Can We Keep Up With Machine-Learning in Transportation?

Machine learning has already begun to make its mark in the transportation industry. Autonomous vehicles are already popping up across the country. Many cars already feature some autonomous capabilities – like parking, steering, and cruise control. By implementing machine-learning algorithms into the transportation industry, it could ultimately save lives and time. Accidents are caused by human error, but take out the human aspect, and it limits error resulting in less accidents. The system could detect and track moving cars and determine normal traffic flow. It could also detect congestion, accidents or pedestrians on the road. Lots of elaborate technologies and extensive testing goes into machine learning for vehicles; the goal is to drive more efficiently by eliminating human error.

One company that has taken machine learning and embraced it is Tesla. They have a system called Enhanced Autopilot that allows the driver to sit in the driver’s seat and do absolutely nothing while the vehicle operates itself. The system has been released in a few different phases and continues to be updated. The car’s cameras and sensors allow it to see through heavy rain, fog, dust, and even a car in front of it. Eventually Enhanced Autopilot will allow the car to match the speed based on traffic conditions, change lanes without the driver’s input, merge on and off highways, and park itself. Tesla’s system also includes active cruise control, forward collision warning, and the ability to park perpendicularly on its own. Tesla’s ultimate goal is to have a car drive itself across the country from LA to New York. This only shows how capable the transportation industry is when it comes to embracing the inevitable machine learning era.

Another aspect of transportation that is being impacted by machine learning is GPS apps. One in particular is gaining traction – Waze. It collects data from other users and creates your route off traffic, accidents, construction, police officers, etc. Waze can suggest a time to leave in order to beat the rush hour traffic and can predict your next destination. Since Waze is owned by Google, the app is able to use past searches to suggest future destinations or stops along your route. There is another GPS app called INRIX Traffic that takes that idea even further. It uses machine learning to get a better understanding of the driver’s habits, interests, and plan each and every route accordingly. Once you create an account, the system begins to learn about locations you visit frequently. Additionally INRIX Traffic, constructs a log of where you visit and when you leave. This app is designed to learn everything about your traveling routines and gives you all the information needed to get you from point A to point B according to the user’s preference.

Though autonomous vehicles and tailored traveling apps may be more convenient and efficient, there are many issues that come with them. Until autonomous vehicles are perfected, there will be plenty of mistakes along the way. For example, one of Tesla’s cars in Autopilot mode was in a fatal car crash and the driver was killed. There were no defects in the system, however, it is not fully capable of avoiding every single possibility of an accident. It can stop the car from rear-ending the car in front of it with no problem, but the accident was a situation that was beyond the performance capabilities of the system. There is still much room for improvement when it comes to self-driving cars. Consequently, the infrastructures of many cities are not equipped to handle autonomous vehicles because the system requires clear and divided lines as well as a less congested road layout. There is also an ethical issue when tailored apps are in question. The app is required to know your location at all times in order to give you an accurate timeline, suggestions and routes. How much of that information is being shared with third parties? Would you like it if a company knew your whereabouts all of the time? These questions are something to consider as we move toward a less private but convenient life style.

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