility (people) and transport (freight). The fundamentals of these computational methods are rooted in space and time, and thus at the core of ACM SIGSPATIAL. In fact, the conference itself had always a significant portion of papers dedicated to these topics. A focused workshop at the beginning of the conference can:

  • Raise further the profile of ACM SIGSPATIAL in the transportation and operation research communities;
  • Provide a dedicated discussion forum to this significant application field of computation and geographic information science;
  • Attract further participants to the conference both by reaching out to non-traditional conference participants and by accepting short papers.

We are committed to provide an intellectual, scientific, and industry platform to share findings, discuss directions, and develop networks through this workshop. Integrated with the conference, the workshop will enable the whole ACM SIGSPATIAL community to benefit from crosspollination of new ideas and discoveries.

Program Schedule

Start
End
Description
Time Slots

09:00

09:15

Opening Remarks Foreword

09:20

11:00

Session 1

09:20

09:40

Group Diagrams for Representing Trajectories
Maike Buchin, TU Dortmund; Bernhard Kilgus, Ruhr University Bochum; Andrea Kölzsch, Max Planck Institute for Ornithology Rad

09:40

10:00

Is Euclidean Distance Really that Bad with Road Networks?
Hua Hua, University of Melbourne; Hairuo Xie, University of Melbourne; Egemen Tanin,University of Melbourne

10:00

10:20

Using Local and Global Divergence Measures to Identify Road Similarity in Different Road Network Datasets
Mousa Almotairi, University of Texas at Arlington; Tariq Alsahfi, University of Texas at Arlington; Ramez Elmasri, University of Texas at Arlington

10:20

10:40

A Multi-layer CRF Based Methodology for Improving Crowdsourced Street Semantics
Musfira Jilani, Dublin City University; Padraig Corcoran, Cardiff University; Michela Bertolotto, University College Dublin

10:40

11:00

Driving in unknown areasFrom UAV images to map for autonomous vehicles
Hai Huang, Bundeswehr University Munich; Patrick Burger, Bundeswehr University Munich; Matthias Schmitz, Bundeswehr University Munich; Lukas Roth, Bundeswehr University Munich; Hans-Joachim Wuensche, Bundeswehr University Munich; Helmut Mayer, Bundeswehr University Munich

11:00

11:30

Coffee Break

11:30

13:00

Invited Talk

13:00

14:00

Lunch

14:00

16:00

Session 2

14:00

14:20

Recognizing Spatio-Temporal Traffic Patterns at Intersections Using Self-Organizing Maps
Richard Brunauer, Salzburg Research; Nina Schmitzberger, Salzburg Research; Karl Rehrl, Salzburg Research

14:20

14:40

Optimizing Bus Stop Spacing Using the Simulated Annealing Algorithm with Spatial Interaction Coverage Model
Yunlei Liang, University of Wisconsin; Song Gao, University of Wisconsin; Tianyu Wu, University of Waterloo; Sujing Wang, University of Waterloo; Yuhao Wu, University of Waterloo

14:40

15:00

Predicting Traffic Congestion Propagation PatternsA Propagation Graph Approach
Haoyi Xiong, The University of Iowa; Amin Vahedian, The University of Iowa; Xun Zhou, The University of Iowa; Yanhua Li, Worcester Polytechnic Institute; Jun Luo, Lenovo Group Limited

15:00

15:55

Panel Discussion

15:55

16:00

Closing Remarks

16:00

16:30

Coffee Break

Workshop Organizers

Gautam S. Thakur

Sabine Storandt

Submission Instructions

All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:

  • Full papers (up to 10 pages)
  • Short papers and Position Papers (up to 4 pages)
  • Demo Papers (up to 4 pages)

Papers must be in ACM SIG format (US Letter size, 8.5 x 11 inches) including text, figures and references.

Accepted papers will be published in the ACM digital library under the condition that at least one author has registered for both the main SIGSPATIAL conference and the workshop, attends the workshop, and presents the accepted paper in the workshop. Otherwise, the accepted paper will not appear in the workshop proceedings or in the ACM Digital Library version of the workshop proceedings.

Submit a paper

Important Dates

Paper submission due: September 8, 2018 (CDT)

Notification to the authors: September 30, 2018

Camera ready papers due: October 10, 2018

IWCTS Workshop: November 6, 2018

ACM SIGSPATIAL Conference: November 6–November 9, 2018

Keynote Speaker

Professor Lars Kulik
University of Melbourne

Title: VIP: Volunteer, Improve and Protect - Opportunities for Future Transportation Services

Abstract: Computational approaches to harness the abundance of real-time traffic data for better transportation services are more pertinent than ever. Pedestrians, cyclists, and vehicles generate a large diversity of transport-related data that can enable novel and personalized transportation services. This volunteered data can be used to improve the data quality while it needs to be carefully protected as it is sensitive data. At the same time, this data leads to volunteered services such as ride-sharing or hitchhiking, can lead to improved experiences for transportation users which again need to be protected.

In my talk I will outline various opportunities how the use of real-time traffic data can enable more effective services. A particular focus is on ridesharing and hitchhiking, protecting user data that is either volunteered or generated while using transportation services, and realistic modelling of real-time traffic for entire cities, including microscopic traffic simulations as well as truck platooning.

Program Committee