Multi-Model-Based Local Path Planning Methodology for Autonomous Driving: An Integrated Framework

Jian, Zhiqiang; Chen, Shitao; Zhang, Songyi; Yu, Chen; Zheng, Nanning

doi:10.1109/tits.2020.3042603

Cited by 27 publications

(14 citation statements)

References 30 publications

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“…The camera monitors the environmental changes and vehicle location with a frequency of 30Hz. Once a critical environmental change is detected, the replanning module is triggered in the desktop PC [32], and the resultant replanned trajectory is sent to the car-like robot via ZigBee for closed-loop tracking. In trajectory tracking, a PID controller is used for longitudinal tracking and a pure-pursuit controller tracks laterally.…”

Section: E Experimental Setups and Resultsmentioning

confidence: 99%

Online Trajectory Replanning for Sudden Environmental Changes During Automated Parking: A Parallel Stitching Method

Yin

Ouyang

et al. 2022

IEEE Trans. Intell. Veh.

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Section: E Experimental Setups and Resultsmentioning

confidence: 99%

Online Trajectory Replanning for Sudden Environmental Changes During Automated Parking: A Parallel Stitching Method

Yin

Ouyang

et al. 2022

IEEE Trans. Intell. Veh.

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“…For example, Levin used dispatch and simulation methods to study the scheduling of AVs and the equation describing the maximum set of demands that can be satisfied when an appropriate scheduling policy is selected and validate preliminary results for large city networks [16]. Jian et al proposed a path-planning framework that adaptively adjusts the planning process according to the changes in traffic scenes and then provides different pathplanning algorithms to ensure the safety and flexibility of the driving process [17].…”

Section: Abstract and Co-words Analysesmentioning

confidence: 99%

The Research on the Autonomous Vehicles: A Bibliometric Analysis

Xia¹,

Cheng²

2023

Proceedings of the 2nd International Conference on Information, Control and Automation, ICICA 2022, December 2-4, 2022, Chongqi

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Autonomous vehicles (AVs) can create human social welfare by reducing traffic accidents, improving traffic efficiency, reducing cost, etc. However, there is a lack of systematic analysis of AVs research. This study used CiteSpace visualization software to conduct bibliometric analysis, and data were collected from 2663 valid documents in the Web of Science (WoS) from 2001 to 2021. By analyzing the annual volume of publications, major distribution, co-occurrence of authors, institutions, keywords, and cluster analysis of AVs research in the past two decades, this study reveals the historical evolution, hotspots and trends in AVs research, which is helpful for researchers to have a comprehensive understanding of this knowledge field and have a more objective and scientific basis for AVs further research from a quantitative perspective.

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“…On the other hand, the fixed high-frequency repeating planning framework applied in the algorithms above leads to the discontinuity of paths between frames, so they cannot maintain a stable avoiding path, reducing the passability in certain extreme scenarios. Reference [15] analyzes the planning frequency problem of traditional algorithms in detail, believing that fixed planning frequency will cause phenomena such as path deviation towards obstacles or path overshooting in specific scenarios, and proposes a new decision-making and planning framework, effectively improving algorithm's performance. The view of reference [15] has been validated through our engineering practice.…”

Section: Introductionmentioning

confidence: 99%

“…Reference [15] analyzes the planning frequency problem of traditional algorithms in detail, believing that fixed planning frequency will cause phenomena such as path deviation towards obstacles or path overshooting in specific scenarios, and proposes a new decision-making and planning framework, effectively improving algorithm's performance. The view of reference [15] has been validated through our engineering practice.…”

Section: Introductionmentioning

confidence: 99%

A trajectory planning method based on triggered planning framework for autonomous driving on unstructured roads in mining areas

Xu,

Liu,

Yang

et al. 2024

Second International Conference on Electrical, Electronics, and Information Engineering (EEIE 2023)

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This article proposes a trajectory planning method for autonomous driving on unstructured roads in mining areas. The proposed method adopts a path and speed decoupling approach and a triggered planning framework based on different trigger events pre-designed, which has higher passability and stability when applied in some unstructured scenarios. At the path planning level, a variable lateral sampling range is utilized to accommodate the irregular boundaries of mining roads. The speed planning module initially determines the vehicle's speed planning tasks (cruising, following, stop) based on the output of path planning, which integrates decision-making into the planning process, eliminating the need for complicated state machine designs used in other methods. Additionally, the introduced triggered planning framework effectively minimizes the mutual influence between the decision planning module and other modules and improves the passability in complex scenarios. The simulation experiments demonstrate the capability of this method in accomplishing decisionmaking and planning tasks successfully on mining roads.

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Multi-Model-Based Local Path Planning Methodology for Autonomous Driving: An Integrated Framework

Cited by 27 publications

References 30 publications

Online Trajectory Replanning for Sudden Environmental Changes During Automated Parking: A Parallel Stitching Method

Online Trajectory Replanning for Sudden Environmental Changes During Automated Parking: A Parallel Stitching Method

The Research on the Autonomous Vehicles: A Bibliometric Analysis

A trajectory planning method based on triggered planning framework for autonomous driving on unstructured roads in mining areas

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