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Dampen the Stop-and-Go Traffic with Connected and Automated Vehicles – A Deep Reinforcement Learning Approach [article]

Liming Jiang, Yuanchang Xie, Danjue Chen, Tienan Li, Nicholas G. Evans
2020 arXiv   pre-print
(CAVs) with carefully designed controllers one could dampen the stop-and-go waves in the vehicle fleet.  ...  Instead of using analytical model, this study adopts reinforcement learning to control the behavior of CAV and put a single CAV at the 2nd position of a vehicle fleet with the purpose to dampen the speed  ...  To our best knowledge, this study is the first attempt to use Deep Reinforcement Learning (DRL) approach for CAV control that builds altruism into the control objective (e.g., dampening stop-and-go wave  ... 
arXiv:2005.08245v1 fatcat:wpqzubpby5effc64xqv7jtzktu

Partially Connected Automated Vehicle Cooperative Control Strategy with a Deep Reinforcement Learning Approach [article]

Haotian Shi, Yang Zhou, Keshu Wu, Xin Wang, Yangxin Lin, Bin Ran
2020 arXiv   pre-print
This paper proposes a cooperative strategy of connected and automated vehicles (CAVs) longitudinal control for partially connected and automated traffic environment based on deep reinforcement learning  ...  Keywords: partially connected automated traffic environment, cooperative control, deep reinforcement learning, traffic oscillation dampening, energy efficiency  ...  Acknowledgement This work was supported by the Wisconsin Traffic Operations and Safety (TOPS) Laboratory. Author Statement  ... 
arXiv:2012.01841v1 fatcat:acbn4uljzzdandx5pev7gj3iuq

Flow: A Modular Learning Framework for Autonomy in Traffic [article]

Cathy Wu, Aboudy Kreidieh, Kanaad Parvate, Eugene Vinitsky, Alexandre M Bayen
2020 arXiv   pre-print
The article presents a modular learning framework which leverages deep Reinforcement Learning methods to address complex traffic dynamics.  ...  In partially-observed single-lane traffic, a small neural network control law can eliminate stop-and-go traffic -- surpassing all known model-based controllers, achieving near-optimal performance, and  ...  ACKNOWLEDGMENTS The authors would like to thank Professor Alexander Skabardonis for insightful discussions about vehicle dynamics; Leah Dickstein and Nathan Mandi for early prototyping; Nishant Kheterpal  ... 
arXiv:1710.05465v3 fatcat:kds7eowu5rhzziz7zzlc3xfhdi

Evaluation approach for a combined implementation of Day 1 C-ITS and Highway Chauffeur – v.1.0

Serio Angelo Maria Agriesti, Marco Ponti, Giovanna Marchionni, Paolo Gandini, Roberto Maja, Fabio Borghetti, Valeria Paglino, Maurizio Bruglieri, Luca Studer
2018 Zenodo  
longitudinal and the lateral behavior of a conditionally automated vehicle.  ...  First, to achieve this objective, in Chapter 2 the available bibliography concerning the Highway Chauffeur system and, more in general, conditional automated driving is analyzed with a particular focus  ...  based learning and deep learning.  ... 
doi:10.5281/zenodo.3637982 fatcat:75uics7gfzcezir3z6ixm5ccu4

Controllability Analysis and Optimal Control of Mixed Traffic Flow with Human-driven and Autonomous Vehicles [article]

Jiawei Wang, Yang Zheng, Qing Xu, Jianqiang Wang, Keqiang Li
2020 arXiv   pre-print
Connected and automated vehicles (CAVs) have a great potential to improve traffic efficiency in mixed traffic systems, which has been demonstrated by multiple numerical simulations and field experiments  ...  Using the Popov-Belevitch-Hautus (PBH) criterion, we prove for the first time that a ring-road mixed traffic system with one CAV and multiple heterogeneous human-driven vehicles is not completely controllable  ...  one single CAV has a certain ability to dissipate stop-and-go waves in a mixed traffic flow.  ... 
arXiv:2002.02099v1 fatcat:jxgfsuqjebd6hj6kycn6xsqdwi

Thorough state-of-the-art analysis of electric and hybrid vehicle powertrains: Topologies and integrated energy management strategies

Dai-Duong Tran, Majid Vafaeipour, Mohamed El Baghdadi, Ricardo Barrero, Joeri Van Mierlo, Omar Hegazy
2019 Renewable & Sustainable Energy Reviews  
In addition, EMSs as applied in the literature are systematically surveyed for a qualitative investigation, classification, and comparison of existing approaches in terms of the principles, advantages,  ...  A R T I C L E I N F O Keywords: Plug-in hybrid electric vehicle Full-electric vehicle Energy management strategy optimisation Online EMS Offline EMS Optimal control strategy A B S T R A C T Hybrid and  ...  We also acknowledge Flanders Make and VLAIO for the support of our research group.  ... 
doi:10.1016/j.rser.2019.109596 fatcat:ybks774km5htvb6f7foyetum7m

Tackling Climate Change with Machine Learning [article]

David Rolnick, Priya L. Donti, Lynn H. Kaack, Kelly Kochanski, Alexandre Lacoste, Kris Sankaran, Andrew Slavin Ross, Nikola Milojevic-Dupont, Natasha Jaques, Anna Waldman-Brown, Alexandra Luccioni, Tegan Maharaj, Evan D. Sherwin, S. Karthik Mukkavilli (+6 others)
2019 arXiv   pre-print
Here we describe how machine learning can be a powerful tool in reducing greenhouse gas emissions and helping society adapt to a changing climate.  ...  Climate change is one of the greatest challenges facing humanity, and we, as machine learning experts, may wonder how we can help.  ...  The authors gratefully acknowledge support from National Science Foundation grant 1803547, the Center for Climate and Energy Decision Making through a cooperative agreement between the National Science  ... 
arXiv:1906.05433v2 fatcat:ykmqsivkbfcazaz3wl5f7srula

Digital Transformation in Smart Farm and Forest Operations Needs Human-Centered AI: Challenges and Future Directions

Andreas Holzinger, Anna Saranti, Alessa Angerschmid, Carl Orge Retzlaff, Andreas Gronauer, Vladimir Pejakovic, Francisco Medel-Jimenez, Theresa Krexner, Christoph Gollob, Karl Stampfer
2022 Sensors  
, the workhorse of AI, statistical machine learning (ML).  ...  For example, a farmer/forester in the loop can often bring in experience and conceptual understanding to the AI pipeline—no AI can do this.  ...  The system also dampens the movements of the cylinders and stops jerky load thrusts in the end positions, which enables jerk-free operation.  ... 
doi:10.3390/s22083043 pmid:35459028 pmcid:PMC9029836 fatcat:73bojrnysrcnzfkem4eomrupqy

AICP: Augmented Informative Cooperative Perception [article]

Pengyuan Zhou, Pranvera Kortoci, Yui-Pan Yau, Tristan Braud, Xiujun Wang, Benjamin Finley, Lik-Hang Lee, Sasu Tarkoma, Jussi Kangasharju, Pan Hui
2022 arXiv   pre-print
Connected vehicles, whether equipped with advanced driver-assistance systems or fully autonomous, require human driver supervision and are currently constrained to visual information in their line-of-sight  ...  Specifically, we propose (i) a dedicated system design with custom data structure and lightweight routing protocol for convenient data encapsulation, fast interpretation and transmission, and (ii) a comprehensive  ...  [24] applied a deep reinforcement learning approach to reduce the information sent between vehicles by only forwarding information about objects that are not likely to have been seen directly by surrounding  ... 
arXiv:2101.05508v3 fatcat:zta3veuwr5anzfbegqxoa4qmba

Smoothing Traffic Flow via Control of Autonomous Vehicles [article]

Yang Zheng and Jiawei Wang and Keqiang Li
2020 arXiv   pre-print
and autonomous vehicles in a ring road.  ...  In this paper, from a control-theoretic perspective, we establish analytical results on the controllability, stabilizability, and reachability of a mixed traffic system consisting of human-driven vehicles  ...  ACKNOWLEDGMENT The authors thank Prof. Antonis Papachristodoulou, Prof. Jianqiang Wang, Dr. Qing Xu, Mr. Licio Romao, Mr. Suhao Yan and Mr. Chaoyi Chen for comments and discussions.  ... 
arXiv:1812.09544v2 fatcat:wybffkrnqjho5av4ftgx25zfnu

IA Meets CRNs: A Prospective Review on the Application of Deep Architectures in Spectrum Management

Mduduzi C. Hlophe, Bodhaswar T. Maharaj
2021 IEEE Access  
With the positive explosion of connected "things", managing, and keeping up with their operations requires an automated approach.  ...  solution approaches has been identified, an introduction to machine learning (ML) and reinforcement learning (RL) is given to enable a smooth understanding of deep architectures.  ... 
doi:10.1109/access.2021.3104099 fatcat:ucyvpx36drdj5dcl2npxipkhd4

Software Engineering for Sustainability: Find the Leverage Points!

Birgit Penzenstadler, Leticia Duboc, Colin C. Venters, Stefanie Betz, Norbert Seyff, Krzsztof Wnuk, Ruzanna Chitchyan, Steve M. Easterbrook, Christoph Becker
2018 IEEE Software  
It covers the structures of mutual trust and communication in a social system and the balance between conflicting interests. The economic dimension covers financial aspects and business value.  ...  General rights This document is made available in accordance with publisher policies. Please cite only the published version using the reference above.  ...  Acknowledgement Part of this work has been supported by the "Refactoring Energy Systems" grant EP/R007373/1.  ... 
doi:10.1109/ms.2018.110154908 fatcat:xdwknq3c5rcjlhszg5f4oqkaoa

Comparing Deep Reinforcement Learning Algorithms' Ability to Safely Navigate Challenging Waters

Thomas Nakken Larsen, Halvor Ødegård Teigen, Torkel Laache, Damiano Varagnolo, Adil Rasheed
2021 Frontiers in Robotics and AI  
Reinforcement Learning (RL) controllers have proved to effectively tackle the dual objectives of path following and collision avoidance.  ...  , and when generalized to environments with a considerable domain gap from the training environment.  ...  The authors acknowledge the financial support from the Norwegian Research Council and the industrial partners: DV GL, Kongsberg and Maritime Robotics of the Autosit project. (Grant No.: 295033).  ... 
doi:10.3389/frobt.2021.738113 pmid:34589522 pmcid:PMC8473616 fatcat:dprzo5pjmfh2nnotmwrk6at3xa

The Death of Rules and Standards

Anthony J. Casey, Anthony Niblett
2015 Social Science Research Network  
A microdirective, like a rule, provides a clear instruction to a citizen on how to comply with the law. But, like a standard, a microdirective is tailored to and adapts to each and every context.  ...  When an individual citizen faces a legal choice, the machine will select from the catalog and communicate to that individual the precise context-specific command (the microdirective) necessary for compliance  ...  law will remain constant and straightforward: a simple stop-go directive.  ... 
doi:10.2139/ssrn.2693826 fatcat:z5ftwc6nf5dihdhx7q25tv2s3y

Social physics [article]

Marko Jusup, Petter Holme, Kiyoshi Kanazawa, Misako Takayasu, Ivan Romic, Zhen Wang, Suncana Gecek, Tomislav Lipic, Boris Podobnik, Lin Wang, Wei Luo, Tin Klanjscek (+3 others)
2021 arXiv   pre-print
Starting with a set of topics that pertain to the modern way of living and factors that enable humankind's prosperous existence, we discuss urban development and traffic, the functioning of financial markets  ...  Physicists tackling societal problems are no longer a curiosity, but rather a force to be reckoned with, yet for reckoning to be truly productive, it is necessary to build dialog and mutual understanding  ...  B, C, More congested traffic with stop-and-go waves (recordings 26 and 25, lanes 2 and 4, respectively).  ... 
arXiv:2110.01866v1 fatcat:ccfxyezl6zgddd6uvrxubmaxua
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