An Evaluation Model for the Comfort of Vehicle Intelligent Cockpits Based on Passenger Experience

Jianjun Yang, Shanshan Xing, Yimeng Chen, Ruizhi Qiu, Chunrong Hua and Dawei Dong
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Jianjun Yang: School of Automobile and Transportation, Xihua University, Chengdu 610039, China
Shanshan Xing: School of Automobile and Transportation, Xihua University, Chengdu 610039, China
Yimeng Chen: School of Automobile and Transportation, Xihua University, Chengdu 610039, China
Ruizhi Qiu: School of Automobile and Transportation, Xihua University, Chengdu 610039, China
Chunrong Hua: School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China
Dawei Dong: School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China

Sustainability, 2022, vol. 14, issue 11, 1-19

Abstract: With the development of intelligence and network connectivity, the development of the automotive industry is also moving toward intelligent systems. For passengers, the utility of intelligence is to achieve more convenience and comfort. The intelligent cockpit is the place where passengers directly interact with the car, which directly affects the experience of passengers in the car. For the intelligent cockpits that have emerged in recent years, a reasonable and accurate comfort evaluation model is urgently needed. Therefore, in this article, from the passenger’s perspective, a subjective evaluation experiment was set up to collect data on four important indicators affecting the comfort of the intelligent cockpit: sound, light, heat, and human–computer interaction. The subjective evaluation weights were derived from a questionnaire, and the entropy weighting method was used to obtain the objective weights. Finally, the two weights were combined using the idea of game theory combination assignment to get the final accurate weights. Using the idea of penalty type substitution, the four index models were then synthesized to get the final evaluation model. The feasibility of the model was verified when measuring the car cockpit. The feasibility of the method means it can evaluate the comfort level of an intelligent cockpit more reasonably, facilitate the enhancement and improvement of the model, and promote the development of the model to achieve maximum passenger comfort.

Keywords: intelligent vehicle cockpit; human comfort; passenger experience; comprehensive evaluation model; analytic hierarchy process (AHP); entropy weight method; game theory (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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