Effects of Road Type and IVIS Task Type on Driver Behavior and Driving Performance in Agricultural Tractors

Abstract

In recent years, terrible driver behavior and driving performance have been the primary causes of increasing agricultural tractor accidents. However, how environmental factors influence driver behavior and driving safety is not clarified clearly yet for tractors. Therefore, this article researched the effects of road type and in-vehicle information system (IVIS) task type on driver behavior and driving performance. Thirty-two participants were randomly assigned to four groups equally. They finished the simulation on three types of roads while each group conducted one different IVIS task. Drivers’ wrist movement acceleration (ACC), rotation angular velocity (GYRO), and surface temperature (TEMP) were recorded and statistically analyzed together with the driving performance parameter (DP) and workload index. Results showed that road and IVIS task types significantly affected drivers’ ACC, GYRO, TEMP, and DP. IVIS task type significantly affected driver workload. This article will contribute to road and tractor IVIS design, driver behavior and safety research.

Keywords:

• Agricultural tractor
• driver behavior
• driving safety
• road type
• IVIS Task

Acknowledgments

The authors gratefully acknowledge the support of the National Key R&D Program of China, the Yantai City School-Land Integration Development Project, and China Agricultural University.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Key R&D Program of China [No. 2020YFB1713502]; and the Yantai City School-Land Integration Development Project [No. 2021XDRHXMPT29].

Notes on contributors

Xiaoning Zhao

Xiaoning Zhao is currently a master student in Vehicle Engineering at China Agricultural University. He received his bachelor degree from Yanshan University in 2019. His research interests include driving simulator design, human–computer interaction, user-centered design in vehicles, ergonomics and vehicle dynamics simulation.

Yuefeng Du

Yuefeng Du is currently an Associate Professor at the Department of Vehicle Engineering in China Agricultural University. He received his PhD in Vehicle Engineering from China Agricultural University in 2014. His research interests include human–computer interaction, digital twin, digital design of agricultural machinery, and mechatronics.

Lichao Yang

Lichao Yang received his bachelor’s degree from Shandong University of Technology in 2021, and he is now a master’s student in Vehicle Engineering at China Agricultural University. His research interests include ergonomics, agricultural machinery development, deep learning, and data acquisition.

Enrong Mao

Enrong Mao is currently a Professor at the Department of Vehicle Engineering in China Agricultural University. He received his PhD in Agricultural Mechanization Engineering from China Agricultural University (1994). His research interests include ergonomics, vehicle dynamics, hydraulic system design and agricultural machinery development.

Dafang Guo

Dafang Guo received his MS degree in Mechanical Design and Theory from Chinese Academy of Agricultural Mechanization Sciences (2021). He is currently a PhD candidate in Vehicle Engineering at China Agriculture University. His research interests include intelligent control system, deep learning, data mining and digital twin.

Zhongxiang Zhu

Zhongxiang Zhu is currently a Professor at the Department of Vehicle Engineering in China Agricultural University. He received his PhD in Biological Resources Science from Iwate University in Japan (2006). His research interests include vehicle electronic control and intelligent technology, vehicle dynamics, and digital design of agricultural machinery.