{"id":120814,"date":"2023-10-30T16:05:23","date_gmt":"2023-10-30T16:05:23","guid":{"rendered":"https:\/\/www.techopedia.com"},"modified":"2023-10-30T16:05:23","modified_gmt":"2023-10-30T16:05:23","slug":"google-green-light","status":"publish","type":"post","link":"https:\/\/www.techopedia.com\/google-green-light","title":{"rendered":"Google’s Green Light: How 30M Drivers a Month Use AI Without Knowing It"},"content":{"rendered":"
Despite the woes, alarms, and fears trailing the increasing adoption of <\/span>artificial intelligence<\/span><\/a> (AI) in about every industry, there is no iota of doubt that AI is here to stay.<\/span><\/p>\n In fact, a McKinsey 2023 <\/span>State of AI report<\/span> shows that 55% of organizations have adopted AI for several usecases<\/a>, and many more are poised to follow suit.\u00a0<\/span><\/p>\n While most discourse around AI these days centers on <\/span>generative AI<\/span><\/a>, Google, through its <\/span>Green Light<\/span><\/a> project, is drawing our attention to another use case that holds the potential to revolutionize traffic management in urban cities, which, by extension, can lead to a greener future.\u00a0<\/span><\/p>\n We can argue that the need for this project partly stems from the increasing number of commuters that have hit the roads since the Covid-19 pandemic was tamed.<\/span><\/p>\n With companies ordering their workforce back to the office, more people on the road, more urban traffic congestion, and a higher dose of greenhouse gas emissions being fed to the cloud.\u00a0<\/span><\/p>\n Google\u2019s Green Light project is an urban traffic optimization initiative that employs AI and data from Google Maps driving trends to model traffic patterns to provide intelligent recommendations to city traffic engineers.<\/span><\/p>\n The project aims to cut down vehicle emissions and enhance urban mobility by optimizing traffic light timing configurations, minimizing unnecessary stops, and subsequently lowering greenhouse gas emissions.\u00a0\u00a0<\/span><\/p>\n Explaining why Green Light is a great project, Fabio Botacci, Founder & CEO at <\/span>VINCI Digital<\/span><\/a>, an IIoT and GenAI Strategic Advisory firm, told Techopedia: \u201cThe project is unique because it\u2019s based on Google Maps traffic data, which means (potentially) petabyte of near-real-time data available to be sent to the cloud and analyzed at scale by AI\/ML advanced algorithms, enabling and enhancing traffic lights actual synchronicity, and resulting in less waiting time\/pollution and therefore increased urban sustainability.\u201d<\/span><\/p><\/blockquote>\n Statistics show that road transportation contributes significantly to global and urban greenhouse gas emissions. According to the United States Environmental Protection Agency, Greenhouse gas <\/span>(GHGs) generated by the transportation<\/span><\/a> sector constitute approximately 29% of the overall greenhouse gas emissions in the United States.<\/span><\/p>\n This makes transportation the primary source of GHG emissions in the country. The International Energy Agency, in a recent <\/span>report<\/span><\/a>, revealed that in 2022, the total global CO2 emissions from the transport sector increased by over 250 million metric tons of CO2, reaching almost 8 billion metric tons of CO2 in total. This marked a 3% rise compared to the emissions observed in 2021.\u00a0<\/span><\/p>\n The numbers above are scary given the urgency of global warming, which pushed world leaders to form the <\/span>Paris Agreement<\/span><\/a>, a blueprint for reducing emissions by 45% by 2030 and achieving net zero by 2025.\u00a0<\/span><\/p>\n According to Google, Green Light focuses on reducing emissions by optimizing how traffic lights work at intersections. Yosil Matias, Google\u2019s VP of Engineering and Research, <\/span>wrote<\/span><\/a>:<\/p>\n \u201cAbout half of the emissions at intersections comes from traffic stopping and starting, and we found that by leveraging AI, we can reduce these emissions by optimizing traffic lights.\u201d<\/span><\/p><\/blockquote>\n One of the strengths of AI lies in its ability to help machines learn, adapt, and make decisions based on data for improved performance over time without extensive programming.<\/span><\/p>\n For the Green Light Project, AI is used to analyze extensive driving data from Google Maps to create AI models that capture details of traffic patterns at specific intersections. Included in these models are information regarding intersection structures, traffic flow dynamics, light scheduling, and the interactions between traffic and signals.<\/span><\/p>\n This detailed data forms the basis for traffic light optimization, as the AI identifies opportunities to synchronize lights for more efficient traffic flow. With this data, it becomes possible to recommend adjustments in light timing and coordinate multiple intersections simultaneously, thereby reducing the dependency on manual counts delivered through sensors.\u00a0<\/span><\/p>\n Green Light\u2019s AI recommendations are designed to work with existing traffic infrastructure for easy implementation and integration with the city\u2019s pre-existing systems.\u00a0<\/span><\/p>\n According to Google, the impact is quick and measurable, as city officials and engineers have reported potential reductions of up to 30% in stops and 10% in emissions at intersections where Green Light is operational. The initiative is already making a difference in many cities, including Abu Dhabi, Bali, Bangalore, Budapest, Haifa, Hamburg, Hyderabad, Jakarta, Kolkata, Manchester, Rio de Janeiro, and Seattle.\u00a0<\/span><\/p>\n Google further claims that Green Light is used to save fuel and lower emissions for up to 30 million car rides every month.<\/span><\/p>\n Considering that every mention of AI exudes some breath of Orwellian-like suspicion, we spoke to some cybersecurity and AI experts to know if there are potential cybersecurity concerns in using Green Light.\u00a0<\/span><\/p>\n In a statement made available to Techopedia, Gary Huestis, owner and director of <\/span>Powerhouse Forensics<\/span><\/a>, argues that while the current scope of Green Light doesn\u2019t lend itself to many security vulnerabilities, his primary concern centers on cities demanding access to the traffic data generated by Google.<\/span><\/p>\n \u201cMy biggest concern is that the goal of Google\u2019s Green Light Project is to provide suggestions to cities on traffic signal timing, which could create the desire for the cities to have access to the data. This, in turn, could lead to the cities using that data against the drivers and eventually un-anonymizing the data and using it to generate traffic citations. The best way to address this is to keep the data anonymous and keep access to the raw data out of the cities and governments.”<\/span><\/p><\/blockquote>\nKey Takeaways<\/span><\/h2>\n
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What is the Green Light Project and Why Does it Matter?<\/span><\/h2>\n
\n<\/span><\/p>\nHow AI Powers Google\u2019s Green Light Project<\/span><\/h2>\n
The Real-World Impact of Green Light<\/span><\/h2>\n
Grey Areas Amidst the Gains<\/span><\/h2>\n