Intersection collision warning systems are essential for crash prevention and safety, as they decrease the probability of crashes in intersections. These systems use sophisticated sensors and communications technologies to inform drivers of possible collision hazards, giving them the necessary information for determining behaviors that would help prevent accidents. The trend in the last decade is towards developing and implementing intersection collision warning systems to improve road safety (Zhang et al., 2024). This literature review aims to provide a general overview of intersection collision warning technology, its areas where it can be used, and known strengths and weaknesses related to the introduction.
A study by Li et al. (2024) shows that intersection collision warning technology covers a variety of systems aimed at reducing the risk associated with collisions in intersections. It is developed to inform drivers of likely collisions at crossroads, where the chance for accidents is strongest due to convoluted traffic patterns and possible blind spots. Vehicle approaching detection is typically done with a combination of sensor cameras and radar, whereby the drivers are warned visually or acoustically if a collision risk exists.
In Alexander & Frith’s (2021) article, the e-NOTIFY system is described according to which this specific application of intersection collision warning technology helps efficient information communication about accidents, focusing on improving emergency services’ response time. The e-NOTIFY system uses onboard units installed in vehicles that collect accident information and communicate it to an external control unit. The control unit then determines the magnitude of the occurrence and alerts responding emergency agencies instead of relying on surviving eyewitnesses for accident notifications. In yet another source, an IoT-based accident detection system was developed, which could detect accidents and locate the place of incidence using different sensors. These sensors include the pressure points to identify a collision while incorporating GPS technology to identify the exact location. Additionally, a microphone is used to feed in the sound of the accident area and be sent off to the destination helper for better comprehension of what happened (Wang et al., 2021). Moreover, the technology uses fuzzy logic and fault-tolerance mechanisms to provide a fast response time when driving in dangerous situations where drivers are drowsy.
In various real-world interventions, intersection collision warning systems have been used in urban intersections, highway junctions and high-traffic areas. Examples include road accident prediction and prevention, faster emergency response times, and better overall highway safety. According to Yue et al. (2021), the Departments of Transportation (DOTs) and automotive manufacturers have championed the implementation of these technologies for better road safety. For instance, some DOTs have fused intersection collision warning systems with traffic signal control systems to alert drivers approaching intersections in real-time. Moreover, an IoT-based collision detection system has been designed that uses various sensors to determine the amount of pressure exerted on the carrier as a result, and location information is gathered through GPS. In addition, a microphone is used to capture the sound of the accident area and transmit it to an external helper for a better understanding of what happened. Intersection collision warning systems are needed to reduce the side-impact collision and pedestrian accidents that mainly occur at busy intersections in urban areas. These systems are used in highways to prevent collisions on complex interchanges and merge points. Intersection collision warning technology can be used in rural areas as a safety measure at uncontrolled intersections with little to no traffic (Zhang et al., 2024). On the other hand, automotive companies have adopted these systems into Advanced Driver Assistance Systems (ADAS) to make vehicles safer.
Applying intersection collision warnings has shown several key advantages in preventing collisions and achieving a more general level of road safety. These advantages include reduced intersection accidents, increased driver awareness and better situational understanding at complex intersections. If adequately maintained, these systems can offer timely warnings to drivers. They may thus prevent T-bone crashes along with other intersection-related collisions, saving people’s lives while reducing the economic burden that comes in the wake of road accidents. As outlined by Wang, Guo, & Yang (2021), there are several advantages associated with intersection collision warning technology. Such technologies also include the reduction of response time delay between accidents and emergency service notifications, improving detection accuracy through sensor use of advanced algorithms, enhanced safety control at intersections by alerting drivers of impending collisions, and assisting accident reconstruction process during events data recording. Research has also shown that these systems can drastically lower the occurrence of intersection crashes by warning drivers about possible dangers and making them veer away from potential impacts (Rachakonda & Pawar, 2023). With timely warnings, intersection collision warning technology can prevent catastrophic injuries and fatalities associated with intersection collisions.
The advantages that intersection collision warning systems could bring are coupled with shortcomings and challenges. A critical flaw is the possibility of false alarms or drivers’ over-reliance on technology that produces complacency and distraction. Moreover, environmental conditions like bad weather or physically obstructed visual fields may interfere with the work of such systems. In addition, more new technology at intersections, such as collision warnings, must be available on low-end or older vehicles, especially in emerging nations where other manufacturers do not install this system (Li et al., 2024). Additionally, there could be issues relating to the operational cost of introducing and maintaining such advanced technologies, especially in smaller municipalities or regions with limited financial power.
In other words, intersection collision warning technology is a new safety approach using crash prevention measures at intersections. It uses several sensors and computer algorithms that identify accidents in real time to alert emergency services. Additionally, it uses fuzzy logic and fault tolerance to improve accuracy and offer a reaction time in hazardous situations. However, although these systems have great promise in reducing road accidents and increasing safety ratings, it is crucial to deal with their weaknesses and challenges adequately. Improvements in the accuracy and reliability of intersection collision sensors will be required, together with consideration given to strategies that could address some potential drawbacks associated with their implementation. In summary, intersection collision warning technology is a valuable device created to prevent collisions and enhance road safety.
References
Alexander, S., & Frith, K. H. (2021). Using Nursys® as a primary source for licensure information. Nursing Education Perspectives, 42(3), 200–201.
Li, L., Zhang, Z., Xu, Z. G., Yang, W. C., & Lu, Q. C. (2024). The role of traffic conflicts in roundabout safety evaluation: a review. Accident Analysis & Prevention, 196, 107430.
Rachakonda, Y., & Pawar, D. S. (2023). Evaluation of intersection conflict warning system at unsignalized intersections: A review. Journal of Traffic and Transportation Engineering (English Edition). Retrieved from: https://www.sciencedirect.com/science/article/pii/S2095756423000752
Wang, J., Guo, X., & Yang, X. (2021). Efficient and safe strategies for intersection management: a review. Sensors, 21(9), 3096.
Yue, L., Abdel-Aty, M., Wu, Y., Ugan, J., & Yuan, C. (2021). Effects of forward collision warning technology in different pre-crash scenarios. Transportation research part F: Traffic psychology and behavior, 76, 336-352.
Zhang, J., Chen, N., Chen, Y., Wang, P., & Zhang, Y. (2024). Intersection collision risk evaluation and active collision avoidance strategies for autonomous vehicles. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 09544070231223676.
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