Controlling Urban Traffic Via Artificial Intelligence Mechanism


The traffic camera footage that films the activities of cars, pedestrians, and other entities at an intersection would see a revolutionary advancement, according to researchers at the University of Texas. The researchers enunciated that they are employing artificial intelligence and data mining techniques to see the interaction of various entities that interplay on roads. It would now be possible for them to gauge the extent of accidents in a specific area, the volume of traffic defaults, and density of traffic across different regions. The traffic engineers would be able to analyze the interactions and interceptions of bikes, cars, pedestrians, trucks, and all other dynamic objects on the road.

Magnifying Traffic Systems

The algorithm uses the knowledge of various objects from its past storage and combines it with the current outlay of the traffic to reap the interaction patterns of various objects. When the algorithm was put to test, it was found that the results exhibited 95% accuracy rate for the tested road. There is a dire need to check the performance of the transportation network, and measure the effectiveness of contemporary transport models in order to ensure safer standards. The new technology would give a comprehensive spatial and temporal analysis of the transportation network, thus, making it easier to understand traffic data sets and manage discrepancies.

Future Growth with Traffic Analysis Techniques

The new algorithm is also a step towards getting more savvy with other forms of traffic analysis, such as identifying designated pathways treaded by pedestrians on busy traffic streets. It would act as a breakthrough towards reducing the manual effort that goes in analyzing videos and spotting traffic defaults. The entire world foresees the introduction of self-driven cars which would require greater computer-based analysis. Hence, the new traffic analysis technology is in synchrony with the needs of the future.

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