Free Research Paper Sample on Advanced Driver Assistance Systems

Introduction

Technology is the discipline of art or science of applying scientific knowledge to practical problems. Contemporarily, car safety technological advancements have been made by several vehicle manufacturers in a bid to enhance passengers’ comfort and safety. Among these car safety technologies are the Advanced Driver Assistance Systems (ADAS) aimed at assisting drivers with the task and minimize accidents. They include; Adaptive Cruise Control (ACC) that enables a car to maintain its speed until it encounters slower traffic, Autonomous Emergency Braking (AEB) that detects impending crashes and brakes automatically, and the Lane-Keeping Support (LSK) that assists drivers to avoid unintentional switching of lanes. These systems have been proved to contribute significantly to pursue the "Vision Zero" initiative that aims at eliminating all traffic fatalities and serious injuries (Stark et al, 2019). However, may a times ADAS have proved not to be absolute in preventing road accidents and to an extent their failures lead to fatal accidents. For instance, using the ACC system, drivers can set the gap to maintain between front traffic from close, medium, or far away (Woo et al. 2019). however, in many instances, accidents caused by this system occur when the system is locked to the vehicle in front of it, especially in a close gap, and the vehicle in front changes lanes swiftly and there is another vehicle stopped ahead. Most people prefer high-technology vehicles equipped with safety and comfort systems for smooth cruising with less driving effort.

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Research Questions

Car safety technologies are deemed to be the future of the automotive industry because they accrue benefits like making driving easier, increasing comfort, and enhancing the safety of passengers and pedestrians. However, these technologies cannot eliminate road accidents exclusively, and if misused these technologies lead to fatal accidents. Most people are migrating to high-tech vehicles fitted with driver assistance systems like the ACC, AEB, and LSK that require less driver involvement, and sadly, accidents caused by these systems are on the rise. According to a study by an insurance organization, ADAS has contributed to many accidents that involve an automated car crashing into stationary cars in front of them (Thatcham Research, nd). This is because the systems are programmed to ignore stationary objects when in motion, as a result, while on self-drive mode and the vehicle in front switches lanes quickly, the system will ignore any immediate stationary object crashing into any stationary object that could be ahead because it will not sense it quickly enough to brake before impact. Also, advanced driver assistance systems cause road accidents because they do not fully engage drivers in the activity, which makes allows them to doze off or lose concentration. ADAS has relieved drivers of tasks that keep them focused in the road, for instance, recent car models that have advanced systems like Autodrive can drive themself to destinations fed by the driver; in this case, the driver might not feel the need to concentrate on the road as they should prevent emergencies. These raise the questions and need to research whether driver assistance systems are safe, how they cause accidents, and what upgrades could make them more efficient.

Tentative Methodology

To determine how advanced driver assistance systems cause road accidents and their effectiveness, it is necessary to research the accidents the technologies resulted in. Many of these car safety technologies are recent inventions with limited scholarly data on their effectiveness and failures. Hence, the proposed research can be carried out by employing the case study method that focuses on occurrences of technology-driven accidents. Also, analyses by the engineers, insurance firms, and automotive companies will be considered to determine what causes these accidents, how frequent they occur, and how the rate is expected to change as more people switch to cars equipped with these technologies. Also, the study will consider the narratives of individual experiences and sequences reported to ascertain the cause of the accidents. All the data collected will be double-checked for authenticity and accuracy before being used for the study. After collecting the data from the various sources, it will be compounded, similarities among different incidences and reports noted, and an encompassing conclusion induced. Case study and narratives are the most suitable methods for collecting this data because; there are inefficient previous researches on the topic and they provide detailed explications of the occurrences, which deems them qualitatively reliable. The information collected will reveal how ADAS are attributed to road accidents, and provide a basis to evaluate what should be done to decimate technology-driven accidents.

Conclusion

To conclude, drivers tend to trust ADAS systems so much that they concentrate less on the road leaving the system to replace them, while others who are not acquainted with the systems may misuse them. Technical failures by car safety systems result in grisly road accidents that lead to deaths and numerous injuries, hence, more research on the effectiveness of ADAS should be done and their weaknesses noted for improvement.

References

Stark, L., Düring, M., Schoenawa, S., Maschke, J. E., & Do, C. M. (2019). Quantifying Vision Zero: crash avoidance in rural and motorway accident scenarios by the combination of ACC, AEB, and LKS projected to German accident occurrence. Traffic injury prevention, 20(sup1), S126-S132. https://www.researchgate.net/publication/334981777_Quantifying_Vision_Zero_Crash_avoidance_in_rural_and_motorway_accident_scenarios_by_combination_of_ACC_AEB_and_LKS_projected_to_German_accident_occurrence

Thatcham Research. (11 August 2020). Advanced Driver Assistance Systems.
https://www.thatcham.org/what-we-do/car-safety/driver-assistance/

Woo, H., Madokoro, H., Sato, K., Tamura, Y., Yamashita, A., & Asama, H. (2019). Advanced adaptive cruise control based on operation characteristic estimation and trajectory prediction. Applied Sciences, 9(22), 4875. file:///C:/Users/kevo/Downloads/applsci-09-04875.pdf.