A Generalized Dynamic Potential Energy Model for Multiagent Path Planning

Author:

He Liu12,Xi Haoning3ORCID,Guo Tangyi12ORCID,Tang Kun12ORCID

Affiliation:

1. Department of Automation, Nanjing University of Science and Technology, Jiangsu 210094, China

2. MIIT Key Lab of Traffic Information Fusion & System Control, Nanjing, China

3. Research Center for Integrated Transport Innovation (RCITI), School of Civil and Environmental Engineering, University of New South Wales, Sydney, NSW 2052, Australia

Abstract

Path planning for the multiagent, which is generally based on the artificial potential energy field, reflects the decision-making process of pedestrian walking and has great importance on the field multiagent system. In this paper, after setting the spatial-temporal simulation environment with large cells and small time segments based on the disaggregation decision theory of the multiagent, we establish a generalized dynamic potential energy model (DPEM) for the multiagent through four steps: (1) construct the space energy field with the improved Dijkstra algorithm, and obtain the fitting functions to reflect the relationship between speed decline rate and space occupancy of the agent through empirical cross experiments. (2) Construct the delay potential energy field based on the judgement and psychological changes of the multiagent in the situations where the other pedestrians have occupied the bottleneck cell. (3) Construct the waiting potential energy field based on the characteristics of the multiagent, such as dissipation and enhancement. (4) Obtain the generalized dynamic potential energy field by superposing the space potential energy field, delay potential energy field, and waiting potential energy field all together. Moreover, a case study is conducted to verify the feasibility and effectiveness of the dynamic potential energy model. The results also indicate that each agent’s path planning decision such as forward, waiting, and detour in the multiagent system is related to their individual characters and environmental factors. Overall, this study could help improve the efficiency of pedestrian traffic, optimize the walking space, and improve the performance of pedestrians in the multiagent system.

Funder

Fundamental Research Funds for the Central Universities

Publisher

Hindawi Limited

Subject

Strategy and Management,Computer Science Applications,Mechanical Engineering,Economics and Econometrics,Automotive Engineering

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