AI for Urban Mobility Workshop
Description of the Workshop
The expected increase in urbanisation in 21st century, coupled with the socio-economic motivation for increasing mobility, is going to push the transport infrastructure well beyond its current capacity. In response, more stringent and intelligent control mechanisms are required to better monitor, exploit, and react to unforeseen conditions.
With an increasing attention towards autonomous vehicles which can assist or even replace human drivers it is important to consider a number of challenges ranging from technological issues to road safety issues. Especially with increasing traffic intensity, especially in urban areas, maintaining high standards for the road safety for all users (e.g., traffic, bikes, pedestrians) is of the utmost importance along with minimisation of congestion and travel times and management of pollution.
Fortunately, a wide variety of data is becoming available to support novel innovations that improve urban mobility and transport. For example, data from traffic cameras, cell phone GPS data, ride-hailing services and even drones has significantly improved the quality and quantity of information available for intelligent real-time traffic solutions. Furthermore, modern (semi-)autonomous vehicles contain a plethora of sensing modalities as well as vehicle to vehicle as well as infrastructure communication abilities.
The aim of this workshop is to bring together researchers who leverage various AI techniques (e.g., Machine Learning, Automated Planning) for innovation in areas of Urban Mobility and Transportation.
Topics
This workshop seeks papers ranging from experience reports to the description of new technology leveraging AI various AI for innovation in any area of Urban Mobility and Transportation, such as (but not limited to):
- Traffic Signal Control
- Vehicle Routing
- Traffic Prediction and Forecasting
- Market-driven Travel Pricing and Routing
- Vehicular Ad-hoc Networks (VANETs)
- Autonomous Driving
- Multi-modal Planning
- On-demand Transport and Ridesharing
- Highway and Intersection Control
- "Big" Traffic Data Management
Important Dates
- Paper submission deadline: November 9, 2020
- Notification: November 30, 2020
- Camera-ready paper submission: December 14,2020
Submission Instructions
Two types of papers can be submitted. Full technical papers with a length up to 8 pages are standard research papers. Short papers with a length between 2 and 4 pages can describe either a particular application, or focus on open challenges. All papers should conform to the AAAI style template.
The submission is done via EasyChair.
Workshop Program - February 8 - 9am - 6pm PST (Vancouver time)
Session 1 9.00am – 10.20am
- Jonathan Morag, Roni Stern, Ariel Felner, Dor Atzmon and Eli Boyarski: Optimality in Online Multi-agent Path Finding (full) Paper
- Guilherme Varela, Pedro Santos, Alberto Sardinha and Francisco Melo: A Methodology for the Development of RL-Based Adaptive Traffic Signal Controllers (full) Paper
- Valentin Starlinger, Cristina de la Rua Lope and Debarghya Ghoshdastidar: Machine Learning Benchmark to Assess the Environmental Impact of Cars (full) Paper
- Jagadish D.N., Arun Chauhan and Lakshman Mahto: Deep Learning Techniques for Autonomous Vehicle Path Prediction (spotlight) Paper
- Luca Romeo, Davide Alessandrini, Eleonora Bicchierini and Emanuele Frontoni: Parking Demand Forecast using Additive Model: a proof of concept on a real parking meters dataset (spotlight) Paper
Invited talk 10.45am – 11.30am
Session 2 12.00pm – 1.00pm
- Guancheng Qiu, Amrita Gupta, Caleb Robinson, Shuo Feng and Bistra Dilkina: Learning-Based Travel Prediction in Urban Road Network Resilience Optimization (full) Paper
- Michael Wilbur, Philip Pugliese, Aron Laszka and Abhishek Dubey: Efficient Data Management for Intelligent Urban Mobility Systems (full) Paper
- Juan Martinez, Ayan Mukhopadhyay, Afiya Ayman, Michael Wilbur, Philip Pugliese, Dan Freudberg, Jonathan Gilligan, Aron Laszka and Abhishek Dubey: Predicting Public Transportation Load to Estimate the Probability of Social Distancing Violations (spotlight) Paper
- Mingxiang Chen, Qichang Chen, Lei Gao, Yilin Chen and Zhecheng Wang: Predicting Geographic Information with Neural Cellular Automata (spotlight) Paper
Invited talk (Alexandre Bayen) 1.30pm - 2.15pm
Session 3 2.40pm – 4.00pm
- Jiajing Ling, Kushagra Chandak and Akshat Kumar: Combining Propositional Logic Based Decision Diagrams with Decision Making in Urban Systems (full) Paper
- Takafumi Okukubo, Yoshiaki Bando, Masaki Onishi and Hiroyasu Ando: Foot Traffic Prediction for Large-Scale Events Based on Pattern-Aware Neural Regression (full) Paper
- Bing Zhao, Rui Xue, Qing Zhang and Yaping Huang: Anomaly detection in Railway transportation based on self-representation and GAN (spotlight) Paper
- Taiga Okamoto, Hiroyasu Ando, Kentaro Wada, Risa Mukai, Yoshifumi Nishiumi and Dai Tamagawa: Predicting Traffic Breakdown in Urban Expressways Based on Simplified Reservoir Computing (spotlight) Paper
- Hao Miao, Senzhang Wang, Meiyue Zhang, Diansheng Guo, Funing Sun and Fan Yang: Deep Multi-View Channel-Wise Spatio-Temporal Network for Traffic Flow Prediction (spotlight) Paper
- Vishal Vinod and Savita Choudhary: Towards Practical and Efficient Computer Vision Models for Extreme-Weather Scenarios in Urban Mobility (spotlight) Paper
Invited talk 4.15m – 5.00pm
Invited talk 5.15am – 6.00pm
Workshop Organizers
- Lukas Chrpa, Czech Technical University in Prague
- Mauro Vallati, University of Huddersfield
- Scott Sanner, University of Toronto
- Stephen F. Smith, Carnegie Mellon University
- Baher Abdulhai, University of Toronto