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AI has applications in almost every field, but one of the most significant is in transportation. The way people get to work and school, how packages are delivered to consumers and so much more. I am also interested in how AI can intersect with these fields. In this padlet wall I will discuss autonomous vehicles, intelligent traffic management, and logistics. My post will detail the AI technologies involved, their benefits and challenges, real-world examples, and broader future and societal implications. Inside the applications I will go into machine learning, computer vision, and predictive analytics. Currently many of our transportation systems are inefficient because they can’t learn from themselves in real time. While it can help humans to make predictions based on past data, it is more suited for an AI who can handle so much more data. In terms of self-driving cars, many trips are extremely repetitive(and boring for people) which would be perfect for AI. I chose this field in part because of my current studies. I am currently doing an internship working on submarines, and am interested in pursuing a career in train/car infrastructure in the United states. If train routes could change in real time to provide the most availability to those who need it, and create optimal alternate pathways for less traveled routes. On the city level, it could be used to improve track switching and predictive maintenance because as it currently stands it is done by hand at the Subway power control center.

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Autonomous Vehicles (Self-Driving Cars & Trucks)

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Autonomous Vehicles (Self-Driving Cars & Trucks)

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https://youtu.be/taMP_n3wL7M?si=aFMC--utl_AYwLIC

Autonomous vehicles like Waymo(a self driving service) rely on machine learning and computer vision for perception and decision-making. They use deep neural networks to detect and classify objects (vehicles, pedestrians, signs) from camera and sensor data. They fuse inputs from cameras, LiDAR, radar, and ultrasonic sensors to build a 360° model of the environment. To recognize this data they use aggregate data of other examples to get as close to 100% recognition. Advanced sensor  and reinforcement learning algorithms enable path planning and control over route planning. Computers with extremely powerful cpus and gpus run these AI models in real time (Autonomous Vehicles: Evolution of Artificial Intelligence and the Current Industry Landscape). The benefits are improved road safety due to improved reaction speed over people, but that is also its biggest challenge(The evolving safety and policy challenges of self-driving cars). They have to perform complex ethical challenges like a human would.

Insights: Self driving automobiles have the possibility to take over driving as we know it, but we have to make sure we are doing it at the right pace. If we do it to fast it could perform fatal errors, unnecessarily wounding people and lowering people's perceptiveness towards it.  We also have to make sure that we have adequate jobs in other sectors for people who will lose their jobs. However if we successfully implement it, it will be a net positive as cars on the road can communicate with each other to prevent accidents.

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Traffic Management (Intelligent Traffic Systems)

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Traffic Management (Intelligent Traffic Systems)

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https://youtu.be/tgYOOPMQmc4?feature=shared

We see traffic lights and signals everywhere, especially in dense places like New York City, but they can often be inefficient and lead to slowdowns. With AI this has a possibility of being greatly reduced. Cities like san francisco and los angeles are using AI from streetlight data that aggregates cell phone usage to create an optimal flow of traffic and predict congestion patterns according to tractiontechnology.com. They can automatically adjust traffic light cameras so instead of a fixed distance it uses optimization algorithms, coordinating with nearby lights. According to smartcitiesdive.com this cut idling time by 40% and traveling times by 25% at equipped stations in pittsburgh. However this creates privacy issues where many drivers don’t want their cars to be constantly recorded and stored for police reasons.

In my opinion this could be an amazing way to clear up congestion in major cities because traffic wastes a large portion of people’s lives. I think more research should be done on how to make the transition smoother between our current system and a more modern one, including having two systems run simultaneously to prevent shutdowns.

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https://www.youtube.com/watch?v=-_wNjLduGiY

In logistics AI can be used for predictive analytics, route optimization, and automation. One major use is predicting when a product will be needed by a consumer so it is already close to them. Amazon does this particularly well netting the one day delivery times. Logistics uses machine learning models to analyze a lot of factors, including historical sales, weather, and market data to predict product demand more accurately than manual methods. They also use it for the trucks, predicting when it needs maintenance or optimizing their routes according to AI In Logistics: The Trends And Benefits Transforming Supply Chains).  UPS’s ORION system uses Ai analytics to map out the most efficient daily routes for tens of thousands of delivery drivers which saved millions of miles according to (Route Smarter, Not Harder: UPS's ORION Success). There are very few problems with this when executed successfully but in unforeseen circumstances like routes being shut down you still need human input.

In my opinion this could be very useful, especially relating to the environment. If shipping routes are cut down upon it could save a large amount of gas, helping reduce pollution. One thing that potentially worries me is it makes buying things online to easy, and can make people lazier.

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Future Trends and Ethical Considerations

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Future Trends and Ethical Considerations

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AI is just getting started when it comes to transportation. By 2030, a notable share of new cars are predicted to handle most driving tasks according to McKinsey (The future of autonomous vehicles (AV) - McKinsey & Company). There is the potential for more robo taxi services like waymo and autonomous truck corridors. AI is also planning to be used in vehicle communication where future vehicles and traffic systems will communicate in real-time across entire smart cities according to syed yusuf (https://www.sciencedirect.com/science/article/pii/S2590198223002270). This could mean a car adjusting its speed because an AI cloud system predicts a traffic light will turn red by the time it arrives.

Studying ethics and safety in humans is hard enough, but AI presents new challenges. One major issue is deciding who is responsible if there is an accident on the road, with regulators are struggling to create liability frameworks to ensure accountability. One of the most important factors in this is transparency. If people know more about how the AI works and what affects their decision making, people can make the choice for themselves. The problem arises when AI is used without peoples consent, like when a AI dash cam recorded a trucker and its location data (AI dashcams enhance trucker safety while raising privacy concerns | Fox News). AI must also consider bias and equity issues. If it is trained on data that is biased toward wealthy people and neighborhoods, it could prioritize traffic flow there at the expense of the poorer one. (AI in Transportation: Ethical Balance between Safety and Privacy).

I think it is extremely important that we look at AI with a careful lens to see if one group is getting unfair treatment. I remember in middle school as a project we had to google general topics and see what types of people were represented. It was usually white, wealthy, heterosexual people and if AI is trained on this data it could prioritize them more.

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Societal Impact (Employment, Privacy, Equity)

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Societal Impact (Employment, Privacy, Equity)

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AI’s role in transportation has and will have an immense effects on jobs. There are about 3.5 million truck drivers and studies estimate that widespread self-driving adoption could potentially displace a large share of those jobs over time (How many jobs will be created by the disruption of transportation? How many jobs will be destroyed?). A 2024 analysis by RethinkX projected “up to 5 million U.S. jobs” could be lost due to autonomous vehicles, including truck, taxi, and delivery drivers. (How many jobs will be created by the disruption of transportation? How many jobs will be destroyed?). Then it will be up to policy makers and companies to make up those jobs in other areas. It could potentially be a benefit for some people, creating high paying jobs in data analyzing, robot maintenance and drone operators. The nature of transportation jobs may shift from manual operation to overseeing automated fleets.

AI taxis or AI-enhanced mobility services could change people’s lives but it could just prop up an already unfair gap between the rich and the poor if companies only target wealthy cities. Planners are already working to create affordable transportation options for with AI, such as subsidized autonomous shuttles in underserved areas (Equity, Artificial Intelligence, and Transportation). We also must make sure that bias in algorithms is removed. If an AI for traffic management is trained on data that reflects a police bias towards a specific race or class, it could further exacerbate the inequality we have in the US.

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My research process consisted of starting out with searching up general topics relating to AI in transportation, and then finding three key areas that I thought were the most interesting. From there I looked through news articles and scholarly papers to find the best ones for my posts. I definitely learned a lot about AI in traffic systems, I had no idea the extent to which they were already being used to improve traffic in cities. Some problems I faced were that many articles weren’t from recognizable sources so I had to do my due diligence to make sure they were trustworthy. AI has already impacted transportation greatly through intelligent traffic systems, driverless taxis and logistics planning, and it is primed to change our society as we know it.

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Brookings Institution. (2024). The evolving safety and policy challenges of self-driving cars (The evolving safety and policy challenges of self-driving cars). Rationale: Am expert explaining the benefits and challenges of AI for safety.

Garikapati, D., & Shetiya, S. S. (2024). Autonomous Vehicles: Evolution of Artificial Intelligence and the Current Industry Landscape. Big Data and Cognitive Computing, 8(4), 42 (Autonomous Vehicles: Evolution of Artificial Intelligence and the Current Industry Landscape) . Rationale: This is a peer reviewed study that goes deep into the actual technologies which is useful for getting a better understanding.

Snow, J. (2017, July 20). This AI traffic system in Pittsburgh has reduced travel time by 25%. Smart Cities Dive (This AI traffic system in Pittsburgh has reduced travel time by 25% | Smart Cities Dive). Rationale: This industry news piece reports a real world example of AI being helpful in reducing traffic time

Traction Technology. (2023). How AI is Revolutionizing Traffic Management (Top AI Startups Revolutionizing Traffic Management | Traction Five | Traction Technology) . Rationale: This article outlines more specific AI traffic technologies being used in cities like san francisco.

Panorama Consulting. (2024, Sep 25). AI in Logistics: The Trends That are Transforming Supply Chains (AI In Logistics: The Trends And Benefits Transforming Supply Chains) (AI In Logistics: The Trends And Benefits Transforming Supply Chains). Rationale: This blog shows AI trends in logistics and the benefits over non AI usage.

Burnham, K. (2024, Aug 20). How artificial intelligence is transforming logistics. MIT Sloan Management Review (How artificial intelligence is transforming logistics | MIT Sloan) (How artificial intelligence is transforming logistics | MIT Sloan). Rationale: This Mit article references specific examples of unnecessary driving being cut down upon.

Knutsson, K. (2025, Mar 15). AI dashcams enhance trucker safety while raising privacy concerns. Fox News (CyberGuy Report) (AI dashcams enhance trucker safety while raising privacy concerns | Fox News). Rationale: This news article provides a specific example of AI encroaching on people’s privacy

RethinkX. (2024). FAQ: How many jobs will be lost due to self-driving vehicles? (How many jobs will be created by the disruption of transportation? How many jobs will be destroyed?). Rationale: This  FAQ provides insight into how driving jobs will be affected by AI.

Tech-Stack (n.d.). AI in Transportation: Ethical Balance between Safety and Privacy (AI in Transportation: Ethical Balance between Safety and Privacy). Rationale: This source brings up important ideas relating to bias, equity and fair design in AI transportation.

UPS. (2024, March 14). UPS strengthens network capabilities and employee experience through innovation. [Press release]. UPS. https://about.ups.com/us/en/newsroom/press-releases/innovation-driven/ups-strengthens-network-capabilities-and-employee-experience--th.html

TED. (2023, June 5). How AI will revolutionize the way we live and work | Kai-Fu Lee [Video]. YouTube. https://www.youtube.com/watch?v=-_wNjLduGiY

Matellio. (2023, October 11). AI traffic management: Revolutionizing smart transportation with artificial intelligence. Matellio. https://www.matellio.com/blog/ai-traffic-management/

Freethink. (2023, December 15). How AI is changing transportation [Video]. YouTube. https://youtu.be/tgYOOPMQmc4?feature=shared

AI Business. (2024, February 8). Waymo launches AI model for autonomous driving. AI Business. https://aibusiness.com/nlp/waymo-launches-ai-model-for-autonomous-driving

Veritasium. (2023, November 22). The future of self-driving cars [Video]. YouTube. https://youtu.be/taMP_n3wL7M?si=aFMC--utl_AYwLIC

iRideTheHarlemLine. (2021, February 18). Behind the scenes at the subway’s power control center. iRideTheHarlemLine.https://www.iridetheharlemline.com/2021/02/18/behind-the-scenes-at-the-subways-power-control-center/

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Padlet's video time limit is 2 minutes so I did it on the computer and uploaded it. Also had to compress it a lot to fit the 20mb limit so I apologize for the low quality.