TMPF: A Two‐Stage Merging Planning Framework for Dense Traffic
Planning for autonomous vehicles to merge into high‐density traffic flows within limited mileage is quite challenging. Specifically, the driving trajectory will inevitably have intersections with other vehicles whose driving intentions can't be directly observed. Herein, a two‐stage algorithm framework that is decomposed into the longitudinal and lateral planning processes for online merging planning is proposed. An improved particle filter is used to estimate the driving models of surrounding vehicles for predicting their future driving intentions. Based on Monte Carlo tree search (MCTS), different action spaces are evaluated for longitudinal merging gap selection and lateral interactive merging operation, while heuristic pruning is used to reduce the computation cost. Moreover, the coefficients related to the driving styles are introduced, and their influences on merging performance are analyzed. Finally, the proposed algorithm is implemented in a two‐lane simulation environment. The results show that the proposal has outperformed other baseline methods.
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource
- Language
-
Englisch
- Bibliographic citation
-
TMPF: A Two‐Stage Merging Planning Framework for Dense Traffic ; day:12 ; month:05 ; year:2023 ; extent:13
Advanced intelligent systems ; (12.05.2023) (gesamt 13)
- Creator
-
Chen, Ci
Yong, Chenghao
Guo, Xuexun
Pei, Xiaofei
- DOI
-
10.1002/aisy.202300081
- URN
-
urn:nbn:de:101:1-2023051315201362482488
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
14.08.2025, 10:48 AM CEST
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Chen, Ci
- Yong, Chenghao
- Guo, Xuexun
- Pei, Xiaofei
Other Objects (12)
Investigating traffic characteristics for merging sections in Iraq
Traffic planning and engineering
Plan merging by reuse for multi-agent planning
Merging enzymatic and synthetic chemistry with computational synthesis planning
Traffic planning in port-cities
Time-sensitive traffic and time-triggered mechanisms : traffic planning and analysis
Merging Metadata
A Two-Stage Robustness Approach to Evacuation Planning with Buses
MFVT: an anomaly traffic detection method merging feature fusion network and vision transformer architecture
Incorporating Traffic Management Information into Logistics Planning
Nonholonomic Motion Planning for Automated Vehicles in Dense Scenarios
Scheduling M2M traffic over LTE uplink of a dense small cell network
Investigating traffic characteristics for merging sections in Iraq
Traffic planning and engineering
Plan merging by reuse for multi-agent planning
Merging enzymatic and synthetic chemistry with computational synthesis planning
Traffic planning in port-cities
Time-sensitive traffic and time-triggered mechanisms : traffic planning and analysis
Merging Metadata
A Two-Stage Robustness Approach to Evacuation Planning with Buses
MFVT: an anomaly traffic detection method merging feature fusion network and vision transformer architecture
Incorporating Traffic Management Information into Logistics Planning
Nonholonomic Motion Planning for Automated Vehicles in Dense Scenarios
Scheduling M2M traffic over LTE uplink of a dense small cell network
Investigating traffic characteristics for merging sections in Iraq
Traffic planning and engineering
Plan merging by reuse for multi-agent planning
Merging enzymatic and synthetic chemistry with computational synthesis planning
Traffic planning in port-cities
Time-sensitive traffic and time-triggered mechanisms : traffic planning and analysis
Merging Metadata
A Two-Stage Robustness Approach to Evacuation Planning with Buses
MFVT: an anomaly traffic detection method merging feature fusion network and vision transformer architecture
Incorporating Traffic Management Information into Logistics Planning
Nonholonomic Motion Planning for Automated Vehicles in Dense Scenarios