Computer Science, asked by Praju11111, 13 hours ago

Given the challenges that exist in our country. using possible sensor data from future cars, derive solutions that can help reduce the carbon footprint that can include things like carbon tax, car pooling detection and matching, traffic re-routing among many other things.

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Answered by CloutedMello
0

Answer:

Introduction and summary

When one thinks of autonomous vehicles, or AVs, it is difficult not to imagine the world of tomorrow. It is easy to visualize safely cruising down the highway while reading for pleasure or writing a work email—rather than watching the road. Vehicle automation promises to transform how people get to work, run errands, and generally travel through the nation’s streets and highway systems. Children could commute to school alone, without relying on a parent. One can also imagine a sight-impaired person traveling alone to a doctor’s appointment. In cities, someone could hail an autonomous vehicle with a ride-sharing app and ride with other passengers going a similar direction. The idea of driverless robot cars has captured the public’s imagination as automakers and technology companies promote the potential leisure, safety, and environmental benefits of AVs.

 

Today, automakers are already adding features to new vehicle models that assist drivers, such as parking assistance, lane centering, and automatic braking. As these features become standard in cars, automakers have set their sights on creating autonomous vehicles that do not need drivers at all. Silicon Valley and ride- and car-sharing companies are investing in technology and betting on the transportation sector’s shift toward autonomous vehicles.

In the midst of these advances in vehicle technology, the international community is working to address one of the greatest challenges of our time: climate change. The United States has committed to reducing its greenhouse gas emissions 26 percent to 28 percent below 2005 levels by 2025 and to achieving greater emissions reductions in the future.1 To meet that goal, the United States will need to cut emissions from the transportation sector, which accounted for 26 percent of the country’s greenhouse gas emissions in 2014. Of these transportation sector emissions, 61 percent came from light-duty vehicles, such as passenger cars.2

Autonomous vehicles—particularly those that are passenger cars—could significantly affect the country’s ability to cut greenhouse gas emissions and move toward a carbon-free economy. Existing studies suggest that three main factors will determine whether putting more AVs on the road increases or decreases tailpipe carbon emissions: effect on the total vehicle-miles traveled in the United States; impacts on congestion; and AVs’ fuel efficiency and fossil fuel consumption. As such, autonomous vehicles must be assessed not only for their safety but also for their effect on carbon emissions levels.

To that end, the Center for American Progress reviewed the existing literature on the environmental impacts of automation in the light-duty vehicle sector. We found that existing research does not draw clear and consistent conclusions about the impact of autonomous vehicles on the environment generally and climate specifically. In particular, the research reviewed shows that:

Vehicle miles traveled, or VMT—the aggregate number of miles driven by vehicles in a given year—could increase because automation lowers the opportunity cost of driving. This could encourage people to take more car trips or accept longer commutes, since drivers would be able to multitask in vehicles rather than focusing on the road. Additionally, autonomous vehicle technology could allow groups of people currently unable to drive—such as the elderly, young, and people with disabilities—to travel alone in autonomous vehicles, putting more people on the road.

VMT could decrease if autonomous vehicle technology is paired with ride- and car-sharing services. A system of shared autonomous vehicles could discourage individual car ownership and use technology to plan efficient routes to transport people from point to point. At the same time, however, shared autonomous vehicles could increase overall VMT if they make frequent passengerless trips to pick up their next client. Specialized software programs could mitigate this effect by planning the most efficient routes.

Automation could reduce congestion and make each mile traveled more efficient. Autonomous vehicles that communicate with each other and their surroundings may drive more smoothly, without needing to frequently brake and accelerate. Fully autonomous and connected vehicles could reduce the number of traffic accidents and, therefore, unnecessary idling on roads.

Drivers may not realize the congestion benefits of automation for years, until a large share of vehicles on the road are equipped with autonomous technology. In the shorter term, VMT and congestion could worsen as autonomous vehicles join the fleet without displacing traditional vehicles.

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