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from_the_proposal.bib
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% Put BibTeX entries other than your own work in this file
@article{wang2020multi,
title={Multi-AI competing and winning against humans in iterated Rock-Paper-Scissors game},
author={Wang, Lei and Huang, Wenbin and Li, Yuanpeng and Evans, Julian and He, Sailing},
journal={Scientific Reports},
volume={10},
number={1},
pages={1--8},
year={2020},
publisher={Nature Publishing Group}
}
@article{mehr2019will,
title={How will the presence of autonomous vehicles affect the equilibrium state of traffic networks?},
author={Mehr, Negar and Horowitz, Roberto},
journal={IEEE Transactions on Control of Network Systems},
volume={7},
number={1},
pages={96--105},
year={2019},
publisher={IEEE}
}
@phdthesis{carvalho2020uber,
title={Uber, a path for profitability or a market misperception?--Advanced TechnologiesGroup and Other Technology Programs},
author={Carvalho, Maria Laura Nunes},
year={2020}
}
@article{heuillet2021explainability,
title={Explainability in deep reinforcement learning},
author={Heuillet, Alexandre and Couthouis, Fabien and Diaz-Rodriguez, Natalia},
journal={Knowledge-Based Systems},
volume={214},
pages={106685},
year={2021},
publisher={Elsevier}
}
@article{cats2020learning,
title={Learning and adaptation in dynamic transit assignment models for congested networks},
author={Cats, Oded and West, Jens},
journal={Transportation Research Record},
volume={2674},
number={1},
pages={113--124},
year={2020},
publisher={SAGE Publications Sage CA: Los Angeles, CA}
}
@article{gunning2019xai,
title={XAI—Explainable artificial intelligence},
author={Gunning, David and Stefik, Mark and Choi, Jaesik and Miller, Timothy and Stumpf, Simone and Yang, Guang-Zhong},
journal={Science Robotics},
volume={4},
number={37},
year={2019},
publisher={Science Robotics}
}
@article{brockman2016openai,
title={Openai gym},
author={Brockman, Greg and Cheung, Vicki and Pettersson, Ludwig and Schneider, Jonas and Schulman, John and Tang, Jie and Zaremba, Wojciech},
journal={arXiv preprint arXiv:1606.01540},
year={2016}
}
@article{zhao2020prediction,
title={Prediction and behavioral analysis of travel mode choice: A comparison of machine learning and logit models},
author={Zhao, Xilei and Yan, Xiang and Yu, Alan and Van Hentenryck, Pascal},
journal={Travel behaviour and society},
volume={20},
pages={22--35},
year={2020},
publisher={Elsevier}
}
@article{millard2018pedestrians,
title={Pedestrians, autonomous vehicles, and cities},
author={Millard-Ball, Adam},
journal={Journal of planning education and research},
volume={38},
number={1},
pages={6--12},
year={2018},
publisher={SAGE Publications Sage CA: Los Angeles, CA}
}
@article{liu2017distributed,
title={Distributed conflict resolution for connected autonomous vehicles},
author={Liu, Changliu and Lin, Chung-Wei and Shiraishi, Shinichi and Tomizuka, Masayoshi},
journal={IEEE Transactions on Intelligent Vehicles},
volume={3},
number={1},
pages={18--29},
year={2017},
publisher={IEEE}
}
@article{fielbaum2021anticipatory,
title={Anticipatory routing methods for an on-demand ridepooling mobility system},
author={Fielbaum, Andres and Kronmueller, Maximilian and Alonso-Mora, Javier},
journal={Transportation},
pages={1--42},
year={2021},
publisher={Springer}
}
@article{alonso2017demand,
title={On-demand high-capacity ride-sharing via dynamic trip-vehicle assignment},
author={Alonso-Mora, Javier and Samaranayake, Samitha and Wallar, Alex and Frazzoli, Emilio and Rus, Daniela},
journal={Proceedings of the National Academy of Sciences},
volume={114},
number={3},
pages={462--467},
year={2017},
publisher={National Acad Sciences}
}
@article{weyl2010price,
title={A price theory of multi-sided platforms},
author={Weyl, E Glen},
journal={American Economic Review},
volume={100},
number={4},
pages={1642--72},
year={2010}
}
@article{arentze2000albatross,
title={ALBATROSS: multiagent, rule-based model of activity pattern decisions},
author={Arentze, Theo and Hofman, Frank and van Mourik, Henk and Timmermans, Harry},
journal={Transportation Research Record},
volume={1706},
number={1},
pages={136--144},
year={2000},
publisher={SAGE Publications Sage CA: Los Angeles, CA}
}
@Article{smartcities4010006,
AUTHOR = {Moreno, Carlos and Allam, Zaheer and Chabaud, Didier and Gall, Catherine and Pratlong, Florent},
TITLE = {Introducing the "15-Minute City": Sustainability, Resilience and Place Identity in Future Post-Pandemic Cities},
JOURNAL = {Smart Cities},
VOLUME = {4},
YEAR = {2021},
NUMBER = {1},
PAGES = {93--111},
ISSN = {2624-6511}}
@article{fielbaum2021split,
title={How to split the costs among travellers sharing a ride? Aligning system's optimum with users' equilibrium},
author={Fielbaum, Andres and Kucharski, Rafal and Cats, Oded and Alonso-Mora, Javier},
journal={European Journal of Operational Research Follow journal},
year={2021}
}
@article{team2021open,
title={Open-ended learning leads to generally capable agents},
author={Stooke, Adam and Mahajan, Anuj and Barros, Catarina and Deck, Charlie and Bauer, Jakob and Sygnowski, Jakub and Trebacz, Maja and Jaderberg, Max and Mathieu, Michael and others},
journal={arXiv preprint arXiv:2107.12808},
year={2021}
}
@article{ye2019evaluating,
title={Evaluating the impact of connected and autonomous vehicles on traffic safety},
author={Ye, Lanhang and Yamamoto, Toshiyuki},
journal={Physica A: Statistical Mechanics and its Applications},
volume={526},
pages={121009},
year={2019},
publisher={Elsevier}
}
@article{hancock2019future,
title={On the future of transportation in an era of automated and autonomous vehicles},
author={Hancock, Peter A and Nourbakhsh, Illah and Stewart, Jack},
journal={Proceedings of the National Academy of Sciences},
volume={116},
number={16},
pages={7684--7691},
year={2019},
publisher={National Acad Sciences}
}
@article{schwarting2019social,
title={Social behavior for autonomous vehicles},
author={Schwarting, Wilko and Pierson, Alyssa and Alonso-Mora, Javier and Karaman, Sertac and Rus, Daniela},
journal={Proceedings of the National Academy of Sciences},
volume={116},
number={50},
pages={24972--24978},
year={2019},
publisher={National Acad Sciences}
}
@article{wang2019multiclass,
title={Multiclass traffic assignment model for mixed traffic flow of human-driven vehicles and connected and autonomous vehicles},
author={Wang, Jian and Peeta, Srinivas and He, Xiaozheng},
journal={Transportation Research Part B: Methodological},
volume={126},
pages={139--168},
year={2019},
publisher={Elsevier}
}
@article{mnih2015human,
title={Human-level control through deep reinforcement learning},
author={Mnih, Volodymyr and Kavukcuoglu, Koray and Silver, David and Rusu, Andrei A and Veness, Joel and Bellemare, Marc G and Graves, Alex and Riedmiller, Martin and Fidjeland, Andreas K and Ostrovski, Georg and others},
journal={nature},
volume={518},
number={7540},
pages={529--533},
year={2015},
publisher={Nature Publishing Group}
}
@article{vinyals2019grandmaster,
title={Grandmaster level in StarCraft II using multi-agent reinforcement learning},
author={Vinyals, Oriol and Babuschkin, Igor and Czarnecki, Wojciech M and Mathieu, Micha{\"e}l and Dudzik, Andrew and Chung, Junyoung and Choi, David H and Powell, Richard and Ewalds, Timo and Georgiev, Petko},
journal={Nature},
volume={575},
number={7782},
pages={350--354},
year={2019},
publisher={Nature Publishing Group}
}
@article{silver2017mastering,
title={Mastering the game of go without human knowledge},
author={Silver, David and Schrittwieser, Julian and Simonyan, Karen and Antonoglou, Ioannis and Huang, Aja and Guez, Arthur and Hubert, Thomas and Baker, Lucas and Lai, Matthew and Bolton, Adrian},
journal={nature},
volume={550},
number={7676},
pages={354--359},
year={2017},
publisher={Nature Publishing Group}
}
@inproceedings{pandey2021disparate,
title={Disparate Impact of Artificial Intelligence Bias in Ridehailing Economy's Price Discrimination Algorithms},
author={Pandey, Akshat and Caliskan, Aylin},
booktitle={Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society},
pages={822--833},
year={2021}
}
@article{iryo2019properties,
title={Properties of equilibria in transport problems with complex interactions between users},
author={Iryo, Takamasa and Watling, David},
journal={Transportation Research Part B: Methodological},
volume={126},
pages={87--114},
year={2019},
publisher={Elsevier}
}
@article{liu2018equilibrium,
title={An equilibrium analysis of commuter parking in the era of autonomous vehicles},
author={Liu, Wei},
journal={Transportation Research Part C: Emerging Technologies},
volume={92},
pages={191--207},
year={2018},
publisher={Elsevier}
}
@article{pawlak2017framework,
title={A framework for joint modelling of activity choice, duration, and productivity while travelling},
author={Pawlak, Jacek and Polak, John W and Sivakumar, Aruna},
journal={Transportation Research Part B: Methodological},
volume={106},
pages={153--172},
year={2017},
publisher={Elsevier}
}
@article{drabicki2021modelling,
title={Modelling the effects of real-time crowding information in urban public transport systems},
author={Drabicki, Arkadiusz and Kucharski, Rafa{\l} and Cats, Oded and Szarata, Andrzej},
journal={Transportmetrica A: Transport Science},
volume={17},
number={4},
pages={675--713},
year={2021},
publisher={Taylor \& Francis}
}
@article{bazzan2019aligning,
title={Aligning individual and collective welfare in complex socio-technical systems by combining metaheuristics and reinforcement learning},
author={Bazzan, Ana LC},
journal={Engineering Applications of Artificial Intelligence},
volume={79},
pages={23--33},
year={2019},
publisher={Elsevier}
}
@inproceedings{wu2017emergent,
title={Emergent behaviors in mixed-autonomy traffic},
author={Wu, Cathy and Kreidieh, Aboudy and Vinitsky, Eugene and Bayen, Alexandre M},
booktitle={Conference on Robot Learning},
pages={398--407},
year={2017},
organization={PMLR}
}
@article{zhuge2021improvement,
title={An improvement in MATSim computing time for large-scale travel behaviour microsimulation},
author={Zhuge, Chengxiang and Bithell, Mike and Shao, Chunfu and Li, Xia and Gao, Jian},
journal={Transportation},
volume={48},
number={1},
pages={193--214},
year={2021},
publisher={Springer}
}
@inproceedings{balac2021simulation,
title={Simulation of intermodal shared mobility in the San Francisco Bay Area using MATSim},
author={Balac, Milos and H{\"o}rl, Sebastian},
booktitle={2021 IEEE International Intelligent Transportation Systems Conference (ITSC)},
pages={3278--3283},
year={2021},
organization={IEEE}
}
@article{van2006impact,
title={The impact of cooperative adaptive cruise control on traffic-flow characteristics},
author={Van Arem, Bart and Van Driel, Cornelie JG and Visser, Ruben},
journal={IEEE Transactions on intelligent transportation systems},
volume={7},
number={4},
pages={429--436},
year={2006},
publisher={IEEE}
}
@article{stern2018dissipation,
title={Dissipation of stop-and-go waves via control of autonomous vehicles: Field experiments},
author={Stern, Raphael E and Cui, Shumo and Delle Monache, Maria Laura and Bhadani, Rahul and Bunting, Matt and Churchill, Miles and Hamilton, Nathaniel and Pohlmann, Hannah and Wu, Fangyu and Piccoli, Benedetto and others},
journal={Transportation Research Part C: Emerging Technologies},
volume={89},
pages={205--221},
year={2018},
publisher={Elsevier}
}
@article{wardrop1952road,
title={Road paper. some theoretical aspects of road traffic research.},
author={Wardrop, John Glen},
journal={Proceedings of the institution of civil engineers},
volume={1},
number={3},
pages={325--362},
year={1952},
publisher={Thomas Telford-ICE Virtual Library}
}
@article{trb,
author = {Guido Cantelmo and Rafał Kucharski and Constantinos Antoniou},
title ={Low-Dimensional Model for Bike-Sharing Demand Forecasting that Explicitly Accounts for Weather Data},
journal = {Transportation Research Record},
volume = {2674},
number = {8},
pages = {132-144},
year = {2020},
abstract = { With the increasing availability of big, transport-related datasets, detailed data-driven mobility analysis is becoming possible. Trips with their origins, destinations, and travel times are now collected in publicly available databases, allowing for detailed demand forecasting with methods exploiting big and accurate data. In this paper, we predict the demand pattern of New York City bikes with a low-dimensional approach utilizing three-level data clustering. We use historical demand data along with temperature and precipitation to first aggregate and then decompose data to obtain meaningful clusters. The core of this approach lies in the proposed clustering technique, which reduces the dimension of the problem and, differently from other machine learning techniques, requires limited assumptions on the model or its parameters. The proposed method allows, for the given temperature and precipitation method, to obtain expected vector of movement (mean number and direction of trips) for each zone. In this paper, we synthesize more than 17 million trips into daily and zonal vectors of movement, which combined with weather data allow forecasting of the trip demand. The method allows us to predict the demand with over 75\% accuracy, as shown in series of experiments in which various settings and parameterizations are validated against 25\% holdout data. },
keywords = {journalpaper}
}
}
@article{cantarella2017transportation,
title={Transportation Systems with Autonomous Vehicles: models and algorithms for equilibrium assignment},
author={Cantarella, GE and Di Febbraro, A},
journal={Transportation Research Procedia},
volume={27},
pages={349--356},
year={2017},
publisher={Elsevier}
}
@article{narayanan2020shared,
title={Shared autonomous vehicle services: A comprehensive review},
author={Narayanan, Santhanakrishnan and Chaniotakis, Emmanouil and Antoniou, Constantinos},
journal={Transportation Research Part C: Emerging Technologies},
volume={111},
pages={255--293},
year={2020},
publisher={Elsevier}
}
@article{talebpour2016influence,
title={Influence of connected and autonomous vehicles on traffic flow stability and throughput},
author={Talebpour, Alireza and Mahmassani, Hani S},
journal={Transportation Research Part C: Emerging Technologies},
volume={71},
pages={143--163},
year={2016},
publisher={Elsevier}
}
@article{abenoza2017travel,
title={Travel satisfaction with public transport: Determinants, user classes, regional disparities and their evolution},
author={Abenoza, Roberto F and Cats, Oded and Susilo, Yusak O},
journal={Transportation Research Part A: Policy and Practice},
volume={95},
pages={64--84},
year={2017},
publisher={Elsevier}
}
@incollection{krajzewicz2010traffic,
title={Traffic simulation with SUMO--simulation of urban mobility},
author={Krajzewicz, Daniel},
booktitle={Fundamentals of traffic simulation},
pages={269--293},
year={2010},
publisher={Springer}
}
@article{gentile2016modelling,
title={Modelling public transport passenger flows in the era of intelligent transport systems},
author={Gentile, Guido and N{\"o}kel, Klaus},
journal={Springer Tracts on Transportation and Traffic},
volume={10},
year={2016},
publisher={Springer}
}
@article{wu2017flow,
title={Flow: Architecture and benchmarking for reinforcement learning in traffic control},
author={Wu, Cathy and Kreidieh, Aboudy and Parvate, Kanaad and Vinitsky, Eugene and Bayen, Alexandre M},
journal={arXiv preprint arXiv:1710.05465},
volume={10},
year={2017}
}
@article{ye2018exploration,
title={Exploration of day-to-day route choice models by a virtual experiment},
author={Ye, Hongbo and Xiao, Feng and Yang, Hai},
journal={Transportation Research Part C: Emerging Technologies},
volume={94},
pages={220--235},
year={2018},
publisher={Elsevier}
}
@article{kucharski2014indirect,
title={Indirect observation of rerouting phenomena in traffic networks--case study of Warsaw bridges},
author={Kucharski, Rafa{\l} and Gentile, Guido},
journal={Archives of Transport},
volume={32},
year={2014}
}
@article{icm,
title={Simulation of rerouting phenomena in dynamic traffic assignment with the information comply model},
author={Kucharski, Rafa{\l} and Gentile, Guido},
journal={Transportation Research Part B: Methodological},
volume={126},
pages={414--441},
year={2019},
publisher={Elsevier}
}
@article{djavadian2017agent,
title={An agent-based day-to-day adjustment process for modeling ‘Mobility as a Service’with a two-sided flexible transport market},
author={Djavadian, Shadi and Chow, Joseph YJ},
journal={Transportation research part B: methodological},
volume={104},
pages={36--57},
year={2017},
publisher={Elsevier}
}
@article{Huang2020,
year = {2020},
month = oct,
publisher = {Institution of Engineering and Technology ({IET})},
volume = {14},
number = {18},
pages = {2752--2763},
author = {Chao Huang and Chen Lv and Fazel Naghdy and Haiping Du},
title = {Reference-free approach for mitigating human{\textendash}machine conflicts in shared control of automated vehicles},
journal = {{IET} Control Theory {\&} Applications}
}
@article{LU201976,
title = {Trajectory-based traffic management inside an autonomous vehicle zone},
journal = {Transportation Research Part B: Methodological},
volume = {120},
pages = {76-98},
year = {2019},
issn = {0191-2615},
author = {Gongyuan Lu and Yu(Marco) Nie and Xiaobo Liu and Denghui Li},
keywords = {Trajectory-based traffic management, Autonomous vehicles, Mixed integer program, Rolling horizon algorithm},
abstract = {This paper studies a trajectory-based traffic management (TTM) problem for the purpose of managing traffic in a road facility reserved exclusively for autonomous vehicles (AV). The base TTM model aims to find optimal trajectories for multiple AVs while resolving inter-vehicle conflicts in the most generic way. The model is formulated as a mixed integer program (MIP) that can be solved using off-the-shelf solvers. To improve computational efficiency, a specialized algorithm based on the rolling horizon approach is also developed. We then show that the base TTM model can be easily extended to first accommodate scheduling decisions (the TTMS model) and to further impose equity constraints (the TTMSE model). For the simplest network and homogeneous users, solutions to TTMS and TTMSE are similar, respectively, to system optimal (SO) and user equilibrium (UE) solutions of Vickrey’s bottleneck model. Numerical experiments highlight TTM’s ability to simultaneously generate optimal trajectories for multiple vehicles. They also show that, while solving TTM exactly is computationally demanding, obtaining good approximate solutions can be accomplished efficiently by the rolling horizon algorithm.}
}
@article{alonso2018cooperative,
title={Cooperative collision avoidance for nonholonomic robots},
author={Alonso-Mora, Javier and Beardsley, Paul and Siegwart, Roland},
journal={IEEE Transactions on Robotics},
volume={34},
number={2},
pages={404--420},
year={2018},
publisher={IEEE}
}
@article{levin2017congestion,
title={Congestion-aware system optimal route choice for shared autonomous vehicles},
author={Levin, Michael W},
journal={Transportation Research Part C: Emerging Technologies},
volume={82},
pages={229--247},
year={2017},
publisher={Elsevier}
}
@article{lazar2021learning,
title={Learning how to dynamically route autonomous vehicles on shared roads},
author={Lazar, Daniel A and B{\i}y{\i}k, Erdem and Sadigh, Dorsa and Pedarsani, Ramtin},
journal={Transportation research part C: emerging technologies},
volume={130},
pages={103258},
year={2021},
publisher={Elsevier}
}
@article{teixeira2020simulating,
title={Simulating collective decision-making for autonomous vehicles coordination enabled by vehicular networks: A computational social choice perspective},
author={Teixeira, Miguel and d’Orey, Pedro M and Kokkinogenis, Zafeiris},
journal={Simulation Modelling Practice and Theory},
volume={98},
pages={101983},
year={2020},
publisher={Elsevier}
}
@article{balmer2008agent,
title={Agent-based simulation of travel demand: Structure and computational performance of MATSim-T},
author={Balmer, Michael and Meister, Konrad and Rieser, Marcel and Nagel, Kai and Axhausen, Kay W},
journal={Arbeitsberichte Verkehrs-und Raumplanung},
volume={504},
year={2008},
publisher={ETH Zurich, Institute for Transport Planning and Systems}
}
@article{klein2018agent,
title={An agent-based model of the emergence of cooperation and a fair and stable system optimum using ATIS on a simple road network},
author={Klein, Ido and Levy, Nadav and Ben-Elia, Eran},
journal={Transportation research part C: emerging technologies},
volume={86},
pages={183--201},
year={2018},
publisher={Elsevier}
}
@article{hopkins2021identify,
title={How to identify win--win interventions that benefit human health and conservation},
author={Hopkins, Skylar R and Sokolow, Susanne H and Buck, Julia C and De Leo, Giulio A and Jones, Isabel J and Kwong, Laura H and LeBoa, Christopher and Lund, Andrea J and MacDonald, Andrew J and Nova, Nicole},
journal={Nature Sustainability},
volume={4},
number={4},
pages={298--304},
year={2021},
publisher={Nature Publishing Group}
}
@article{mariotte2021assessing,
title={Assessing traveler compliance with the social optimum: A stated preference study},
author={Mariotte, Guilhem and Leclercq, Ludovic and Ramirez, Humberto Gonzalez and Krug, Jean and Becarie, C{\'e}cile},
journal={Travel behaviour and society},
volume={23},
pages={177--191},
year={2021},
publisher={Elsevier}
}
@article{bachrach2020negotiating,
title={Negotiating team formation using deep reinforcement learning},
author={Bachrach, Yoram and Everett, Richard and Hughes, Edward and Lazaridou, Angeliki and Leibo, Joel Z and Lanctot, Marc and Johanson, Michael and Czarnecki, Wojciech M and Graepel, Thore},
journal={Artificial Intelligence},
volume={288},
pages={103356},
year={2020},
publisher={Elsevier}
}
@article{lin2019pareto,
title={Pareto multi-task learning},
author={Lin, Xi and Zhen, Hui-Ling and Li, Zhenhua and Zhang, Qing-Fu and Kwong, Sam},
journal={Advances in neural information processing systems},
volume={32},
pages={12060--12070},
year={2019}
}
@inproceedings{schmidt2021can,
title={Can You Trust Your Autonomous Car? Interpretable and Verifiably Safe Reinforcement Learning},
author={Schmidt, Lukas M and Kontes, Georgios and Plinge, Axel and Mutschler, Christopher},
booktitle={2021 IEEE Intelligent Vehicles Symposium (IV)},
pages={171--178},
year={2021},
organization={IEEE}
}
@article{adadi2018peeking,
title={Peeking inside the black-box: a survey on explainable artificial intelligence (XAI)},
author={Adadi, Amina and Berrada, Mohammed},
journal={IEEE access},
volume={6},
pages={52138--52160},
year={2018},
publisher={IEEE}
}
@article{kagho2020agent,
title={Agent-based models in transport planning: Current state, issues, and expectations},
author={Kagho, Grace O and Balac, Milos and Axhausen, Kay W},
journal={Procedia Computer Science},
volume={170},
pages={726--732},
year={2020},
publisher={Elsevier}
}
@article{klein2018emergence,
title={Emergence of cooperative route-choice: a model and experiment of compliance with system-optimal ATIS},
author={Klein, Ido and Ben-Elia, Eran},
journal={Transportation research part F: traffic psychology and behaviour},
volume={59},
pages={348--364},
year={2018},
publisher={Elsevier}
}
@article{shou2020reward,
title={Reward design for driver repositioning using multi-agent reinforcement learning},
author={Shou, Zhenyu and Di, Xuan},
journal={Transportation research part C: emerging technologies},
volume={119},
pages={102738},
year={2020},
publisher={Elsevier}
}
@inproceedings{holler2019deep,
title={Deep reinforcement learning for multi-driver vehicle dispatching and repositioning problem},
author={Holler, John and Vuorio, Risto and Qin, Zhiwei and Tang, Xiaocheng and Jiao, Yan and Jin, Tiancheng and Singh, Satinder and Wang, Chenxi and Ye, Jieping},
booktitle={2019 IEEE International Conference on Data Mining (ICDM)},
pages={1090--1095},
year={2019},
organization={IEEE}
}
@inproceedings{chremos2020game,
title={A game-theoretic analysis of the social impact of connected and automated vehicles},
author={Chremos, Ioannis Vasileios and Beaver, Logan E and Malikopoulos, Andreas A},
booktitle={2020 IEEE 23rd ITSC},
pages={1--6},
year={2020},
organization={IEEE}
}
@article{anil2020travel,
author = {Anil NP Koushik and M. Manoj and N. Nezamuddin},
title = {Machine learning applications in activity-travel behaviour research: a review},
journal = {Transport Reviews},
volume = {40},
number = {3},
pages = {288-311},
year = {2020},
publisher = {Routledge}
}
@article{aradi2020survey,
title={Survey of deep reinforcement learning for motion planning of autonomous vehicles},
author={Aradi, Szil{\'a}rd},
journal={IEEE Transactions on Intelligent Transportation Systems},
year={2020},
publisher={IEEE}
}
@article{moreira2016online,
title={An online learning approach to eliminate Bus Bunching in real-time},
author={Moreira-Matias, Lu{\'\i}s and Cats, Oded and Gama, Jo{\~a}o and Mendes-Moreira, Jo{\~a}o and De Sousa, Jorge Freire},
journal={Applied Soft Computing},
volume={47},
pages={460--482},
year={2016},
publisher={Elsevier}
}
@article{bonnefon2016social,
title={The social dilemma of autonomous vehicles},
author={Bonnefon, Jean-Fran{\c{c}}ois and Shariff, Azim and Rahwan, Iyad},
journal={Science},
volume={352},
number={6293},
pages={1573--1576},
year={2016},
publisher={American Association for the Advancement of Science}
}
@inproceedings{zhang2016optimal,
title={Optimal control and coordination of connected and automated vehicles at urban traffic intersections},
author={Zhang, Yue J and Malikopoulos, Andreas A and Cassandras, Christos G},
booktitle={2016 American Control Conference (ACC)},
pages={6227--6232},
year={2016},
organization={IEEE}
}
@inproceedings{chen2020toward,
title={Toward a thousand lights: Decentralized deep reinforcement learning for large-scale traffic signal control},
author={Chen, Chacha and Wei, Hua and Xu, Nan and Zheng, Guanjie and Yang, Ming and Xiong, Yuanhao and Xu, Kai and Li, Zhenhui},
booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
volume={34},
number={04},
pages={3414--3421},
year={2020}
}
@inproceedings{sun2018probabilistic,
title={Probabilistic prediction of interactive driving behavior via hierarchical inverse reinforcement learning},
author={Sun, Liting and Zhan, Wei and Tomizuka, Masayoshi},
booktitle={2018 21st International Conference on Intelligent Transportation Systems (ITSC)},
pages={2111--2117},
year={2018},
organization={IEEE}
}
@article{klein2016emergence,
title={Emergence of cooperation in congested road networks using ICT and future and emerging technologies: A game-based review},
author={Klein, Ido and Ben-Elia, Eran},
journal={Transportation Research Part C: Emerging Technologies},
volume={72},
pages={10--28},
year={2016},
publisher={Elsevier}
}
@article{jaderberg2019human,
title={Human-level performance in 3D multiplayer games with population-based reinforcement learning},
author={Jaderberg, Max and Czarnecki, Wojciech M and Dunning, Iain and Marris, Luke and Lever, Guy and Castaneda, Antonio Garcia and Beattie, Charles and Rabinowitz, Neil C and Morcos, Ari S and Ruderman, Avraham and others},
journal={Science},
volume={364},
number={6443},
pages={859--865},
year={2019},
publisher={American Association for the Advancement of Science}
}
@inproceedings{chen2015peeking,
title={Peeking beneath the hood of uber},
author={Chen, Le and Mislove, Alan and Wilson, Christo},
booktitle={Proceedings of the 2015 internet measurement conference},
pages={495--508},
year={2015}
}
@article{zhou2020reinforcement,
title={A reinforcement learning scheme for the equilibrium of the in-vehicle route choice problem based on congestion game},
author={Zhou, Bo and Song, Qiankun and Zhao, Zhenjiang and Liu, Tangzhi},
journal={Applied Mathematics and Computation},
volume={371},
pages={124895},
year={2020},
publisher={Elsevier}
}
@techreport{cohen2016using,
title={Using big data to estimate consumer surplus: The case of uber},
author={Cohen, Peter and Hahn, Robert and Hall, Jonathan and Levitt, Steven and Metcalfe, Robert},
year={2016},
institution={National Bureau of Economic Research}
}
@inproceedings{uberdyn,
author = {Chen, M. Keith},
title = {Dynamic Pricing in a Labor Market: Surge Pricing and Flexible Work on the Uber Platform},
year = {2016},
isbn = {9781450339360},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
abstract = {In many markets, new technologies allow traditional jobs to be divided into discrete tasks that are widely distributed across workers and dynamically priced given prevailing supply and demand conditions. This "sharing" or "gig" economy represents a more flexible work system, and is most common in two-sided markets in which a firm acts as a platform to connect service providers and consumers. One prominent example of this is the ride-sharing company Uber, which connects riders and driver-partners, and dynamically prices trips using a system known as "surge" pricing. In this talk, I discuss the practical problems of designing such a dynamic pricing system, how that dynamic pricing coordinates workers who can now earn compensation on a flexible schedule, and more broadly how the "gig" economy is evolving and growing as a form of market organization.},
booktitle = {Proceedings of the 2016 ACM Conference on Economics and Computation},
pages = {455},
numpages = {1},
keywords = {flexible work, sharing economy, uber, dynamic pricing, gig economy, surge pricing},
location = {Maastricht, The Netherlands},
series = {EC '16}
}
@article{lu2018dynamic,
title={A dynamic pricing demand response algorithm for smart grid: reinforcement learning approach},
author={Lu, Renzhi and Hong, Seung Ho and Zhang, Xiongfeng},
journal={Applied Energy},
volume={220},
pages={220--230},
year={2018},
publisher={Elsevier}
}
@article{alonso2017multi,
title={Multi-robot formation control and object transport in dynamic environments via constrained optimization},
author={Alonso-Mora, Javier and Baker, Stuart and Rus, Daniela},
journal={The International Journal of Robotics Research},
volume={36},
number={9},
pages={1000--1021},
year={2017},
publisher={SAGE Publications Sage UK: London, England}
}
@article{sun2020cooperative,
title={Cooperative decision-making for mixed traffic: A ramp merging example},
author={Sun, Zhanbo and Huang, Tianyu and Zhang, Peitong},
journal={Transportation research part C: emerging technologies},
volume={120},
pages={102764},
year={2020},
publisher={Elsevier}
}
@article{ghiasi2019mixed,
title={A mixed traffic speed harmonization model with connected autonomous vehicles},
author={Ghiasi, Amir and Li, Xiaopeng and Ma, Jiaqi},
journal={Transportation Research Part C: Emerging Technologies},
volume={104},
pages={210--233},
year={2019},
publisher={Elsevier}
}
@article{kucharski2022simulating,
title={Simulating two-sided mobility platforms with MaaSSim},
author={Kucharski, Rafa{\l} and Cats, Oded},
journal={PloS one},
volume={17},
number={6},
pages={e0269682},
year={2022},
publisher={Public Library of Science San Francisco, CA USA}
}
@article{kucharski2020exact,
title={Exact matching of attractive shared rides (ExMAS) for system-wide strategic evaluations},
author={Kucharski, Rafa{\l} and Cats, Oded},
journal={Transportation Research Part B: Methodological},
volume={139},
pages={285--310},
year={2020},
publisher={Elsevier}
}
@article{ashkrof2021ride,
title={Ride Acceptance Behaviour of Ride-sourcing Drivers},
author={Ashkrof, Peyman and Correia, Gon{\c{c}}alo Homem de Almeida and Cats, Oded and van Arem, Bart},
journal={arXiv preprint arXiv:2107.07864},
year={2021}
}
@article{ashkrof2020understanding,
title={Understanding ride-sourcing drivers' behaviour and preferences: Insights from focus groups analysis},
author={Ashkrof, Peyman and de Almeida Correia, Gon{\c{c}}alo Homem and Cats, Oded and van Arem, Bart},
journal={Research in Transportation Business \& Management},
volume={37},
pages={100516},
year={2020},
publisher={Elsevier}
}
@inproceedings{xi2021ddrl,
title={DDRL: A Decentralized Deep Reinforcement Learning Method for Vehicle Repositioning},
author={Xi, Jinhao and Zhu, Fenghua and Chen, Yuanyuan and Lv, Yisheng and Tan, Chang and Wang, Feiyue},
booktitle={2021 IEEE International Intelligent Transportation Systems Conference (ITSC)},
pages={3984--3989},
year={2021},
organization={IEEE}
}
@article{turan2020dynamic,
title={Dynamic pricing and fleet management for electric autonomous mobility on demand systems},
author={Turan, Berkay and Pedarsani, Ramtin and Alizadeh, Mahnoosh},
journal={Transportation Research Part C: Emerging Technologies},
volume={121},
pages={102829},
year={2020},
publisher={Elsevier}
}
@article{fielbaum2020beyond,
title={Beyond the Mohring effect: Scale economies induced by transit lines structures design},
author={Fielbaum, Andr{\'e}s and Jara-Diaz, Sergio and Gschwender, Antonio},
journal={Economics of Transportation},
volume={22},
pages={100163},
year={2020},
publisher={Elsevier}
}
@article{stachl2020predicting,
title={Predicting personality from patterns of behavior collected with smartphones},
author={Stachl, Clemens and Au, Quay and Schoedel, Ramona and Gosling, Samuel D and Harari, Gabriella M and Buschek, Daniel and V{\"o}lkel, Sarah Theres and Schuwerk, Tobias and Oldemeier, Michelle and Ullmann, Theresa and others},
journal={Proceedings of the National Academy of Sciences},
volume={117},
number={30},
pages={17680--17687},
year={2020},
publisher={National Acad Sciences}
}
@article{matz2017psychological,
title={Psychological targeting as an effective approach to digital mass persuasion},
author={Matz, Sandra C and Kosinski, Michal and Nave, Gideon and Stillwell, David J},
journal={Proceedings of the national academy of sciences},
volume={114},
number={48},
pages={12714--12719},
year={2017},
publisher={National Acad Sciences}
}
@article{kosinski2013private,
title={Private traits and attributes are predictable from digital records of human behavior},
author={Kosinski, Michal and Stillwell, David and Graepel, Thore},
journal={Proceedings of the national academy of sciences},
volume={110},
number={15},
pages={5802--5805},
year={2013},
publisher={National Acad Sciences}
}
@article{blake2020integrated,
title={An integrated modelling approach examining the influence of goals, habit and learning on choice using visual attention data},
author={Blake, Miranda R and Dubey, Subodh and Swait, Joffre and Lancsar, Emily and Ghijben, Peter},
journal={Journal of Business Research},
volume={117},
pages={44--57},
year={2020},
publisher={Elsevier}
}
@article{yap2020crowding,
title={Crowding valuation in urban tram and bus transportation based on smart card data},
author={Yap, Menno and Cats, Oded and van Arem, Bart},
journal={Transportmetrica A: Transport Science},
volume={16},
number={1},
pages={23--42},
year={2020},
publisher={Taylor \& Francis}
}
@article{alonso2021determinants,
title={What are the determinants of the willingness to share rides in pooled on-demand services?},
author={Alonso-Gonz{\'a}lez, Mar{\'\i}a J and Cats, Oded and van Oort, Niels and Hoogendoorn-Lanser, Sascha and Hoogendoorn, Serge},
journal={Transportation},
volume={48},
number={4},
pages={1733--1765},
year={2021},
publisher={Springer}
}
@article{cats2021beyond,
title={Beyond the Dichotomy: How Ride-hailing Competes with and Complements Public Transport},
author={Cats, Oded and Kucharski, Rafa{\l} and Danda, Santosh Rao and Yap, Menno},