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Interaction-Aware Trajectory Prediction and Planning for Autonomous Vehicles in Forced Merge Scenarios
[article]
2021
arXiv
pre-print
Preserved Fulltext
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
2016
2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC)
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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]
2018
arXiv
pre-print
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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
2018
IEEE Transactions on Intelligent Vehicles
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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]
2021
arXiv
pre-print
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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]
2018
arXiv
pre-print
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, 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]
2019
arXiv
pre-print
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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
2017
2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC)
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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]
2022
arXiv
pre-print
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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]
2019
arXiv
pre-print
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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]
2018
arXiv
pre-print
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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]
2020
arXiv
pre-print
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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]
2019
arXiv
pre-print
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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]
2021
arXiv
pre-print
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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 Planning
❷Planning ...
arXiv:2108.04629v1
fatcat:wz4al34wtbht5cjxarjd7i3opu
EPSILON: An Efficient Planning System for Automated Vehicles in Highly Interactive Environments
[article]
2021
arXiv
pre-print
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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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