The evaluation of driving performance is a vital way to reflect the usability of in-vehicle system. Study the impact of in-vehicle interaction on driving performance can help avoiding hidden driving dangers. Speed of vehicles and distance from the vehicles ahead during driving are important indicators to reflect driving performance. In this study, Speed measurement relies on the GPS module. Conventionally, precise distance detection during driving is mostly based on radar sensors or high-resolution cameras that are both quite expensive. This paper proposed an object distance detection algorithm that relies on ordinary HD binocular camera with relatively low price to detect the distance. A new mismatch elimination method is proposed to improve the performance of the algorithm. At the same time, this paper designed a driving performance evaluation experiment. The distance is measured according to the proposed algorithm. Driving performance with primary tasks (speed maintenance and distance maintenance) and secondary tasks (touch control and voice control) on different driving scenes (straight road and curve road) are evaluated. Experimental results showed that introduction of secondary tasks dose influence the operation of the driver by distracting him. It also affects the driver’s response to external changes. Both speed maintenance task and distance maintenance task have verified this conclusion. The proposed object distance detection method satisfies the accuracy required for driving performance evaluation.
CITATION STYLE
Gao, Y., Wang, Z., & Fu, S. (2020). An object distance detection method for driving performance evaluation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12187 LNAI, pp. 292–303). Springer. https://doi.org/10.1007/978-3-030-49183-3_23
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