Road accidents cause the death of more than one million people every year, most often due to human error or mechanical failure, hence the importance of using artificial intelligence to reduce serious damage associated with traffic accidents, and one of its most prominent uses in this field is: autonomous vehicles, they rely on artificial intelligence to provide multiple advantages such as: collision prevention mechanisms and means to enhance road safety, with the number of these vehicles expected to exceed two billion vehicles by 2050; this type of vehicle can help reduce traffic congestion by communicating with each other. In this article we will talk about the role of artificial intelligence in the field of transport, and the most prominent technologies based on it that have been used to enhance road safety, with some real-life examples. First: artificial intelligence in the field of transport: The application of artificial intelligence in the field of transport is not new, many intelligent systems have been integrated into vehicles and transport infrastructure for a long time. However, recent developments in artificial intelligence technologies, such as machine learning, computer vision and natural language processing, have opened up new horizons for the development of more sophisticated and effective solutions. Here are some of how artificial intelligence is used in the field of Transportation: Driver assistance systems: AI-powered assistance systems can provide multiple advantages to help the driver while driving, such as: warning him when leaving the lane, helping to avoid a collision, intelligent speed control, reducing the likelihood of human errors and mitigating the impact of accidents. Traffic management: artificial intelligence can be leveraged to optimize traffic, adapt to different conditions, and dynamically adjust the timing of traffic signals, reducing congestion and reducing the risk of accidents. Predictive analytics and risk assessment: machine learning algorithms can analyze very large amounts of data, such as long-duration accident data, weather and traffic conditions, to identify potential risk factors and enable proactive safety measures. Autonomous vehicles: artificial intelligence is an essential part of autonomous vehicles, it allows these vehicles to perceive their surroundings, make decisions and navigate safely without human intervention, which can reduce accidents caused by human errors. Road monitoring and maintenance: AI-powered systems can be used to monitor the condition of roads, detect potential hazards, and prioritize maintenance, ensuring a safer infrastructure for all road users. Potential benefits of artificial intelligence in enhancing road safety and security: The integration of artificial intelligence into various aspects of the transport system provides many potential benefits, the most notable of which are: Reducing human errors: By automating certain tasks and providing advanced driver assistance features, artificial intelligence can mitigate the impact of human errors, which are one of the main causes of road accidents. Traffic optimization: traffic management systems powered by artificial intelligence can optimize traffic, reduce congestion, which is one of the contributors to accidents. Road maintenance assistance: AI-powered road monitoring and maintenance systems can proactively identify and address potential hazards, such as potholes, debris, or structural problems, and improve overall road safety. Provide personal safety solutions: artificial intelligence can provide personal safety solutions by analyzing individual driving behaviors, identifying risk factors, and providing personalized recommendations or interventions. Second: the most prominent artificial intelligence technologies to enhance road safety and security: What is the role of artificial intelligence in enhancing road safety and reducing accidents Many AI-based technologies have been used to help enhance road safety and safety and reduce accidents, most notably: Machine learning technology for predictive analytics:
Machine learning is a part of artificial intelligence, and involves the development of algorithms and statistical models that enable systems to learn from data and make predictions or make decisions without being programmed directly. In terms of road safety, machine learning techniques can be applied to identify potential risks, estimate the likelihood of accidents, and enable proactive measures. By analyzing large amounts of data, such as accident reports, traffic patterns, weather conditions, and driver behavior, machine learning algorithms can detect hidden patterns and correlations that may not be obvious to human analysts, and then these insights can be used to develop predictive models that estimate the risk of accidents in specific scenarios or locations. Natural language processing technique:
In the context of road safety, natural language processing technologies can be applied to driver monitoring and assistance systems, enabling intelligent interactions between drivers and vehicles. Through this technology, drivers can communicate with their vehicles using their natural language. this, in turn, can enhance safety by reducing driver distraction as they can keep their hands on the steering wheel and their eyes on the road while interacting with the vehicle's systems. Natural language processing can also be used to analyze the driver's speech patterns and tone, which can lead to identifying signs of fatigue, distraction, or weakness, after which this information can be used to issue alerts or start activating safety measures, such as activating autonomous driving modes or suggesting taking a break. Natural language processing technology can also be integrated with computer vision and data collected by sensors to develop comprehensive driver monitoring systems.By integrating multiple data sources, these systems can assess the driver's physical and cognitive condition, enabling personalized measures to enhance safety.
With the many benefits of natural language processing technology, the challenges lie in dealing with different accents and ambient noise conditions. Examples of practical applications of using artificial intelligence to enhance road safety and reduce accidents: Here are some real-life examples of the use of artificial intelligence technologies for the purposes of increasing road safety and reducing accidents: Tesla Autopilot system: Tesla Autopilot (Tesla Autopilot) is an advanced driver assistance system (ADAS) that combines many technologies based on artificial intelligence, such as computer vision, Waymo self-driving cars: Alphabet Inc.'s Waymo (Google's parent company) is a pioneer in the development of fully autonomous vehicles, and its self-driving car program, which started as the Google Self-Driving Car Project in 2009, has made great strides in leveraging artificial intelligence for safe and reliable autonomous driving. Waymo's self-driving cars have traveled more than 35 billion miles on public roads across multiple cities since their launch in 2022, avoided many potential collisions, and demonstrated their ability to navigate safely in complex driving conditions. Waymo vehicles are equipped with a set of advanced sensors, and the platform for these vehicles processes data from sensors to perceive the environment, predict the behaviors of other road users, and make driving decisions. Toyota Safety Sense technologies: Toyota Safety Sense is a set of safety technologies that rely on artificial intelligence and advanced sensors to provide driver assistance features aimed at enhancing safety and reducing the risk of accidents. Toyota's technology includes a pre-collision system that uses a camera and radar to detect pedestrians, vehicles, and obstacles, and can start reducing speed automatically to mitigate or avoid collisions. In addition, there is a lane departure alert that monitors lane markings and provides audio and visual alerts if the car veers off course, and a dynamic cruise control system that maintains a previously set distance between the Toyota car and the car in front of it by automatically adjusting the speed, reducing the risk of collisions. Toyota Safety Sense technologies have been widely adopted in the Toyota car range, which has contributed to improving safety and reducing accident rates. According to Toyota data, vehicles equipped with the Toyota Safety Sense system have experienced a 92% reduction in rear-end collisions compared to vehicles not equipped with the system.