Automatic traffic monitoring by intelligent sound detection

https://flore.unifi.it/bitstream/2158/1184675/1/Active%20safety%20systems%20for%20powered%20two%20wheelers%20A%20systematic%20review%20final.pdf

Active safety systems for powered two-wheelers: A systematic review.

Vision-based vehicle detection for a driver assistance system

The effect of a collision warning system on the driving performance of young drivers at intersections

There are many types of collision warning systems to increase the safety of motorcyclists. These systems use different types of collision detection techniques with each one having some limitations, restricting the performance of the system. To find the effectiveness of collision warning system notifications, it is important to study the physiological response of drivers toward these systems. Existing studies are limited to the physiological response of car drivers and use only buzzer warnings for these systems. Unfortunately, no such work in that particular domain has been reported for motorcyclists. Since motorcycles have different maneuverability as compared with cars and other vehicles, it is important to investigate the response of motorcyclists toward these collision warning systems. Also, it is believed that providing verbal information about any potential hazard will further assist the motorcyclist to avoid it. The aim of this paper is to investigate the physiological responses of motorcyclists to the rear end collision warning system when auditory verbal warnings are utilized. To study the response of the motorcyclists, the N100, N200, P300, and N400 event-related potential components have been extracted from the recorded Electroencephalography data. It has been found that the rear end collision warning system with auditory verbal warnings significantly increases the alertness of the motorcyclist and can be helpful to avoid the possible rear-end collision scenarios. This system has shown positive effects at neural levels on motorcyclists and reduces their reaction time and attentional resources required for processing the target correctly.

Event-Related Potential Responses of Motorcyclists Towards Rear End Collision Warning System

In many Asian countries, motorcyclists have a higher fatality rate as compared to other vehicles. Among many other factors, rear end collisions are also contributing for these fatalities. Collision detection systems can be useful to minimize these accidents. However, the designing of efficient and cost effective collision detection system for motorcyclist is still a major challenge. In this paper, an acoustic information based, cost effective and efficient collision detection system is proposed for motorcycle applications. The proposed technique uses the Short time Fourier Transform (STFT) to extract the features from the audio signal and Principal component analysis (PCA) has been used to reduce the feature vector length. The reduction of feature length, further increases the performance of this technique. The proposed technique has been tested on self recorded dataset and gives accuracy of 97.87%. We believe that this method can help to reduce a significant number of motorcycle accidents.

Motorcyclists safety system to avoid rear end collisions based on acoustic signatures

The number of vehicle accidents is rapidly increasing and causing significant economic losses in many countries. According to the World Health Organization, road accidents will become the fifth major cause of death by the year 2030. To minimize these accidents different types of collision warning systems have been proposed for motor vehicle drivers. These systems can early detect and warn the drivers about the potential danger, up to a certain accuracy. Many researchers study the effectiveness of these systems by using different methods, including Electroencephalography (EEG). From the literature review, it has been observed that, these systems increase the drivers' response and can help to minimize the accidents that may occur due to drivers unconsciousness. For these collision warning systems, tactile early warnings are found more effective as compared to the auditory and visual early warnings. This review also highlights the areas, where further research can be performed to fully analyze the collision warning system. For example, some contradictions are found among researchers, about these systems' performance for drivers within different age groups. Similarly, most of the EEG studies focus on the front collision warning systems and only give beep sound to alert the drivers. Therefore, EEG study can be performed for the rear end collision warning systems, against proper auditory warning messages which indicate the types of hazards. This EEG study will help to design more friendly collision warning system and may save many lives.

A. Saeed Malik

Papers

Motorcyclists safety system to avoid rear end collisions based on acoustic signatures

Studying the response of drivers against different collision warning systems: a review