Vol-3173
urn:nbn:de:0074-3173-4

Copyright © 2022 for the individual papers by the papers' authors. Copyright © 2022 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).

ATT 2022
Agents in Traffic and Transportation

Twelfth International Workshop on Agents in Traffic and Transportation
co-located with the the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJCAI-ECAI 2022)

Vienna, Austria, July 25, 2022.

Edited by

Ana Lúcia C. Bazzan *
Ivana Dusparic
Marin Lujak *
Giuseppe Vizzari ****

* Institute of Informatics, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
** School of Computer Science and Statistics at Trinity College Dublin, Ireland
*** CETINIA, University Rey Juan Carlos, Spain
**** Department of Informatics, Systems and Communication, Università degli Studi di Milano-Bicocca, Milano, Italy

Table of Contents

Session 1: Traffic Signal Control

Reward Function Design in Multi-Agent Reinforcement Learning for Traffic Signal Control 1-13
Behrad Koohy, Sebastian Stein, Enrico Gerding, Ghaithaa Manla
The Real Deal: A Review of Challenges and Opportunities in Moving Reinforcement Learning-Based Traffic Signal Control Systems Towards Reality 14-31
Rex Chen, Fei Fang, Norman Sadeh
Multiagent Reinforcement Learning for Traffic Signal Control: a k-Nearest Neighbors Based Approach 32-46
Vicente Nejar de Almeida, Ana L. C. Bazzan, Monireh Abdoos

Session 2: On-Demand Mobility and Ride-Sharing

Multiobjective Routing in Sustainable Mobility-On-Demand 47-61
Mengya Liu, Vahid Yazdanpanah, Sebastian Stein, Enrico Gerding
On Balancing Fairness and Efficiency in Routing of Cooperative Vehicle Fleets 62-76
Aitor Lopez Sanchez, Marin Lujak, Frederic Semet, Holger Billhardt
Improving Zonal Fairness While Maintaining Efficiency in Rideshare Matching 77-90
Ashwin Kumar, Yevgeniy Vorobeychik, William Yeoh

Session 3: Autonomous Vehicles and UAVs

Design of AI-Based Lane Changing Models in Connected and Autonomous Vehicles: a Survey 91-107
Bharathkumar Hegde, Melanie Bouroche
Autonomous Drone Interception with Reinforcement Learning 108-123
Adrien Gauffriau, Damien Grasset, David Bertoin, Jayant Sen Gupta

Session 4: Analysis and Modeling of Human Behavior in Traffic Systems

Furthering an Agent-Based Modeling Approach Introducing Affective States Based on Real Data 124-136
Marta Giltri, Stefania Bandini, Francesca Gasparini, Daniela Briola
Machine Learning Analysis of Pedestrians’ Hazard Anticipation from Eye Tracking Data 137-159
Andreas Gregoriades, Loukas Dimitriou, Harris Michail, Maria Pampaka, Michael Georgiades
A Multiobjective Reinforcement Learning Approach to Trip Building 160-174
Guilherme Santos, Ana L. C. Bazzan
Incorporating Social Norms into a Configurable Agent-Based Model of the Decision to Perform Commuting Behaviour 175-193
Robert Greener, Daniel Lewis, Jon Reades, Simon Miles, Steven Cummins
A Machine Learning Pipeline for Extracting Decision-Support Features from Traffic Scenes 194-208
Vitor Fraga, Lincoln Schreiber, Rafael Kunst, Jorge Barbosa, Gabriel Ramos

2022-07-20: submitted by Giuseppe Vizzari, metadata incl. bibliographic data published under Creative Commons CC0
2022-07-26: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|