Parameter Adjustments in POMDP-Based Trajectory Planning for Unsignalized Intersections

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F24%3A00374634" target="_blank" >RIV/68407700:21730/24:00374634 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21230/24:00374634

Výsledek na webu

<a href="http://dx.doi.org/10.5220/0012742400003702" target="_blank" >http://dx.doi.org/10.5220/0012742400003702</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5220/0012742400003702" target="_blank" >10.5220/0012742400003702</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Parameter Adjustments in POMDP-Based Trajectory Planning for Unsignalized Intersections

Popis výsledku v původním jazyce

This paper investigates the problem of trajectory planning for autonomous vehicles at unsignalized intersections, specifically focusing on scenarios where the vehicle lacks the right of way and yet must cross safely. To address this issue, we have employed a method based on the Partially Observable Markov Decision Processes (POMDPs) framework designed for planning under uncertainty. The method utilizes the Adaptive Belief Tree (ABT) algorithm as an approximate solver for the POMDPs. We outline the POMDP formulation, beginning with discretizing the intersection’s topology. Additionally, we present a dynamics model for the prediction of the evolving states of vehicles, such as their position and velocity. Using an observation model, we also describe the connection of those states with the imperfect (noisy) available measurements. Our results confirmed that the method is able to plan collision-free trajectories in a series of simulations utilizing real-world traffic data from aerial footage of two distinct intersections. Furthermore, we studied the impact of parameter adjustments of the ABT algorithm on the method’s performance. This provides guidance in determining reasonable parameter settings, which is valuable for future method applications.

Název v anglickém jazyce

Parameter Adjustments in POMDP-Based Trajectory Planning for Unsignalized Intersections

Popis výsledku anglicky

This paper investigates the problem of trajectory planning for autonomous vehicles at unsignalized intersections, specifically focusing on scenarios where the vehicle lacks the right of way and yet must cross safely. To address this issue, we have employed a method based on the Partially Observable Markov Decision Processes (POMDPs) framework designed for planning under uncertainty. The method utilizes the Adaptive Belief Tree (ABT) algorithm as an approximate solver for the POMDPs. We outline the POMDP formulation, beginning with discretizing the intersection’s topology. Additionally, we present a dynamics model for the prediction of the evolving states of vehicles, such as their position and velocity. Using an observation model, we also describe the connection of those states with the imperfect (noisy) available measurements. Our results confirmed that the method is able to plan collision-free trajectories in a series of simulations utilizing real-world traffic data from aerial footage of two distinct intersections. Furthermore, we studied the impact of parameter adjustments of the ABT algorithm on the method’s performance. This provides guidance in determining reasonable parameter settings, which is valuable for future method applications.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

20204 - Robotics and automatic control

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 10th International Conference on Vehicle Technology and Intelligent Transport Systems

ISBN

978-989-758-703-0

ISSN

2184-495X

e-ISSN

2184-495X

Počet stran výsledku

8

Strana od-do

522-529

Název nakladatele

Science and Technology Publications, Lda

Místo vydání

Setúbal

Místo konání akce

Angers

Datum konání akce

2. 5. 2024

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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