This research analyzes Taiwan region’s five years of accident data (2016-2020), focusing on bus-related incidents to identify prevalent accident types, crash factors, and locations. Simultaneously, this study has collected interviews with 40 bus drivers, which were conducted to understand their experiences with ADAS and perceived blind spots. The findings reveal that the right front, right side, and front of the bus are the most common impact areas in crashes, often involving motorcycles and pedestrians. Despite the potential benefits of ADAS in enhancing safety, the bus drivers remain system inconvenient. These factors included a high failure rate of the ADAS system, delays in video information transmission between the bus camera and the ADAS system, low image resolution and inadequate panel screen size, distracting warning tones of the system and inadequate knowledge of ADAS systems. The study emphasizes the necessity for tailored ADAS functions that address specific blind spots and driving conditions encountered by bus drivers. Recommendations include enhancing ADAS features to improve driver awareness of potential hazards, aiming to reduce the severity and frequency of bus-related accidents. The results underscore the importance of aligning technological advancements with professional drivers’ practical needs and concerns, advocating for further research to enhance ADAS effectiveness in real-world driving scenarios.
References
[1]
Asadianfam, S., Shamsi, M., & Rasouli Kenari, A. (2020). Big Data Platform of Traffic Violation Detection System: Identifying the Risky Behaviors of Vehicle Drivers. MultimediaToolsandApplications,79, 24645-24684. https://doi.org/10.1007/s11042-020-09099-8
[2]
Baldwin, C. L., May, J. F., & Parasuraman, R. (2014). Auditory Forward Collision Warnings Reduce Crashes Associated with Task-Induced Fatigue in Young and Older Drivers. InternationalJournalofHumanFactorsandErgonomics,3, 107-121. https://doi.org/10.1504/ijhfe.2014.067804
[3]
Cicchino, J. B. (2017). Effectiveness of Forward Collision Warning and Autonomous Emergency Braking Systems in Reducing Front-To-Rear Crash Rates. AccidentAnalysis&Prevention,99, 142-152. https://doi.org/10.1016/j.aap.2016.11.009
[4]
Cicchino, J. B. (2018). Effects of Blind Spot Monitoring Systems on Police-Reported Lane-Change Crashes. TrafficInjuryPrevention,19, 615-622. https://doi.org/10.1080/15389588.2018.1476973
[5]
Cicchino, J. B., & McCartt, A. T. (2015). Critical Older Driver Errors in a National Sample of Serious U.S. Crashes. AccidentAnalysis&Prevention,80, 211-219. https://doi.org/10.1016/j.aap.2015.04.015
[6]
Consumer Reports (2019). Guideto Lane Departure Warningand Lane Keeping Assist. https://www.consumerreports.org/car-safety/lane-departure-warning-lane-keeping-assist-guide
[7]
Eckoldt, K., Knobel, M., Hassenzahl, M., & Schumann, J. (2012). An Experiential Perspective on Advanced Driver Assistance Systems. ITIT,54, 165-171. https://doi.org/10.1524/itit.2012.0678
[8]
Eichelberger, A. H., & McCartt, A. T. (2014). Volvo Drivers’ Experiences with Advanced Crash Avoidance and Related Technologies. TrafficInjuryPrevention,15, 187-195. https://doi.org/10.1080/15389588.2013.798409
[9]
Engström, J., Werneke, J., Bärgman, J., Nguyen, N., & Cook, B. (2013). Analysis of the Role of Inattention in Road Crashes Based on Naturalistic On-Board Safety Monitoring Data. In 3rdInternationalConferenceonDriverDistractionandInattention (p. 17). SAFER Vehicle and Traffic Safety Centre.
[10]
Greenwood, P. M., Lenneman, J. K., & Baldwin, C. L. (2022). Advanced Driver Assistance Systems (ADAS): Demographics, Preferred Sources of Information, and Accuracy of ADAS Knowledge. TransportationResearchPartF:TrafficPsychologyandBehaviour,86, 131-150. https://doi.org/10.1016/j.trf.2021.08.006
[11]
Gu, X., Abdel-Aty, M., Xiang, Q., Cai, Q., & Yuan, J. (2019). Utilizing UAV Video Data for In-Depth Analysis of Drivers’ Crash Risk at Interchange Merging Areas. AccidentAnalysis&Prevention,123, 159-169. https://doi.org/10.1016/j.aap.2018.11.010
[12]
Hadi, M., Islam, M. A., Afreen, S., & Wang, T. (2021). Evaluation of an Advanced Driver-Assistance System to Reduce Pedestrian and Rear-End Crashes of Transit Vehicles. Transportation Research Record: Journal of the Transportation Research Board, 2675, 1301-1309. https://doi.org/10.1177/03611981211026302
[13]
Hancock, P. A., Kajaks, T., Caird, J. K., Chignell, M. H., Mizobuchi, S., Burns, P. C. et al. (2020). Challenges to Human Drivers in Increasingly Automated Vehicles. HumanFactors:TheJournaloftheHumanFactorsandErgonomicsSociety,62, 310-328. https://doi.org/10.1177/0018720819900402
[14]
Hubele, N., & Kennedy, K. (2018). Forward Collision Warning System Impact. Traffic Injury Prevention, 19, S78-S83. https://doi.org/10.1080/15389588.2018.1490020
[15]
Institute of Transportation (2016-2020). Traffic Accident Data [Data File]. TPE.
[16]
Jansen, R. J., & Varotto, S. F. (2022). Caught in the Blind Spot of a Truck: A Choice Model on Driver Glance Behavior Towards Cyclists at Intersections. Accident Analysis & Prevention, 174, Article ID: 106759. https://doi.org/10.1016/j.aap.2022.106759
[17]
Johansson, M., Ekman, F., Karlsson, M., Strömberg, H., & Jonsson, J. (2022). ADAS at Work: Assessing Professional Bus Drivers’ Experience and Acceptance of a Narrow Navigation System. Cognition,Technology&Work,24, 625-639. https://doi.org/10.1007/s10111-022-00704-4
[18]
McDonald, A., Camey, C., & McGehee, D. V. (2024). Vehicle Owners; Experienceswithand Reactions to Advanced Driver Assistance Systems. https://trid.trb.org/View/1562298
[19]
Mele, J. (2018). Will Fleets Turn to Advanced Safety Tech for Improvement? https://www.fleetowner.com/safety/article/21703052/will-fleets-turn-to-advanced-safety-tech-for-improvement
[20]
National Safety Council (2020). Advanced Driver Assistance Systems. Injury Facts. https://injuryfacts.nsc.org/motor-vehicle/occupant-protection/advanced-driver-assistance-systems
[21]
Peden, M., & Sminkey, L. (2004). World Health Organization Dedicates World Health Day to Road Safety. InjuryPrevention,10, 67-67. https://doi.org/10.1136/ip.2004.005405
[22]
Reagan, I. J., Cicchino, J. B., Kerfoot, L. B., & Weast, R. A. (2018). Crash Avoidance and Driver Assistance Technologies—Are They Used? TransportationResearchPartF:TrafficPsychologyandBehaviour,52, 176-190. https://doi.org/10.1016/j.trf.2017.11.015
[23]
Saffarian, M., de Winter, J. C. F., & Happee, R. (2012). Automated Driving: Human-Factors Issues and Design Solutions. ProceedingsoftheHumanFactorsandErgonomicsSocietyAnnualMeeting,56, 2296-2300. https://doi.org/10.1177/1071181312561483
[24]
Schindler, R., & Bianchi Piccinini, G. (2021). Truck Drivers’ Behavior in Encounters with Vulnerable Road Users at Intersections: Results from a Test-Track Experiment. AccidentAnalysis&Prevention,159, Article ID: 106289. https://doi.org/10.1016/j.aap.2021.106289
[25]
Seppelt, B. D., Seaman, S., Lee, J., Angell, L. S., Mehler, B., & Reimer, B. (2017). Glass Half-Full: On-Road Glance Metrics Differentiate Crashes from Near-Crashes in the 100-Car Data. AccidentAnalysis&Prevention,107, 48-62. https://doi.org/10.1016/j.aap.2017.07.021
[26]
Souders, D. J., Charness, N., Roque, N. A., & Pham, H. (2020). Aging: Older Adults’ Driving Behavior Using Longitudinal and Lateral Warning Systems. HumanFactors:TheJournaloftheHumanFactorsandErgonomicsSociety,62, 229-248. https://doi.org/10.1177/0018720819864510
[27]
Susilawati, S., Wong, W. J., & Pang, Z. J. (2022). Safety Effectiveness of Autonomous Vehicles and Connected Autonomous Vehicles in Reducing Pedestrian Crashes. TransportationResearchRecord:JournaloftheTransportationResearchBoard,2677, 1605-1618. https://doi.org/10.1177/03611981221108984
[28]
Tu, Y., Wang, W., Li, Y., Xu, C., Xu, T., & Li, X. (2019). Longitudinal Safety Impacts of Cooperative Adaptive Cruise Control Vehicle's Degradation. JournalofSafetyResearch,69, 177-192. https://doi.org/10.1016/j.jsr.2019.03.002
[29]
Wang, T., Chen, Y., Yan, X., Chen, J., & Li, W. (2020). The Relationship between Bus Drivers’ Improper Driving Behaviors and Abnormal Vehicle States Based on Advanced Driver Assistance Systems in Naturalistic Driving. Mathematical Problems in Engineering, 2020, Article ID: 9743504. https://doi.org/10.1155/2020/9743504
[30]
Wang, X., Jiao, Y., Huo, J., Li, R., Zhou, C., Pan, H. et al. (2021). Analysis of Safety Climate and Individual Factors Affecting Bus Drivers’ Crash Involvement Using a Two-Level Logit Model. AccidentAnalysis&Prevention,154, Article ID: 106087. https://doi.org/10.1016/j.aap.2021.106087
[31]
Woodrooffe, J., Blower, D., & Green, P. E. (2012). Safety Performance and Benefits of Heavy Truck Stability Control: Providing Insight into Compliance Evaluation. SAEInternationalJournalofCommercialVehicles,5, 429-440. https://doi.org/10.4271/2012-01-1906
[32]
World Health Organization (WHO) (2018). Global Status Reporton Road Safety 2018:Summary. https://www.who.int/publications/i/item/9789241565684
[33]
Xu, Y., Ye, Z., & Wang, C. (2021). Modeling Commercial Vehicle Drivers’ Acceptance of Advanced Driving Assistance System (ADAS). JournalofIntelligentandConnectedVehicles,4, 125-135. https://doi.org/10.1108/jicv-07-2021-0011