Engineering Proposal Possible Sources

Group 4: Adam Asad, Ayaan Rahman, Michael You, Matthew Leon

 

Proposal: Many cities, like New York City, face problems with traffic congestion leading to wasted time and emissions. We can use smart traffic lights with real time cameras to optimize the flow of traffic and reduce delays. Unlike old fixed time signals this system can adapt to actual traffic conditions. For Manhattan, utilizing such technology would reduce the likelihood of bottlenecks, jams, and backed up traffic flow. AI traffic lights would be a further step in the mobility of traffic in Midtown and other densely populated regions.

 

“AA: 

The source below describes how Ai-driven adaptive traffic light systems utilize real time data and machine learning to dynamically adjust signal timings to better manage traffic demand and enhance the efficiency of urban transportation. 

https://www.researchgate.net/publication/390233439_AI-Powered_Adaptive_Traffic_Light_Control_Systems_for_Congestion_Reduction

 

The source below provides information about how one of the largest cities with traffic jams, Boston, collaborated with Google to implement “ Project Green Light”. This project utilizes Ai to optimize traffic signal timing and overall led to a 50% reduction in stop-and-go traffic at intersections, enhancing traffic flow and reducing emissions. 

https://www.boston.gov/news/city-boston-partners-google-traffic-signal-optimization

 

AR: https://www.nyc.gov/site/nypd/stats/traffic-data/traffic-data-trafficstat.page

https://jknylaw.com/blog/worst-traffic-times-in-new-york-city/

Links contain statistics related to traffic conditions, fatalities, rush hours, how to avoid traffic etc. within NYC

 

https://parquery.com/control-traffic-signals-with-cameras-not-induction-loops/

”

ML:  

1. https://www.sciencedirect.com/science/article/pii/S2352146525000687 
   1. Article discusses the implementation of AI to help improve traffic in Macedonia. One method used was Q-Learning. Reduced traffic times, emission, etc. Another tool listed as GoodVision, which was used more to monitor and collect data. Used in traffic simulations, realistic traffic flow, etc
2. https://www.swarco.com/stories/ai-based-traffic-management
   1. (Non-Research Paper). The article revolves around the AI based management system implemented in Denmark. The technology SWARCO uses real time GPS data, cameras, and consciously adjusts its green light times to reduce congestion in busy or rural areas. Adapts to road work, traffic flow, time of day, etc. Small use in only 10-20 locations. Around 20,000 – 40,000 Euro to implement.

“MY:

 https://www.mdpi.com/2571-5577/7/1/3?utm_source

This is research that talks about how implementing smart traffic lights could help reduce carbon emissions waiting times. 

 

https://www.smartcitiesdive.com/news/this-ai-traffic-system-in-pittsburgh-has-reduced-travel-time-by-25/447494/?utm_

Approximately $20,000 per intersection. This system utilizes AI to adapt traffic signals based on real-time conditions, leading to significant reductions in travel and idling times.”