According to MDPI, machine learning, deep learning, and generative AI are all used. They all do independent tasks but work together to produce the common product of a self driving car. Machine learning is used to perceive different patterns and adapt to new environments using reinforcement learning (A subset of machine learning). Deep learning is used to copy the human mind. DL is used to display human behavior in driving, especially over time. Generative AI is used to communicate to the vehicle, giving it possible scenarios to help the car and AI learn.

According to the National Library of Medicine there are many benefits that come from autonomous vehicles. This ranges from the safety of people, economic benefits, enviorment benefits and public health benefits especially fighting covid. According to the same paper a major limitation is laws allowing for this change to happen. The development of AV means a whole new sector in the legal side, making it much more challenging, and one lawmakers are not ready for yet.

To me, self driving cars are an un-needed innovation. While it may pose a lot of benefits and good ones concerning COVID, we are now starting to steer away from COVID. In my opinion self driving cars will hurt companies like uber, Lyft, etc. Leaving millions out of jobs and clients who use these companies possibly scared.

According to Wiley, Machine learning and Deep learning are the two main systems used in navigation. Specifically DL divisions like Convolutional Neutral Networks (CNNs), Recurrent Neutral Networks (RNNs), and Graph Neutral Networks (GNNs) are used to analyze huge data sets to allow for better predictions. The AI systems that are able to take real time data like, current traffic speeds, traffic cameras, sensors, satellite weather data and historical traffic/ weather patterns to make their predictions.

According to SpringerOpen the use of DL in navigation is a huge advantage for people all over the world. Since traffic is everywhere, more congested areas lead to lost time and more fuel consumption. With shorter travel times, less fuel is used, making it better for the environment. Also with the use of AI in traffic, cities and highly populated urban areas with a lot of traffic would be subject to better infrastructure plans due to new traffic models, making traffic flow even faster. More standard benefits that AI bring in navigation is faster travel time and more traffic control.

Some challenges that are faced with this technology are false predictions and data breaches. While AI is given a lot of resources to make the correct prediction, they can still be wrong. If something spontaneous happens while AI is making a prediction it can mess with the traffic flow and mess up the data that AI is analyzing. Since we would be giving AI access to a lot of government controlled resources, it becomes a matter of hackers gained access to these systems and manipulating government property. This can also mess with AI predictions and traffic flow. It also brings up an issue of safety for people.

In my opinion this is a great use of AI. This is one of the areas AI should permanently be used. Since humans cannot analyze as much data as AI can to help reduce traffic and there is not much jobs concerning lowering traffic, AI is a great source for this. I use Apple Maps all the time mostly when I am going somewhere new or far, because I want the fastest route there.

According to Cornell University, there are many AI technologies used for safety in the vehicles. Two most abundant and common ones are machine learning for pattern recognition and computer vision to detect inside the car, you face, posture and inside environment and outside the car for other cars, lane tracking and outside environment. Cameras inside the car are able to recognize patterns of drowsiness, fatigue and distraction to assist the driver to pay attention or steer the car away from any danger. Cameras and sensors outside the car allow for AI to see where the lanes are to make sure the driver is staying in those lanes and not putting other cars in danger.

According to the National Library of Medicine, AI systems in cars, specifically commercial divers who are mostly in their vehicles for work for long periods of time significantly reduced the amount of possible accidents. Speeding incidents reduced almost 60%, hard breaking went down by 40-50%, cell phone use decreased, and seatbelt compliance also increased. Due to the AI systems being in place it was able to help the driver know when they were speeding, distracted, tired, etc. Through methods like vibrations on the steering wheel, audio queues or messages the drivers were able to be more attentive. This study also showed that with the AI systems in place drivers fixed their previous bad habits over time, compared to drivers without the AI system.

Some challenges that come with this technology is mostly involve false positives. While the AI systems might be unable to correctly identify an issue with the driver through the camera because of poor visibility or obstructions on the driver like sunglasses, the AI system might give prompts to stay attentive when the driver actually is. The AI can also get confused in lane situations like pulling the driver towards their lane, when the driving is actually merging into a single lane road.

Personally, this technology scares me. I like the idea of prompts when the system feels the driver is distracted or fatigued but only giving those prompts from outside sensors. My family members car which is a Kia Sportage will actually ask you if you are sleepy and recommend you have some caffeine if it feels you are tired. Cameras on the inside of the car feel like an invasion of privacy. The higher risk of data breaches make me feel like these systems data can be easily obtained. Dash cams are different because they are an external source, not connected to the car itself making it more cyber safe. I would like to see the technology be an option in cars not an automatic given.

In the field of delivery of goods and freight, AI will dominate. In this field AI will almost essentially take out the need for humans in driving. While humans will be needed to deliver the goods (except for when robots are fully developed), AI will fully drive commercial vehicles to reduce the amount of human error and accidents

In the field of safety AI is dominating, but only getting started. Companies are putting out vehicles that are fully equipped with safety technologies like, lane assist, emergency braking, and accident prevention. This technology is only to expand like in my detailed description.

In the field of traffic AI is also expanding. Los Angeles for example is filled with traffic and is now implementing AI systems to help reduce this congestion. AI systems are able to analyze current and previous traffic/ weather patterns to make new predictions for users to get to their destinations in quicker and safer manner while reducing CO2 usage.

AI is also starting to be used in the field of maintenance of vehicles. AI systems equipped in vehicles without using outside tools will be able to tell you certain issues with your car, so you are able to get the issue fixed before it becomes a major problem.

These are just some examples of how AI will be used in the future of transportation. AI will soon be used everywhere and be our own personal assistant everywhere. Most of these technologies are for the benefit for humans, but it also raises the ethical questions of should these be allowed or are they a liability? There is ethical considerations everywhere with AI. Some of the benefits outweigh the negatives but some are still concerning. With AI being unpredictable and little to no regulation right now, when do we know when it's telling the truth or if these systems will always work. While they are still new it is hard to tell if we should give these systems all of this trust and burdens.

I find AI in transportation a good thing in a few situations, for example traffic control and safety. I do not like the idea of autonomous cars or anything autonomous because these systems are still never like the human brain. In my opinion, we are giving AI too much responsibility at the moment and it needs to be more securely checked.

Employment:

AI is taking over more lower skill jobs but creating more highly skilled jobs. Jobs like truck driving, delivery driving, taxis, and warehouse jobs are being pushed out because of AI being able to fulfill the task for cheaper cost and loss of human error. Though these jobs are being pushed away, more are being created in the view of maintaining and watching over this AI. This jobs will generally require more skill and education. This involves more collaboration between AI and humans.

Privacy:

AI has a huge impact on personal data. In order for AI to help with traffic control and safety monitoring, it needs to collect massive amount of data. This data ranges from your personal data stored in your phone, images of you through safety systems, traffic cameras, GPS tracking, and your personal habits. If mishandled this data can be stolen, sold or used to attack somebody. This can also be used to advertise certain products to people, leading to accusation of devices listening. So while privacy is a huge issue, there are still not many laws concerning the regulation of this and can lead to further misuse.

Equity:

AI also has a big impact on equity. This also has its positives and negatives. Some positives could be the accessibility of AI powered transportation apps. These apps are asscessible to anyone and the drivers can go anywhere. Also with AI monitoring traffic, it can help reduce the amount of injuries in highly populated areas like cities, which are more prone to accidents. AI can also optimize public transportation, by lowering operation costs which would lower the fares, and help the poorer communities. Some negatives are, AI in the workforce taking away low skill jobs like trucking. AI based transportation apps could also develop a bias to richer neighborhoods to maximize profits. Lastly, there would be an inequity with technology. Since everything involving AI and transportation in this case invoices technology, people who do not have access to smartphone or anything similar would not be able to access the AI powered systems.

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Afandizadeh, Shahriar, Abdolahi, Saeid, Mirzahossein, Hamid, Deep Learning Algorithms for Traffic Forecasting: A Comprehensive Review and Comparison with Classical Ones, Journal of Advanced Transportation, 2024, 9981657, 30 pages, 2024. https://doi.org/10.1155/2024/9981657 [Rationale: This article provides the necessary AI technologies needed for navigation and how AI makes these predictions.]

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Bell, J. L., Taylor, M. A., Chen, G. X., Kirk, R. D., & Leatherman, E. R. (2017). Evaluation of an in-vehicle monitoring system (IVMS) to reduce risky driving behaviors in commercial drivers: Comparison of in-cab warning lights and supervisory coaching with videos of driving behavior. Journal of safety research, 60, 125–136. https://doi.org/10.1016/j.jsr.2016.12.00 [Rationale: This article gives an outstanding study of safety systems in vehicles over time and how they benefit drivers.]

Tagobitsky, O. (2025, February 18). 10 ai trends transforming transportation in 2025: The future of smart mobility. api4ai. https://api4.ai/blog/10-ai-trends-transforming-the-transportation-industry-in-2025 [Rationale: This article provides a list of the future of AI in transportation and possible implications which is needed to understand the future in this sector.]