Comprehensive Subjective–Objective Combined Performance Evaluation Methodology for Human–Machine Shared Steering Control System

In response to the inconsistency and lack of multidimensionality in existing evaluation methodologies for human–machine shared steering control (SSC) systems, an integrated approach that combines both objective and subjective evaluation methods is proposed. By analyzing the key subsystems within the SSC system, an objective evaluation method is developed, focusing on four critical dimensions: safety, reliability, comfort, and suitability. Specific indexes are defined to assess each dimension quantitatively, ensuring a systematic and comprehensive evaluation process. To complement the objective approach, a subjective evaluation method is formulated, addressing the same four dimensions. The subjective evaluation method incorporates weight coefficients for individual evaluation indexes; a detailed procedure for comprehensive evaluation is outlined, thereby enhancing the robustness and adaptability of the proposed framework. The effectiveness of the proposed methodology is validated through experimental trials and questionnaire surveys involving 32 drivers. The results demonstrate the feasibility of comparing the overall performance of different SSC systems using both objective and subjective evaluations. Furthermore, the strong consistency between the objective and subjective evaluation outcomes confirms the coherence, rationality, and practical suitability of the proposed approach, establishing its suitability for practical applications in SSC system assessment.

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Publication Details

Journal
Transportation Research Record Journal of the Transportation Research Board
Published
2026-11-06
DOI
https://doi.org/10.1177/03611981261493933
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
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article

Comprehensive Subjective–Objective Combined Performance Evaluation Methodology for Human–Machine Shared Steering Control System

Xueyun Li, Xiaobing Chen, Ke shanjun, Luo longfei et al.
Transportation Research Record Journal of the Transportation Research Board
Human-Automation Interaction and Safety
article

Comprehensive Subjective–Objective Combined Performance Evaluation Methodology for Human–Machine Shared Steering Control System

Xueyun Li, Xiaobing Chen, Ke shanjun, Luo longfei, Guo Dong, Wang Yiping
article en

Abstract

In response to the inconsistency and lack of multidimensionality in existing evaluation methodologies for human–machine shared steering control (SSC) systems, an integrated approach that combines both objective and subjective evaluation methods is proposed. By analyzing the key subsystems within the SSC system, an objective evaluation method is developed, focusing on four critical dimensions: safety, reliability, comfort, and suitability. Specific indexes are defined to assess each dimension quantitatively, ensuring a systematic and comprehensive evaluation process. To complement the objective approach, a subjective evaluation method is formulated, addressing the same four dimensions. The subjective evaluation method incorporates weight coefficients for individual evaluation indexes; a detailed procedure for comprehensive evaluation is outlined, thereby enhancing the robustness and adaptability of the proposed framework. The effectiveness of the proposed methodology is validated through experimental trials and questionnaire surveys involving 32 drivers. The results demonstrate the feasibility of comparing the overall performance of different SSC systems using both objective and subjective evaluations. Furthermore, the strong consistency between the objective and subjective evaluation outcomes confirms the coherence, rationality, and practical suitability of the proposed approach, establishing its suitability for practical applications in SSC system assessment.

Transportation Research Record Journal of the Transportation Research Board
Wuhan University of Technology (CN), Hubei University of Automotive Technology (CN), Chongqing University of Technology (CN)
Openalex Percentile: Top 13%
Human-Automation Interaction and Safety
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