PRACA ORYGINALNA
Preliminary driving style classification of the professional drivers
1
Faculty of Mechatronics and Mechanical Engineering, Kielce University of Technology, Polska
2
Department of Automotive Engineering and Transport, Kielce University of Technology, Polska
Data nadesłania: 17-11-2022
Data ostatniej rewizji: 19-12-2022
Data akceptacji: 20-12-2022
Data publikacji: 30-12-2022
Autor do korespondencji
Emilia Szumska
Faculty of Mechatronics and Mechanical Engineering, Kielce University of Technology, Al. Tysiąclecia P.P. 7, 25-314, Kielce, Polska
Faculty of Mechatronics and Mechanical Engineering, Kielce University of Technology, Al. Tysiąclecia P.P. 7, 25-314, Kielce, Polska
The Archives of Automotive Engineering – Archiwum Motoryzacji 2022;98(4):25-39
SŁOWA KLUCZOWE
DZIEDZINY
STRESZCZENIE
Driving style and driver behaviour are important in evaluating city bus drivers. Buses are one of the means of public transportation in cities, used by millions of people. The purpose of this study was to present a model for preliminary classification of driving style of the professional drivers based on averaged maximum values of lateral and longitudinal acceleration recorded during regular work. First, the recorded acceleration values of 69 city bus drivers were analysed. Then, the correlation between the acceleration values and the age and experience of the city bus drivers was examined. Based on the results of the preliminary classification of drivers, extreme values for both lateral acceleration and longitudinal acceleration (deceleration and acceleration) were obtained by 3 drivers out of the 69 tested. The study also examined the relationship between averaged values of maximum lateral and longitudinal acceleration and driver age and experience. Based on the correlation results, showed that age and the number of years of holding a driver's license are not significantly related to acceleration. Therefore, the method can be used to analyse drivers regardless of their age and experience.
REFERENCJE (39)
1.
Af Wåhlberg A.: Comparisons of Predictive Power for Traffic Accident Involvement; Celeration Behaviour versus Age, Sex, Ethnic Origin, and Experience. Safety. 2018, 4(4), 59, DOI: 10.3390/safety4040059.
2.
Af Wåhlberg A.: The stability of driver acceleration behavior, and a replication of its relation to bus accidents. Accident Analysis & Prevention. 2004, 36(1), 83–92, DOI: 10.1016/S0001-4575(02)00130-6.
3.
Ameen H.A., Mahamad A.K., Saon S., Ahmadon M.A.: Yamaguchi S.: Driving Behaviour Identification based on OBD Speed and GPS Data Analysis. Advances in Science, Technology and Engineering Systems Journal. 2021, 6(1), 550–569, DOI: 10.25046/aj060160.
4.
Biggs H.C., Dingsdag D.P., Stenson N.: Fatigue factors affecting metropolitan bus drivers: a qualitative investigation. Work. 2009, 32(1), 5–10, DOI: 10.3233/WOR-2009-0810.
5.
Bobermin M.P., Silva M.M., Ferreira S.: Driving simulators to evaluate road geometric design effects on driver behaviour: A systematic review. Accident Analysis & Prevention. 2021, 150, 105923, DOI: 10.1016/j.aap.2020.105923.
6.
Bokare P.S., Maurya A.K.: Acceleration-Deceleration Behaviour of Various Vehicle Types. Transportation Research Procedia. 2017, 25, 4733–4749, DOI: 10.1016/j.trpro.2017.05.486.
7.
Brambilla M., Mascetti P., Mauri A.: Comparison of different driving style analysis approaches based on trip segmentation over GPS information. 2017 IEEE International Conference on Big Data (Big Data). 2017, 3784–3791, DOI: 10.1109/BigData.2017.8258379.
8.
Camacho-Torregrosa F.J., Pérez-Zuriaga A.M., Campoy-Ungría J.M., García-García A.: New geometric design consistency model based on operating speed profiles for road safety evaluation. Accident Analysis & Prevention. 2013, 61, 33–42, DOI: 10.1016/j.aap.2012.10.001.
9.
Davey J., Freeman J., Wishart D.A.: Study predicting crashes among a sample of fleet drivers. Road Safety Research, Policing and Education Conference, Gold Coast, Australia, 2006.
10.
Delhomme P., Gheorghiu A.: Perceived stress, mental health, organizational factors, and self-reported risky driving behaviors among truck drivers circulating in France. Journal of Safety Research. 2021, 79, 341–351, DOI: 10.1016/j.jsr.2021.10.001.
11.
Eboli L., Mazzulla G., Pungillo G.: Combining speed and acceleration to define car users’ safe or unsafe driving behaviour. Transportation Research Part C: Emerging Technologies. 2016, 68, 113–125, DOI: 10.1016/j.trc.2016.04.002.
12.
Fugiglando U., Massaro E., Santi P., Milardo S., Abida K., Stahlmann R., et al.: Driving Behavior Analysis through CAN Bus Data in an Uncontrolled Environment. IEEE Transactions on Intelligent Transportation Systems. 2019, 20(2), 737–748, DOI: 10.1109/TITS.2018.2836308.
13.
Greenberg J.A., Blommer M.: Physical Fidelity of Driving Simulators. CRC Press, New York, USA, 2011.
14.
Guilford J.P.: Fundamental Statistics in Psychology and Education. McGraw-Hill, New York, 1965.
15.
Guo J., Liu Y., Zhang L., Wang Y.: Driving Behaviour Style Study with a Hybrid Deep Learning Framework Based on GPS Data. Sustainability. 2018, 10(7), 2351, DOI: 10.3390/su10072351.
16.
Han W., Zhao J.: Driver behaviour and traffic accident involvement among professional urban bus drivers in China. Transportation Research Part F: Traffic Psychology and Behaviour. 2020, 74, 184–197, DOI: 10.1016/j.trf.2020.08.007.
17.
Hlotova Y., Cats O., Meijer S.: Measuring Bus Driver’s Occupational Stress under Changing Working Conditions. Transportation Research Record. 2014, 2415, 13–20, DOI: 10.3141/2415-02.
18.
Ishikawa Y., Kobayashi A., Minamikawa A., Ono C.: Predicting a Driver's Personality from Daily Driving Behavior. Tenth International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design. New Mexico, USA, 2019, DOI: 10.17077/drivingassessment.1696.
19.
Jurecki R.: Influence of the scenario complexity and the lighting conditions on the driver behaviour in a car-following situation. The Archives of Automotive Engineering – Archiwum Motoryzacji. 2019, 83(1), 151–173, DOI: 10.14669/AM.VOL83.ART11.
20.
Jurecki R.S., Stańczyk T.L.: A Methodology for Evaluating Driving Styles in Various Road Conditions. Energies. 2021, 14(12), 3570, DOI: 10.3390/en14123570.
21.
Khoo H.L., Ahmed M.: A Case Study of Public Bus Driver Behaviour at Batu Feringghi. Journal of the Eastern Asia Society for Transportation Studies. 2015, 11(2015), 1982–1998, DOI: 10.11175/easts.11.1982.
22.
Lee B., Chung W.: Driver Alertness Monitoring Using Fusion of Facial Features and Bio-Signals. IEEE Sensors Journal. 2012, 12(7), 2416–2422, DOI: 10.1109/JSEN.2012.2190505.
23.
Li G., Wang Y., Zhu F., Sui X., Wang N., Qu X., et al.: Drivers’ visual scanning behavior at signalized and unsignalized intersections: A naturalistic driving study in China. Journal of Safety Research. 2019, 71, 219–229, DOI: 10.1016/j.jsr.2019.09.012.
24.
Liu R., Zhao X., Zhu X., Ma J.: Statistical characteristics of driver acceleration behaviour and its probability model. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering. 2022, 236(2–3), 395–406, DOI: 10.1177/09544070211018039.
25.
Ma X., Andreasson I.: Behavior Measurement, Analysis, and Regime Classification in Car Following. IEEE Transactions on Intelligent Transportation Systems. 2007, 8(1), 144–156, DOI: 10.1109/TITS.2006.883111.
26.
Malik M., Nandal R., Dalal S., Jalglan V., Le D.: Driving pattern profiling and classification using deep learning. Intelligent Automation & Soft Computing. 2021, 28(3), 887–906, DOI: 10.32604/iasc.2021.016272.
27.
Montella A., Pariota L., Galante F., Imbriani L.L., Mauriello F.: Prediction of Drivers’ Speed Behavior on Rural Motorways Based on an Instrumented Vehicle Study. Transportation Research Record. 2014, 2434(1), 52–62, DOI: 10.3141/2434-07.
28.
Niezgoda M., Kamiński T., Kruszewski M., Tarnowski A.: Self - reported drivers’ behaviour : an application of DBQ in Poland. Journal of KONES. 2013, 20(1), 233–238. DOI: 10.5604/12314005.1136157.
29.
Omar N., Prasetijo J., Daniel B.D., Abdullah M.A.E., Ismail I.: Study of Car Acceleration and Deceleration Characteristics at Dangerous Route FT050. IOP Conference Series: Earth and Environmental Science. 2018, 140, 012078, DOI: 10.1088/1755-1315/140/1/012078.
30.
Puchalski A., Komorska I.: Driving style analysis and driver classification using OBD data of a hybrid electric vehicle. Transport Problems. 2020, 15(4), 83–94, DOI: 10.21307/tp-2020-050.
31.
Rohani M.M., Buhari R.: Bus Driver: Factors That Influences Behaviour. 9th International Conference of Geotechnical and Transportation Engineering (GEOTROPIKA) and 1st International Conference on Construction and Building Engineering (ICONBUILD) – GEOCON2013, Johor Bahru, Malaysia, 2013.
32.
Szumska E.M., Jurecki R.: The Effect of Aggressive Driving on Vehicle Parameters. Energies. 2020, 13(24), 6675, DOI: 10.3390/en13246675.
33.
Szumska E.M., Stańczyk T.L., Zuska A., Grabski P., Jaśkiewicz M., Jurecki R., et al.: Experimental testing of longitudinal acceleration in urban buses. IOP Conference Series: Materials Science and Engineering. 2022, 1247, 012017, DOI: 10.1088/1757-899X/1247/1/012017.
34.
Useche S.A., Ortiz V.G., Cendales B.E.: Stress-related psychosocial factors at work, fatigue, and risky driving behavior in bus rapid transport (BRT) drivers. Accident Analysis & Prevention. 2017, 104, 106–114, DOI: 10.1016/j.aap.2017.04.023.
35.
Vaiana R., Iuele T., Astarita V., Caruso M.V., Tassitani A., Zaffino C., et al.: Driving Behavior and Traffic Safety: An Acceleration-Based Safety Evaluation Procedure for Smartphones. Modern Applied Science. 2014, 8(1), 88–96, DOI: 10.5539/mas.v8n1p88.
36.
Vaitkus V., Lengvenis P., Žylius G.: Driving style classification using long-term accelerometer information. 19th International Conference on Methods and Models in Automation and Robotics (MMAR), Miedzyzdroje, Poland, 2014, 641–644, DOI: 10.1109/MMAR.2014.6957429.
37.
Zaranka J., Pečeliūnas R., Žuraulis V.: A Road Safety-Based Selection Methodology for Professional Drivers: Behaviour and Accident Rate Analysis. International Journal of Environmental Research and Public Health. 2021, 18(23), 12487, DOI: 10.3390/ijerph182312487.
38.
Zhang C., Patel M., Buthpitiya S., Lyons K., Harrison B., Abowd G.D.: Driver Classification Based on Driving Behaviors. 21st International Conference on Intelligent User Interfaces (IUI '16). Association for Computing Machinery, New York, NY, USA, 2016, 7–10, 80–84, DOI: 10.1145/2856767.2856806.
39.
Zhang Z., Zhang X., Ji J., Lin S., Wang K., Ma T., et al.: A Study on the Differences in Driving Skills of Chinese Bus and Taxi Drivers. Journal of Advanced Transportation. 2019, 2019, 8675318, DOI: 10.1155/2019/8675318.
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