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Interaction-Aware Trajectory Prediction and Planning for Autonomous Vehicles in Forced Merge Scenarios [article]

Kaiwen Liu, Nan Li, H. Eric Tseng, Ilya Kolmanovsky, Anouck Girard
2021 arXiv   pre-print
In this paper, we consider the problem of autonomous vehicle control for forced merge scenarios.  ...  Merging is, in general, a challenging task for both human drivers and autonomous vehicles, especially in dense traffic, because the merging vehicle typically needs to interact with other vehicles to identify  ...  Therefore, our leader-follower model ( 8 )-( 11 ) is suitable for trajectory prediction and planning in forced merge scenarios. B.  ... 
arXiv:2112.07624v1 fatcat:pjjyeqnahnbffgait2yq7b2uhi

Interaction aware trajectory planning for merge scenarios in congested traffic situations

Niclas Evestedt, Erik Ward, John Folkesson, Daniel Axehill
2016 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC)  
Many motion planning frameworks for autonomous vehicles adopt a reactive approach where simple models of other traffic participants are used and therefore need to adhere to large margins in order to behave  ...  This is especially true for merge manoeuvres into dense traffic, where drivers sometimes must be somewhat aggressive and show the intention of merging in order to interact with the other driver and make  ...  for upstream vehicle during merge in HM scenario for interaction aware planner (IA) and baseline (BL) using a f ollower,min = −4 m/s 2 and t f ollower,min = 1 s, respectively. d iv Freq.  ... 
doi:10.1109/itsc.2016.7795596 dblp:conf/itsc/EvestedtWFA16 fatcat:a4i47woqjjhflejmsd6vagzbpy

Towards a Fatality-Aware Benchmark of Probabilistic Reaction Prediction in Highly Interactive Driving Scenarios [article]

Wei Zhan, Liting Sun, Yeping Hu, Jiachen Li, Masayoshi Tomizuka
2018 arXiv   pre-print
Moreover, reactive predictions are necessary in highly interactive driving scenarios to answer "what if I take this action in the future" for autonomous vehicles.  ...  Autonomous vehicles should be able to generate accurate probabilistic predictions for uncertain behavior of other road users.  ...  Moreover, reactive predictions are necessary in highly interactive driving scenarios to answer "what if I take this action in the future" for autonomous vehicles.  ... 
arXiv:1809.03478v1 fatcat:uujngpf6azgd7i3hx3rvlqssdy

Autonomous Navigation in Interaction-Based Environments—A Case of Non-Signalized Roundabouts

Maradona Rodrigues, Andrew McGordon, Graham Gest, James Marco
2018 IEEE Transactions on Intelligent Vehicles  
Most traditional autonomous planning approaches use rule-based speed assignment for generating admissible motion trajectories, which work successfully in non-interaction-based driving scenarios.  ...  A non-signalized roundabout adds to the autonomous vehicle planning challenge, as navigating such interaction-dependent scenarios safely, efficiently, and comfortably has been a challenge even for human  ...  Groenewald from WMG for providing the Simulator Lab facilities and the hardware necessary to develop and run the human driving experiment.  ... 
doi:10.1109/tiv.2018.2873916 fatcat:kffulaporraqvpmcmletustnly

Learning Interaction-aware Guidance Policies for Motion Planning in Dense Traffic Scenarios [article]

Bruno Brito, Achin Agarwal, Javier Alonso-Mora
2021 arXiv   pre-print
This paper presents a novel framework for interaction-aware motion planning in dense traffic scenarios.  ...  Autonomous navigation in dense traffic scenarios remains challenging for autonomous vehicles (AVs) because the intentions of other drivers are not directly observable and AVs have to deal with a wide range  ...  This paper presents a novel framework for interaction-aware motion planning in dense traffic scenarios.  ... 
arXiv:2107.04538v1 fatcat:j7iuudg3ufey7pxwoz43np2hry

Hierarchical Game-Theoretic Planning for Autonomous Vehicles [article]

Jaime F. Fisac, Eli Bronstein, Elis Stefansson, Dorsa Sadigh, S. Shankar Sastry, Anca D. Dragan
2018 arXiv   pre-print
, quantitatively accounting for the autonomous vehicle and the human driver's ability and incentives to influence each other.  ...  In this paper, we introduce a novel game-theoretic trajectory planning algorithm for autonomous driving, that enables real-time performance by hierarchically decomposing the underlying dynamic game into  ...  ) between candidate plans and predicted human trajectories.  ... 
arXiv:1810.05766v1 fatcat:f6hpqdsnbjbbdiaqqtl4jsafou

INTERACTION Dataset: An INTERnational, Adversarial and Cooperative moTION Dataset in Interactive Driving Scenarios with Semantic Maps [article]

Wei Zhan, Liting Sun, Di Wang, Haojie Shi, Aubrey Clausse, Maximilian Naumann, Julius Kummerle, Hendrik Konigshof, Christoph Stiller, Arnaud de La Fortelle, Masayoshi Tomizuka
2019 arXiv   pre-print
In this paper, we present an INTERnational, Adversarial and Cooperative moTION dataset (INTERACTION dataset) in interactive driving scenarios with semantic maps.  ...  Five features of the dataset are highlighted. 1) The interactive driving scenarios are diverse, including urban/highway/ramp merging and lane changes, roundabouts with yield/stop signs, signalized intersections  ...  The authors also would like to thank the Karlsruhe House of Young Scientists (KHYS) for their support of Maximilian's research visit at MSC Lab.  ... 
arXiv:1910.03088v1 fatcat:cycdo6pvrvavjdfaub5fuoj2bq

Adaptive behaviour selection for autonomous vehicle through naturalistic speed planning

Maradona Rodrigues, Graham Gest, Andrew McGordon, James Marco
2017 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC)  
In such a situation it is necessary for the autonomous vehicle to be able to understand its surrounding scenario context, predict its evolution and generate plans that will enable its successful navigation  ...  In such an interaction dependent scenario, the behaviour of other actors in the scene can be dynamically changing and sometimes non-predictable.  ... 
doi:10.1109/itsc.2017.8317907 dblp:conf/itsc/RodriguesGMM17 fatcat:v6gyxvt725fabpqqycc6644x6i

Socially-Compatible Behavior Design of Autonomous Vehicles with Verification on Real Human Data [article]

Letian Wang, Liting Sun, Masayoshi Tomizuka, Wei Zhan
2022 arXiv   pre-print
In this paper, we propose an uncertain-aware integrated prediction and planning (UAPP) framework.  ...  We first propose the definitions for courtesy and confidence. Based on that, their influences on the behaviors of AVs in interactive driving scenarios are explored.  ...  ACKNOWLEDGEMENT We thank Wilko Shwarting and Qingyun Wang for insightful discussions.  ... 
arXiv:2010.14712v7 fatcat:njrugyvdtfavldklonc7bfdwye

Risk-Aware Reasoning for Autonomous Vehicles [article]

Majid Khonji, Jorge Dias, Lakmal Seneviratne
2019 arXiv   pre-print
Second, an intention recognition subsystem that predicts the driving-style and the intention of agent vehicles (and pedestrians).  ...  In this paper, we propose a system architecture for risk-aware AVs capable of reasoning about uncertainty and deliberately bounding the risk of collision below a given threshold.  ...  Probabilistic predictions are beneficial in many safety-critical tasks such as collision checking and risk-aware motion planning.  ... 
arXiv:1910.02461v1 fatcat:cng3d2v6crdeflvy735yyl64di

Courteous Autonomous Cars [article]

Liting Sun, Wei Zhan, Masayoshi Tomizuka, Anca D. Dragan
2018 arXiv   pre-print
Such a courtesy term enables the robot car to be aware of possible irrationality of the human behavior, and plan accordingly. We analyze the effect of courtesy in a variety of scenarios.  ...  Typically, autonomous cars optimize for a combination of safety, efficiency, and driving quality.  ...  Acknowledgement This work was partially supported by Mines Paris-Tech Foundation, "Automated Vehciles-Drive for All" Chair, and NSF CAREER. We thank Jaime F. Fisac for helpful discussion and feedback.  ... 
arXiv:1808.02633v2 fatcat:az2ji4mwibesjnzyhrypspzbza

Interaction-aware Kalman Neural Networks for Trajectory Prediction [article]

Ce Ju, Zheng Wang, Cheng Long, Xiaoyu Zhang, Dong Eui Chang
2020 arXiv   pre-print
Forecasting the motion of surrounding obstacles (vehicles, bicycles, pedestrians and etc.) benefits the on-road motion planning for intelligent and autonomous vehicles.  ...  as interaction-aware accelerations, a motion layer for transforming the accelerations to interaction aware trajectories, and a filter layer for estimating future trajectories with a Kalman filter network  ...  ., Ltd.) and Ruihui Zhao (Tencent Jarvis Lab) for their useful suggestions and contributions.  ... 
arXiv:1902.10928v3 fatcat:ibz3zk67pjhj5h3mkc3o6kgaue

Cooperation-Aware Lane Change Maneuver in Dense Traffic based on Model Predictive Control with Recurrent Neural Network [article]

Sangjae Bae, Dhruv Saxena, Alireza Nakhaei, Chiho Choi, Kikuo Fujimura, Scott Moura
2019 arXiv   pre-print
In particular, RNN predicts interactive motions of other drivers in response to potential actions of the autonomous vehicle, which are then systematically evaluated in safety constraints.  ...  In this case, classical robust controls may not apply since there is no safe area to merge to without interacting with the other drivers.  ...  The autonomous-driving vehicle would get stuck in the merging area, unless other vehicles slow down to make a space for the vehicle.  ... 
arXiv:1909.05665v2 fatcat:x4a4tgejnjftdmnowcovvmu77i

Roadside-assisted Cooperative Planning using Future Path Sharing for Autonomous Driving [article]

Mai Hirata and Manabu Tsukada and Keisuke Okumura and Yasumasa Tamura and Hideya Ochiai and Xavier Défago
2021 arXiv   pre-print
We conducted simulation experiments with two vehicles at a blind intersection scenario, finding that each car can travel safely and more efficiently by planning a path that reflects the action plans of  ...  In addition to real-time information sharing, self-driving cars need to coordinate their action plans to achieve higher safety and efficiency.  ...  Future path sharing Vehicle ❶ ❸ Control Autonomous Coordinated Autonomous path Coordinated path Trajectory Speed Perception & Prediction Reservation table ❷Cooperative PlanningPlanning  ... 
arXiv:2108.04629v1 fatcat:wz4al34wtbht5cjxarjd7i3opu

EPSILON: An Efficient Planning System for Automated Vehicles in Highly Interactive Environments [article]

Wenchao Ding, Lu Zhang, Jing Chen, Shaojie Shen
2021 arXiv   pre-print
In this paper, we present an Efficient Planning System for automated vehicles In highLy interactive envirONments (EPSILON).  ...  EPSILON is an efficient interaction-aware planning system for automated driving, and is extensively validated in both simulation and real-world dense city traffic.  ...  His research interests include planning, optimization programming, mobile robot navigation.  ... 
arXiv:2108.07993v1 fatcat:yvhgk33sxbebvn5l5v574dcjn4
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