## 2 Overview of Artificial Intelligence and Machine Learning in Road Transport Systems
### Advance Approaches for Incident Detectors of Road Traffic Accidents Using AI and ML  
#### 2.5.1 Incident Detectors through In-Vehicle Equipment  
Equipment installed in vehicles is crucial for detecting incidents and preventing users from irregular use. For example, installing a speed limiter is a clear way to regulate speed and prevent traffic accidents. Speed restrictions must be in line with the intended speed of the road to be successful. Speed is a major cause of accidents. Lowering the risks put forward by drivers in their choice of speed with speed restrictions serves the primary objective of improving safety. Tachographs, or speed logging devices, are examples of in-vehicle equipment [51]. Technologies for detecting and monitoring vehicles are being developed to deliver better data on speed monitoring, traffic counting, presence detection, headway measuring, and vehicle categorization [52], and several other characteristics, including symmetry, color, edge (horizontal/vertical), shadow, etc., have been employed as crucial signals for vehicle recognition because of the rectangular shape of vehicles [53]. The equipment employed in vehicles varies in classification, and the accuracy of incident detectors differs; the findings indicate that the success rate of the length-based classification of sedans, passenger trucks/SUVs, motorcycles, buses, small commercial trucks, and big commercial trucks is poor. With an extremely low classification rate between sport utility vehicles (SUVs) and small commercial vehicles, their multi-class support vector machine (SVM) classifier has an average accuracy of 74%. However, the outcome of the classification of vehicles by make and model and subjection to video resolution has not been provided [54], and based on the algorithm's comparatively greater practical value, a kind of magnetoresistive traffic flow collecting equipment with low power consumption and compact size was created. It uses the vehicle speed detection algorithm of micro-magnetoresistive vehicle detection equipment for accuracy [55]. The vehicle equipment necessary in road safety has seen a significant evolution with the introduction of active safety systems such as the anti-lock braking system, the traction control system, the stability control system, etc. Vehicle active safety systems are those that aim to prevent collisions or lower the likelihood of having one in the automobile industry [56]. In the automobile industry, on-road vehicle detection has always been the main emphasis. The inclusion of the collision avoidance system (CAS) in current automobiles may lower the accident rate by rapidly and effectively recognizing all types of vehicles and alerting drivers to the possibility of an accident. The review of sensors and methods for tracking and detecting vehicles for the collision avoidance system (CAS), an automobile safety system, is intended to lessen the likelihood of an accident. It may gather information on on-road traffic using various sensors (such as radar, laser, and cameras) and then identify and categorize cars. When a collision is foreseen, these devices either warn the driver or respond automatically without the driver's involvement (by braking or steering or both) [57]. What may pose a challenge for this in-vehicle equipment is the managing of the maintenance of a commercial fleet; this is an active new application field for mining and utilizing vehicle on-board sensor data for vehicle problem diagnosis and failure prediction [58]. Another type of vehicle equipment is the two loop detector that makes up the dual loop detectors. It has the ability to assess vehicle speed and length depending on the set longitudinal distance between the two loop detectors; this is a fundamental advantage of dual loop detectors over single loop detectors.