Traffic jams are a common problem in urban areas. It kills time, reduces productivity, wastes fuel, and causes air pollution. Various advanced measures have been taken to control vehicles; AI (artificial intelligence) technologies are one of them. In this post, we will be sharing an overview of how AI helps in traffic control and road safety.
Adaptive Traffic Signal: Sensors and CCTV cameras of AI devices monitor the speed, traffic number, condition, etc. All videos and readings are processed accurately and transferred to the adaptive control system to make decisions accordingly. Then, it can change the traffic signal cycle with respect to the current vehicle conditions. The duration is generally longer when traffic congestion is high. This promising technique can make signalized intersections more efficient and well-managed.
Real-Time Management: AI technologies like Intelligent Traffic Management System (ITMS) are delivering excellent performance in recent years. They play a massive role in enhancing transport productivity, traffic reliability, and vehicle connectivity. Their operations include traffic monitoring via security cameras, lane-by-lane analysis, recording motions, listing nameplates, suggesting safer lanes, estimating congestion rates at a particular time, etc. Most systems also generate real-time warnings about road conditions and possible clashes for the drivers. If any accident happens, they send an emergency message to nearby hospitals and police stations.
Security: Since AI-based methods include roadways surveillance, they can provide quick details to the security regarding kidnapping, accidents, robber attacks, violence, and natural calamities. Besides, they can detect disobeying cars, track details, and investigate other violations with high accuracy. They store these huge amounts of data, pictures, and CCTV footage in cloud storage, which the authorities can access as per demand.
Safety: Many researchers claim that AI technologies can reduce road fatalities and deaths significantly. As these models improve vehicle coordination, the chances of clashing minimize automatically. They work on safer roads, smarter traffic, pre-crash alerts, and post-crash responses too. By reviewing past data, AI algorithms find out collision rates, and risky areas, and suggest solutions to avoid them. Moreover, their recorded information can be helpful to an accident victim, insurance company, pedestrian accident lawyer, car crash attorney, and police.
Automation: The vehicle industry has launched numerous electric cars, super-cars, racing cars, and regular transports with autonomous features. They usually cover high-precision sensors, actuators, high-end processors, 360° vision systems, lidars, radars, etc. Such cars are ideal for people with limited mobility. Although the crash percentage of autonomous two-wheelers is not zero yet, it is way lower than human driving. However, there are still some complications and we shouldn’t fully rely on these vehicles.
Travel Demands Analysis: AI tools can predict travel demand in the upcoming days based on the previous data. Similarly, they can be designed to estimate the number of tourists, transports, and trips in a specific period. As a result, the traffic management authorities can prepare to cope with the sudden changes.
Pedestrian And Cyclists Behavior Analysis: Road accidents take the lives of many pedestrians and cyclists every year. Complex AI algorithms of pedestrian behavior models have the potential to cut down the number. Like the vehicles, they predict how many pedestrians and cyclists will cross a road, who ignores the traffic rules, who uses the flyovers and who doesn’t, etc. These smart systems can understand if a particular street needs more crossings, cameras, and traffic lights by analyzing the behaviors.
