How to use AI technology to improve the safety of autonomous driving

The concept of intelligent transportation has been around for a long time, but in recent times, AI has become a major topic in the transportation industry. Advances in self-driving cars, smart city systems, and vehicle safety technology are driving the in-depth application of AI in the transportation field. "Intelligent transportation systems are the product of the combination of artificial intelligence technology and urban planning." Dana Ross, professor of electrical and computer engineering at University College London, said, "Transportation is one of the most important components of human society. It is the core that connects cities and the world." Ross said: "We need to understand how artificial intelligence technology works in this field and ensure that AI systems can best serve us."

1. Self-driving cars

Self-driving cars are changing the transportation industry, and their widespread adoption will bring about a huge change in the way people travel. As technology advances, self-driving cars are also growing and are expected to completely replace human drivers in the next 10 years. But at present, self-driving cars are still in the development stage and are subject to many limitations. For example, in order for self-driving cars to better understand the world and environment around them, they need to know their operating conditions and know how to respond to any events that occur in the surrounding environment. This is why cars need to be equipped with high-precision maps and sensors to understand where they are and know how to perceive the surrounding environment. Many companies are developing self-driving technology, and some of them have already launched commercial vehicle products. Waymo, owned by Google, is the first company that is fully committed to the development of self-driving technology. The company is already testing self-driving cars and has conducted road tests in parts of Arizona, California, and Texas.

Self-driving cars are gradually becoming an integral part of people's daily lives. People can book online ride-hailing cars through mobile phone applications and receive suggestions and routes from drivers even minutes before the trip. According to a report released by Waymo in 2022, each self-driving car will save about $1,500 in fuel costs per year. This figure may not be very precise, but it shows some of the advantages of self-driving cars: no driver intervention is required. At present, many large automakers have launched self-driving car products or plan to produce such vehicles. For example, General Motors and Ford are actively developing their own self-driving technology; in addition, some small manufacturers and technology companies are also considering providing their own self-driving technology products or services. In China, in addition to car companies, most mobile phone manufacturers are involved in the field of self-driving. As technology companies continue to develop and improve their self-driving systems, it will become one of the most important developments in the field of intelligent transportation.

Automated driving systems require a lot of data to train their functions, and this data is already stored in sensors and other on-board technologies. "The transportation industry has realized that if they want to improve efficiency and reduce the possibility of traffic accidents, they must have a reliable and safe automated driving system," Ross said. "However, this is also an extremely complex task: it must be able to identify and predict the possibility of traffic conditions and dangerous situations; it must also be able to identify and avoid dangerous situations." To achieve this goal, artificial intelligence technology will become a very important component in this field. "It is crucial that artificial intelligence technology can help autonomous vehicles identify and avoid traffic accidents; at the same time, it can also help autonomous vehicles better understand the surrounding environment and make correct decisions." However, there are some limitations to the application of artificial intelligence technology in the transportation field: for example, there are many factors in the traffic system that may affect the identification and judgment of these factors by the autonomous vehicle system; at the same time, if there is no human intervention, the automated system may make wrong judgments when handling road conditions.

2. Intelligent Transportation System

Professor Ross pointed out that the intelligent transportation system is a highly complex system that involves a variety of technologies and tools. Autonomous vehicles, vehicle safety technologies, and smart city systems are all part of the intelligent transportation system. Professor Ross explained: "Autonomous vehicle technology occupies an important position in this field because it helps improve the safety and efficiency of the entire city. Autonomous vehicles can make traffic smoother, reduce traffic congestion, and achieve zero emissions throughout the city." In the smart city system, the advancement of vehicle safety technology is promoting the development of vehicle autonomous driving. "As vehicle autonomous driving technology matures, we can see more automation and intelligence in different city ranges. For example, in the Los Angeles area, many pedestrians are anticipated by autonomous vehicles when crossing intersections. This makes traffic smoother and reduces traffic congestion." Ross said. Professor Ross believes that one of the most important technologies in the smart city system is the "Intelligent Traffic Signal" (ITS) system. The ITS system uses sensors to collect vehicle and pedestrian data and uses artificial intelligence algorithms for analysis, thereby improving traffic efficiency and safety. Professor Ross explained: “ITS is vital to urban development because it helps city planners understand how to make the most of limited transport resources. Therefore, AI has great potential in ITS, as it can enable city planners to better understand how to best use existing resources to meet people’s needs and expectations.”

1. ITS system based on artificial intelligence

Professor Ross pointed out that the application of artificial intelligence in ITS systems mainly focuses on the following three aspects: First, traffic flow can be optimized by detecting vehicles. For example, artificial intelligence algorithms can be used to analyze vehicle data and adjust traffic lights based on this data. Professor Ross said: "Although traditional signal control methods can also be used to control traffic lights, these methods cannot accurately predict traffic flow, so they can only provide a rough estimate of traffic flow." Secondly, artificial intelligence algorithms can be used to determine the best travel time. Professor Ross said: "Because the ITS system is a large and complex system, using traditional methods alone cannot effectively optimize traffic. However, using artificial intelligence algorithms to determine the best travel time can effectively reduce traffic congestion and improve traffic efficiency."

2. Other applications of AI in transportation

In addition to self-driving cars and intelligent transportation systems, AI is also playing an important role in other areas. Professor Ross explained: "Another application of AI in the field of transportation is to optimize public transportation routes. AI algorithms can improve the operating efficiency of buses by analyzing data from bus companies and calculating the most efficient route planning." "In public transportation route optimization, AI can use image processing and deep learning to detect problems and propose better solutions. For example, an AI system can identify vehicle routes, passenger numbers and route planning of a bus company. If the system finds that there are too many buses, it can deploy them through an intelligent bus network." Professor Ross said. Professor Ross pointed out: "In some countries, governments are promoting the development of intelligent transportation systems by encouraging the development of self-driving cars. For example, the Australian government is building a smart city system to reduce the number of vehicles on the road. By using AI algorithms and image processing technology to identify traffic problems and propose solutions, we can see that intelligent transportation systems will play a greater role in the coming years."

3. AI technology improves the safety of autonomous driving

The improvement of the safety of autonomous vehicles is due to the development and application of multiple AI technologies:

1. Computer Vision

Computer vision plays a vital role in self-driving cars, giving them the ability to perceive and understand their surroundings. Through computer vision applications, self-driving cars can perform tasks such as depth estimation, object detection, lane detection, traffic sign recognition, and night vision. These capabilities ensure that vehicles can drive safely in complex environments.

2. Deep Learning

The basis of the perception system is deep learning, which is mainly responsible for image processing and interpretation in the field of autonomous driving. Deep learning can achieve high-precision perception tasks and improve the performance of subsystems such as target detection and classification, multi-target tracking, and scene understanding by learning from large amounts of data.

3. Perception system

The perception system uses deep learning architecture and sensors such as cameras, LiDAR, and radar to perceive the environment. These systems provide self-driving cars with rich environmental information and assist in obstacle detection and avoidance.

4. Decision-making algorithm

The decision-making algorithms of self-driving cars can analyze environmental data and make corresponding driving decisions based on the data, such as turning left, turning right, avoiding or overtaking, etc. These algorithms ensure that the vehicle can follow traffic rules while ensuring safety.