Probabilistic traversability risk-aware one-stage motion planner for unmanned ground vehicle in unstructured environments

Jie Fan; Zhongbao Wang; Jiangbo Geng; Yijie Chen; Yutong Jiang; Xudong Zhang

doi:10.1109/VTC2025-Fall65116.2025.11310121

Probabilistic traversability risk-aware one-stage motion planner for unmanned ground vehicle in unstructured environments

Jie Fan
, Zhongbao Wang
, Jiangbo Geng
, Yijie Chen
, Yutong Jiang
, Xudong Zhang^*

^*Corresponding author for this work

Beijing Institute of Technology
Beijing North Vehicle Group Corporation
China North Vehicle Research Institute

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

This paper introduces a motion planning framework that uses a probabilistic traversability risk model and an entropy-based risk measure to unify risk data into a single metric for effective planning. A cross-entropy based one-stage planner is proposed to balance global optimality with local feasibility, improving path efficiency. Experimental results show the framework outperforms traditional methods (e.g., A*-DWA, CL-RRT) in travel time, path smoothness, and length, confirming its robustness and efficiency in complex unstructured environments.

Original language	English
Title of host publication	2025 IEEE 102nd Vehicular Technology Conference, VTC 2025-Fall - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798331503208
DOIs	https://doi.org/10.1109/VTC2025-Fall65116.2025.11310121
Publication status	Published - 2025
Externally published	Yes
Event	2025 IEEE 102nd Vehicular Technology Conference, VTC 2025 - Chengdu, China Duration: 19 Oct 2025 → 22 Oct 2025

Publication series

Name	IEEE Vehicular Technology Conference
ISSN (Print)	1090-3038

Conference

Conference	2025 IEEE 102nd Vehicular Technology Conference, VTC 2025
Country/Territory	China
City	Chengdu
Period	19/10/25 → 22/10/25

Keywords

motion planning
probabilistic traversability risk evaluation
unmanned ground vehicle
unstructured environment

Access to Document

10.1109/VTC2025-Fall65116.2025.11310121

Cite this

Fan, J., Wang, Z., Geng, J., Chen, Y., Jiang, Y., & Zhang, X. (2025). Probabilistic traversability risk-aware one-stage motion planner for unmanned ground vehicle in unstructured environments. In 2025 IEEE 102nd Vehicular Technology Conference, VTC 2025-Fall - Proceedings (IEEE Vehicular Technology Conference). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VTC2025-Fall65116.2025.11310121

@inproceedings{b0f89ae6e4244c1d8a880c109ca4e88d,

title = "Probabilistic traversability risk-aware one-stage motion planner for unmanned ground vehicle in unstructured environments",

abstract = "This paper introduces a motion planning framework that uses a probabilistic traversability risk model and an entropy-based risk measure to unify risk data into a single metric for effective planning. A cross-entropy based one-stage planner is proposed to balance global optimality with local feasibility, improving path efficiency. Experimental results show the framework outperforms traditional methods (e.g., A*-DWA, CL-RRT) in travel time, path smoothness, and length, confirming its robustness and efficiency in complex unstructured environments.",

keywords = "motion planning, probabilistic traversability risk evaluation, unmanned ground vehicle, unstructured environment",

author = "Jie Fan and Zhongbao Wang and Jiangbo Geng and Yijie Chen and Yutong Jiang and Xudong Zhang",

note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 2025 IEEE 102nd Vehicular Technology Conference, VTC 2025 ; Conference date: 19-10-2025 Through 22-10-2025",

year = "2025",

doi = "10.1109/VTC2025-Fall65116.2025.11310121",

language = "English",

series = "IEEE Vehicular Technology Conference",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2025 IEEE 102nd Vehicular Technology Conference, VTC 2025-Fall - Proceedings",

address = "United States",

}

Fan, J, Wang, Z, Geng, J, Chen, Y, Jiang, Y & Zhang, X 2025, Probabilistic traversability risk-aware one-stage motion planner for unmanned ground vehicle in unstructured environments. in 2025 IEEE 102nd Vehicular Technology Conference, VTC 2025-Fall - Proceedings. IEEE Vehicular Technology Conference, Institute of Electrical and Electronics Engineers Inc., 2025 IEEE 102nd Vehicular Technology Conference, VTC 2025, Chengdu, China, 19/10/25. https://doi.org/10.1109/VTC2025-Fall65116.2025.11310121

Probabilistic traversability risk-aware one-stage motion planner for unmanned ground vehicle in unstructured environments. / Fan, Jie; Wang, Zhongbao; Geng, Jiangbo et al.
2025 IEEE 102nd Vehicular Technology Conference, VTC 2025-Fall - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2025. (IEEE Vehicular Technology Conference).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Probabilistic traversability risk-aware one-stage motion planner for unmanned ground vehicle in unstructured environments

AU - Fan, Jie

AU - Wang, Zhongbao

AU - Geng, Jiangbo

AU - Chen, Yijie

AU - Jiang, Yutong

AU - Zhang, Xudong

PY - 2025

Y1 - 2025

N2 - This paper introduces a motion planning framework that uses a probabilistic traversability risk model and an entropy-based risk measure to unify risk data into a single metric for effective planning. A cross-entropy based one-stage planner is proposed to balance global optimality with local feasibility, improving path efficiency. Experimental results show the framework outperforms traditional methods (e.g., A*-DWA, CL-RRT) in travel time, path smoothness, and length, confirming its robustness and efficiency in complex unstructured environments.

AB - This paper introduces a motion planning framework that uses a probabilistic traversability risk model and an entropy-based risk measure to unify risk data into a single metric for effective planning. A cross-entropy based one-stage planner is proposed to balance global optimality with local feasibility, improving path efficiency. Experimental results show the framework outperforms traditional methods (e.g., A*-DWA, CL-RRT) in travel time, path smoothness, and length, confirming its robustness and efficiency in complex unstructured environments.

KW - motion planning

KW - probabilistic traversability risk evaluation

KW - unmanned ground vehicle

KW - unstructured environment

UR - https://www.scopus.com/pages/publications/105032475595

U2 - 10.1109/VTC2025-Fall65116.2025.11310121

DO - 10.1109/VTC2025-Fall65116.2025.11310121

M3 - Conference contribution

AN - SCOPUS:105032475595

T3 - IEEE Vehicular Technology Conference

BT - 2025 IEEE 102nd Vehicular Technology Conference, VTC 2025-Fall - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2025 IEEE 102nd Vehicular Technology Conference, VTC 2025

Y2 - 19 October 2025 through 22 October 2025

ER -

Fan J, Wang Z, Geng J, Chen Y, Jiang Y, Zhang X. Probabilistic traversability risk-aware one-stage motion planner for unmanned ground vehicle in unstructured environments. In 2025 IEEE 102nd Vehicular Technology Conference, VTC 2025-Fall - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2025. (IEEE Vehicular Technology Conference). doi: 10.1109/VTC2025-Fall65116.2025.11310121

Probabilistic traversability risk-aware one-stage motion planner for unmanned ground vehicle in unstructured environments

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