HIERARCHICAL DECISION-MAKING FOR AUTONOMOUS DRIVING

Contact

• Please feel free to contact to share your feedbacks, ideas and experiences about Scene-Understanding and Decision-Making for autonomous driving
• [LinkedIn]
• [ResearchGate]

Versions

• [Pre-Print - full version]

To cite this version:

-- Simon Chauvin, "Hierarchical Decision-Making for Autonomous Driving," Aug 2018, DOI 10.13140/RG.2.2.24352.43526

Overview

REFERENCES

-- Last update: 2018-08-11

[1] X. Geng, H. Liang, B. Yu, P. Zhao, L. He, and R. Huang, "A Scenario-Adaptive Driving Behavior Prediction Approach to Urban Autonomous Driving," 2017. [pdf]

[2] S. Ulbrich, T. Nothdurft, M. Maurer, and P. Hecker, "Graph-Based Context Representation , Environment Modeling and Information Aggregation for Automated Driving," 2014. [pdf]

[3] R. Kohlhaas, T. Bittner, T. Schamm, and J. Z. Marius, "Semantic State Space for High-level Maneuver Planning in Structured Traffic Scenes," 2014. [html]

[4] R. Kohlhaas, D. Hammann, T. Schamm, and J. M. Zollner, "Planning of High-Level Maneuver Sequences on Semantic State Spaces," 2015. [html]

[5] C. Chen, A. Gaschler, M. Rickert, and A. Knoll, "Task Planning for Highly Automated Driving," 2015. [pdf]

[6] J. Rieken, R. Matthaei, and M. Maurer, "Toward Perception-Driven Urban Environment Modeling for Automated Road Vehicles," 2015. [pdf]

[7] M. Hülsen, J. M. Zöllner, and C. Weiss, "Traffic intersection situation description ontology for advanced driver assistance," 2011. [html]

[8] L. Yu, X. Shao, Y. Wei, and K. Zhou, "Intelligent Land Vehicle Model Transfer Trajectory Planning Method Based on Deep Reinforcement Learning," 2018. [html]

[9] R. Regele, "Using ontology-based traffic models for more efficient decision making of autonomous vehicles," 2008. [html]

[10] L. Kunze, T. Bruls, T. Suleymanov, and P. Newman, "Reading between the Lanes: Road Layout Reconstruction from Partially Segmented Scenes," 2018. [pdf]

[11] W. Liu, S. W. Kim, S. Pendleton, and M. H. Ang, "Situation-aware decision making for autonomous driving on urban road using online POMDP," 2015. [html]

[12] M. Ardelt, P. Waldmann, F. Homm, and N. Kaempchen, "Strategic decision-making process in advanced driver assistance systems," 2010. [html]

[13] P. Wolf, K. Kurzer, T. Wingert, F. Kuhnt, and J. Z. Marius, "Adaptive Behavior Generation for Autonomous Driving using Deep Reinforcement Learning with Compact Semantic States," 2018. [pdf]

[14] D. Steckelmacher and P. Vrancx, "An Empirical Comparison of Neural Architectures for Reinforcement Learning in Partially Observable Environments," 2015. [pdf]

[15] J. Morton, T. A. Wheeler, and M. J. Kochenderfer, "Analysis of Recurrent Neural Networks for Probabilistic Modeling of Driver Behavior," 2016. [pdf]

[16] O. Scheel, L. Schwarz, N. Navab, and F. Tombari, "Situation Assessment for Planning Lane Changes: Combining Recurrent Models and Prediction," 2018. [pdf]

[17] A. El Sallab, M. Abdou, E. Perot, and S. Yogamani, "Deep Reinforcement Learning framework for Autonomous Driving," 2017. [pdf]

[18] X. Huang, J. Sun, and J. Sun, "A car-following model considering asymmetric driving behavior based on long short-term memory neural networks," 2018. [html]

[19] N. Deo and M. M. Trivedi, "Multi-Modal Trajectory Prediction of Surrounding Vehicles with Maneuver based LSTMs," 2018. [pdf]

[20] S. S. Mousavi, M. Schukat, and E. Howley, "Traffic Light Control Using Deep Policy-Gradient and Value-Function Based Reinforcement Learning," 2017. [html]

[21] J. Liu, P. Hou, L. Mu, Y. Yu, and C. Huang, "Elements of Effective Deep Reinforcement Learning towards Tactical Driving Decision Making," 2017. [pdf]

[22] M. A. F. Khan and O. H. Elibol, "Car Racing using Reinforcement Learning," 2016. [pdf]

[23] M. Legrand, "Deep Reinforcement Learning for Simulated Autonomous Vehicle Control," 2016. [pdf]

[24] S. W. Jang, J. Min, and C. Lee, "Reinforcement Car Racing with A3C," 2016. [pdf]

[25] S. Ulbrich et al., "Towards a Functional System Architecture for Automated Vehicles," 2017. [pdf]

[26] Y. Hu, W. Zhan, and M. Tomizuka, "Probabilistic Prediction of Vehicle Semantic Intention and Motion," 2018. [pdf]

[27] J. Schlechtriemen, F. Wirthmueller, A. Wedel, G. Breuel, and K. D. Kuhnert, "When will it change the lane? A probabilistic regression approach for rarely occurring events," 2015. [html]

[28] B. Zhou, W. Schwarting, D. Rus, and J. Alonso-mora, "Joint Multi-Policy Behavior Estimation and Receding-Horizon Trajectory Planning for Automated Urban Driving," 2018. [pdf]

[29] E. Galceran, A. Cunningham, R. Eustice, and E. Olson, "Multipolicy decision-making for autonomous driving via changepoint-based behavior prediction: Theory and experiment," 2017. [html]

[30] C. Dong, J. M. Dolan, and B. Litkouhi, "Interactive Ramp Merging Planning in Autonomous Driving: Multi-Merging Leading PGM (MML-PGM)," 2017. [pdf]

[31] C. Hubmann, J. Schulz, M. Becker, D. Althoff, and C. Stiller, "Automated Driving in Uncertain Environments: Planning with Interaction and Uncertain Maneuver Prediction," 2018. [html]

[32] A. Lawitzky, D. Althoff, C. F. Passenberg, G. Tanzmeister, D. Wollherr, and M. Buss, "Interactive Scene Prediction for Automotive Applications," 2013. [pdf]

[33] L. Wei, "Planning under Uncertainties for Autonomous Driving on Urban Road," 2016. [pdf]

[34] A. Kendall and Y. Gal, "What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?," 2017. [pdf]

[35] Y. Gal, "Uncertainty in Deep Learning," 2016. [pdf]

[36] A. Furda and L. Vlacic, "Enabling safe autonomous driving in real-world city traffic using Multiple Criteria decision making," 2011. [html]

[37] R. Matthaei and M. Maurer, "Autonomous driving - A top-down-approach," 2015. [pdf]

[38] C. Paxton, V. Raman, G. D. Hager, and M. Kobilarov, "Combining Neural Networks and Tree Search for Task and Motion Planning in Challenging Environments," 2017. [pdf]

[39] L. Li, K. Ota, and M. Dong, "Human-Like Driving: Empirical Decision-Making System for Autonomous Vehicles," 2018. [html]

[40] C. Menendez-Romero, F. Winkler, C. Dornhege, and W. Burgard, "Maneuver planning for highly automated vehicles," 2017. [pdf]

[41] X. Li, Z. Sun, D. Cao, Z. He, and Q. Zhu, "Real-time trajectory planning for autonomous urban driving: Framework, algorithms, and verifications," 2016. [html]

[42] Ö. Sahin Tas, F. Kuhnt, J. M. Zöllner, and C. Stiller, "Functional System Architectures towards Fully Automated Driving," 2016. [html]

[43] A. G. Cunningham, E. Galceran, R. M. Eustice, and E. Olson, "MPDM: Multipolicy decision-making in dynamic, uncertain environments for autonomous driving," 2015. [html]

[44] Y. Wang, H. He, and C. Sun, "Learning to Navigate through Complex Dynamic Environment with Modular Deep Reinforcement Learning," 2018. [html]

[45] R. Liaw, S. Krishnan, A. Garg, D. Crankshaw, J. E. Gonzalez, and K. Goldberg, "Composing Meta-Policies for Autonomous Driving Using Hierarchical Deep Reinforcement Learning," 2017. [pdf]

[46] L. P. Tuyen, N. A. Vien, T. Chung, C. Science, and S. Korea, "Deep Hierarchical Reinforcement Learning Algorithm in Partially Observable Markov Decision Processes," 2018. [pdf]

[47] S. Shalev-Shwartz, S. Shammah, and A. Shashua, "Safe, Multi-Agent, Reinforcement Learning for Autonomous Driving," 2016. [pdf]

[48] W. Schwarting, J. Alonso-mora, and D. Rus, "Survey on Planning and Decision-Making for Autonomous Vehicles," 2018. [pdf]

[49] J. Rasmussen, "Skills, Rules, and Knowledge; Signals, Signs, and Symbols, and Other Distinctions in Human Performance Models," 1983. [html]

[50] L. Claussmann, M. Revilloud, S. Glaser, and D. Gruyer, "A study on ai-based approaches for high-level decision making in highway autonomous driving," 2017. [html]

[51] D. Isele, A. Cosgun, K. Subramanian, and K. Fujimura, "Navigating Intersections with Autonomous Vehicles using Deep Reinforcement Learning," 2017. [pdf]

[52] H. Bai, D. Hsu, and W. S. Lee, "Integrated perception and planning in the continuous space: A POMDP approach," 2014. [pdf]

[53] V. Sezer, T. Bandyopadhyay, D. Rus, E. Frazzoli, and D. Hsu, "Towards autonomous navigation of unsignalized intersections under uncertainty of human driver intent," 2015. [html]

[54] P. Wang, C. Chan, and A. La De Fortelle, "A Reinforcement Learning Based Approach for Automated Lane Change Maneuvers," 2018. [pdf]

[55] X. Liang, T. Wang, L. Yang, and E. P. Xing, "CIRL: Controllable Imitative Reinforcement Learning for Vision-based Self-driving," 2018. [pdf]

[56] M. Bouton, K. Julian, A. Nakhaei, K. Fujimura, and M. J. Kochenderfer, "Utility Decomposition with Deep Corrections for Scalable Planning under Uncertainty," 2018. [pdf]

[57] M. Wulfmeier, D. Z. Wang, and I. Posner, "Watch This: Scalable Cost-Function Learning for Path Planning in Urban Environments," 2016. [pdf]

[58] M. Wulfmeier, "On machine learning and structure for driverless cars mobile robots," 2017. [pdf]

[59] N. Ye, A. Somani, D. Hsu, and W. S. Lee, "DESPOT: Online POMDP Planning with Regularization," 2017. [pdf]

[60] C. Shaojun, "Online POMDP Planning for Vehicle Navigation in Densely Populated Area," 2014. [pdf]

[61] K. H. Wray, S. J. Witwicki, and S. Zilberstein, "Online decision-making for scalable autonomous systems," 2017. [pdf]

[62] C.-J. Hoel, K. Wolff, and L. Laine, "Automated Speed and Lane Change Decision Making using Deep Reinforcement Learning," 2018. [pdf]

[63] A. Kendall et al., "Learning to Drive in a Day," 2018. [pdf]

[64] M. El Chamie, Y. Yu, B. Acikmese, and M. Ono, "Controlled Markov Processes with Safety State Constraints," 2018. [html]

[65] M. Mukadam, A. Cosgun, A. Nakhaei, and K. Fujimura, "Tactical Decision Making for Lane Changing with Deep Reinforcement Learning," 2017. [pdf]

[66] M. Alshiekh, R. Bloem, and K. Bettina, "Safe Reinforcement Learning via Shielding," 2017. [pdf]

[67] M. Bahram, A. Wolf, M. Aeberhard, and D. Wollherr, "A prediction-based reactive driving strategy for highly automated driving function on freeways," 2014. [html]

[68] J. Eggert and T. Puphal, "Continuous Risk Measures for Driving Support," 2018. [html]

[69] S. Shalev-Shwartz, S. Shammah, and A. Shashua, "On a Formal Model of Safe and Scalable Self-driving Cars," 2017. [pdf]

[70] F. Yang, D. Lyu, B. Liu, and S. Gustafson, "PEORL: Integrating Symbolic Planning and Hierarchical Reinforcement Learning for Robust Decision-Making," 2018. [pdf]

[71] D. Isele, R. Rahimi, A. Cosgun, K. Subramanian, and K. Fujimura, "Navigating Occluded Intersections with Autonomous Vehicles using Deep Reinforcement Learning," 2018. [pdf]

[72] M. Bouton, A. Cosgun, and M. J. Kochenderfer, "Belief state planning for autonomously navigating urban intersections," 2017. [pdf]

[73] C. Wu, A. Kreidieh, K. Parvate, E. Vinitsky, and A. M. Bayen, "Flow: Architecture and Benchmarking for Reinforcement Learning in Traffic Control," 2017. [pdf]

[74] D. Krajzewicz, J. Erdmann, M. Behrisch, and L. Bieker, "Recent Development and Applications of SUMO - Simulation of Urban MObility," 2012. [pdf]

[75] R. Mcallister et al., "Concrete Problems for Autonomous Vehicle Safety: Advantages of Bayesian Deep Learning," 2017. [pdf]

[76] H. Grimmett, R. Triebel, R. Paul, and I. Posner, "Introspective classification for robot perception," 2016. [pdf]

[77] M. Nolte, S. Ernst, J. Richelmann, and M. Maurer, "Representing the Unkown - Impact of Uncertainty on the Interaction between Decision Making and Trajectory Generation," 2018. [pdf]

[78] S. Brechtel, T. Gindele, and R. Dillmann, "Probabilistic Decision-Making under Uncertainty for Autonomous Driving using Continuous POMDPs," 2015. [html]

[79] H. Berndt and K. Dietmayer, "Driver intention inference with vehicle onboard sensors," 2009. [html]

[80] D. Meyer-delius, "Probabilistic Situation Recognition for Vehicular Traffic Scenarios," 2009. [html]

[81] W. Song, G. Xiong, and H. Chen, "Intention-Aware Autonomous Driving Decision-Making in an Uncontrolled Intersection," 2016. [pdf]

[82] T. Streubel and K. H. Hoffmann, "Prediction of driver intended path at intersections," 2014. [html]

[83] J. R. Chandiramani, "Decision Making under Uncertainty for Automated Vehicles in Urban Situations," 2017. [pdf]

[84] M. Schreier, "Bayesian environment representation, prediction, and criticality assessment for driver assistance systems," 2017. [pdf]

[85] T. Gindele, S. Brechtel, and R. Dillmann, "A probabilistic model for estimating driver behaviors and vehicle trajectories in traffic environments," 2010. [html]

[86] S. Lefèvre, C. Laugier, and J. Ibañez-Guzmán, "Exploiting map information for driver intention estimation at road intersections," 2011. [html]

[87] J. F. P. Kooij, F. Flohr, E. A. I. Pool, and D. M. Gavrila, "Context-based Path Prediction for Targets with Switching Dynamics," 2018. [pdf]

[88] E. Galceran, E. Olson, and R. M. Eustice, "Augmented vehicle tracking under occlusions for decision-making in autonomous driving," 2015. [pdf]

[89] W. Zhan, C. Liu, C. Y. Chan, and M. Tomizuka, "A non-conservatively defensive strategy for urban autonomous driving," 2016. [html]

[90] B. Paden, M. Cap, S. Z. Yong, D. Yershov, and E. Frazzoli, "A Survey of Motion Planning and Control Techniques for Self-driving Urban Vehicles," 2016. [pdf]

[91] S. Karaman, M. R. Walter, A. Perez, E. Frazzoli, and S. Teller, "Anytime motion planning using the RRT," 2011. [pdf]