With the rapid enhancement in the field of technology, the concept of Artificial Intelligence and the possibility of utilizing it for different tasks became realistic. As time flies, the capability of AI is increasing exponentially, and as a result, leading to game-changing opportunities in various fields such as the transport industry, where AI-algorithms are slowly being implemented. The innovations can manage a tremendous amount of information and reach a decision in less than a second, while for mere human beings it will take at least one minute. Therefore, such systems can provide efficiency and accessibility, both qualities that are deemed crucial for long-term sustainability.
One of the many problems in the transportation sector is traffic jams, which are especially common in urban areas. According to a private company called INRIX, in 2022, the average U.S. driver spent around 51 hours in congestion. It is absolutely clear that the transportation system should be optimized to reduce travel times and improve traffic flow, which AI actually can achieve successfully through real-time data analysis. A great example would be ATSAC (Automated Traffic Surveillance and Control) in Los Angeles, which uses detectors to change signal timing in response to specific traffic conditions. Basically, it examines vast amounts of data from cameras and sensors and then efficiently processes it to adjust signal timing. Other than that, it also prioritizes emergency vehicles by providing clear paths through intersections. This way it refines urban transportation and coordinates the traffic. In the same manner, automated cars would also aid in mitigating the issue by choosing the best route for the drivers to effectively guide them. It has already begun operating in Tokyo as well as in some states in the USA.
Another major issue is inefficient parking zones that don’t meet the residents’ needs. On average a person spends 17 hours in the parking annually. Besides that, research conducted by Mercedes-Benz demonstrated that 40% of car incidents with physical damage happen while parking and maneuvering, which proves the incompetence of the infrastructure plan. In this case, the optimal way to address the problem would be through analytical programs that can identify whether the space is occupied or free, recognize patterns, and detect the license plates. An example of such apps would be AI-Parking and AI-LPR which inspect cameras in parking lots to navigate and tackle the dilemma.
To conclude, the integration of AI in the logistics industry promises positive changes in urban transportation systems including parking and driving issues. Moreover, while cities continuously grapple with challenges the ever-evolving algorithms are erecting a path to a sustainable future and promoting safety. As a result, dispelling myriads of concerns connected to transportation in metropolitans.