Jachimczyk Bartosz, Dziak Damian, Czapla Jacek, Damps Pawel, Kulesza Wlodek J
BetterSolutions S.A. Al. Grunwaldzka 103, 80-244 Gdansk, Poland.
Blekinge Institute of Technology, Department of Applied Signal Processing, 371 79 Karlskrona, Sweden.
Sensors (Basel). 2018 Apr 17;18(4):1233. doi: 10.3390/s18041233.
The assessment of skills is essential and desirable in areas such as medicine, security, and other professions where mental, physical, and manual skills are crucial. However, often such assessments are performed by people called “experts” who may be subjective and are able to consider a limited number of factors and indicators. This article addresses the problem of the objective assessment of driving style independent of circumstances. The proposed objective assessment of driving style is based on eight indicators, which are associated with the vehicle’s speed, acceleration, jerk, engine rotational speed and driving time. These indicators are used to estimate three driving style criteria: , , and . The presented solution is based on the embedded system designed according to the Internet of Things concept. The useful data are acquired from the car diagnostic port—OBD-II—and from an additional accelerometer sensor and GPS module. The proposed driving skills assessment method has been implemented and experimentally validated on a group of drivers. The obtained results prove the system’s ability to quantitatively distinguish different driving styles. The system was verified on long-route tests for analysis and could then improve the driver’s behavior behind the wheel. Moreover, the spider diagram approach that was used established a convenient visualization platform for multidimensional comparison of the result and comprehensive assessment in an intelligible manner.
在医学、安保及其他精神、身体和手工技能至关重要的职业领域，技能评估至关重要且很有必要。然而，此类评估通常由所谓的“专家”进行，他们可能带有主观性，且只能考虑有限的因素和指标。本文探讨了独立于具体情境对驾驶风格进行客观评估的问题。所提出的驾驶风格客观评估基于八个指标，这些指标与车辆速度、加速度、加加速度、发动机转速和驾驶时间相关。这些指标用于估计三个驾驶风格标准： ， ，和 。所呈现的解决方案基于根据物联网概念设计的嵌入式系统。有用数据从汽车诊断端口——OBD-II——以及一个额外的加速度传感器和GPS模块获取。所提出的驾驶技能评估方法已在一组驾驶员身上实施并通过实验验证。所得结果证明了该系统定量区分不同驾驶风格的能力。该系统在用于分析的长距离测试中得到验证，进而可以改善驾驶员的驾驶行为。此外，所采用的雷达图方法建立了一个方便的可视化平台，以便以易懂的方式对结果进行多维比较和综合评估。
