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The Role of AI in Transportation

AI and transportation

Artificial Intelligence (AI) is poised to play a significant role in transportation, whether it’s being used to provide driver assistance in cars or to organize logistics for shipping.  AI can collect data on the surrounding environment using LiDAR technology and cameras, a process that uses information through machine learning algorithms, then use it to make decisions faster than humans are capable of.

More time is spent commuting now than ever before, especially as cities grow bigger and more congested with residents taking up limited space on busy roads. This leads to frustration over traffic jams which leads to road rage—the cause of more deaths per year than any other thing.  Even the smallest accidents cause massive jams and fuel anger, enough so that some cities have used principles of crowd psychology to reduce road rage.  Some of this is built around creating a strong sense of community in the city through fostering trust between strangers on the roads.

AI can be used to achieve similar aims by using driverless cars to break up traffic jams and ease congestion.  Driverless cars would not fall prey to road rage, nor would small accidents or slight oversights escalate into dangerous situations as human drivers do.

Companies like Tesla Motors, General Motors, and Google have been testing driverless cars for a while now.  Google has developed an autonomous car that can travel from one destination to another without human interaction through a combination of cameras, sensors, and a machine learning system that includes driving information collected throughout the company’s fleet of self-driving cars.  

These self-driving cars need AI to guide them in order to navigate public roads safely.  The biggest obstacle is the paucity of data on big city streets compared to rural areas. Self-driving cars must be taught how to drive around these obstacles in much the same way humans learn when they get their licenses—by playing simulated video games or by road-testing them in controlled conditions before taking them out into the real world.  Another potential issue with a self-driving car is a bug in the programming that causes the AI to behave erratically.

Unlike other tasks where human judgment can be outsourced or automated, driverless cars run with artificial intelligence need to make ethical decisions on what course of action should be taken if there are going to avoid accidents; how much care they take when driving around pedestrians, for example, will depend on what kind of algorithms they use.  If self-driving vehicles become widespread, questions like these about their programmed behavior will likely arise quite often.

Artificial Intelligence in the Transportation sector is becoming more common as companies invest in developing new technology.  AI has the potential to save lives if it reduces road rage and makes driving safer.  However, due to the need for self-driving cars to make ethical decisions, the AI systems used in them will need to be carefully monitored.

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