Self-Driving Vehicles: Bottlenecks to Success
Tags: ai, iot, discuss, security
Published: 2022-07-22 14:20:20


The topic of self-driving vehicles (SDVs) has been in the [news](https://www.bbc.co.uk/news/technology-56906145) a lot lately. Some say that SDVs will bring about the end of personal car ownership and usher in a new era of transportation. Others say that we have decades before this happens, if ever. While both sides have valid arguments, several bottlenecks must be overcome before SDVs can become mainstream.

##Legal Bottlenecks
Self-driving vehicles will require new legislation to regulate how they interact with other vehicles, infrastructure, and pedestrians.

To prevent crashes, self-driving cars must be able to [communicate](https://eu.usatoday.com/story/money/cars/2016/12/13/self-driving-cars-vehicle-to-vehicle-technology-v-to-v-nhtsa-autonomous-cars-v2v/95367310/) with one another. They also need to communicate with the cloud for their software programs and maps to be updated as needed. Additionally, self-driving cars must consider the rules of the road when communicating with pedestrians or other cars on the road; this includes stopping at stop signs and traffic lights, yielding right of way when appropriate, slowing down when approaching a school bus (or any vehicle transporting children) or making sure no one is standing behind the vehicle before reversing.

##AI and Machine Learning
AI and machine learning are the main [technologies](https://mindy-support.com/news-post/how-machine-learning-in-automotive-makes-self-driving-cars-a-reality/#:~:text=shape%20and%20depth.-,LiDAR,development%20of%20self%2Ddriving%20vehicles.) behind self-driving vehicles. As you probably know, AI refers to computers that can perform tasks normally requiring human intelligence, such as visual perception, speech recognition and decision-making. Machine learning is a subclass of Artificial Intelligence in which systems learn from data without being explicitly programmed.

For example, consider the problem of detecting pedestrians in images taken by a camera on a car’s windshield. This task is considered relatively easy for humans but difficult for computers because it requires understanding objects (people) in context (moving around or standing still). Researchers have developed algorithms that can accurately identify pedestrians using only two-dimensional images. However, they require large amounts of training data to do so—for instance, millions of images showing pedestrians in various positions and light conditions against different backgrounds before they can reliably recognise them. Such quantities are prohibitively expensive for deployment at scale on consumer vehicles today.

##Ethical Considerations
[Ethics](https://towardsdatascience.com/the-ethics-of-self-driving-cars-efaaaaf9e320) must be at the core of how self-driving cars are programmed. As the number of self-driving vehicles increases, ethical decisions become more complex. There are many more potential scenarios where the car must choose based on its programming. For example, imagine you’re driving down the highway when a child darts into traffic. Your vehicle could swerve into oncoming traffic, but if it did that it could mean crashing into oncoming cars or hitting other pedestrians. How would you want these decisions made?

This is just one example of an ethical dilemma that self-driving vehicles will face as they navigate our highways and city streets. To complicate matters further, some people might prefer different outcomes than others depending on their experiences or values; these differences can lead us down a path toward personal bias where we choose what kind of world, we want by selecting which cars we buy based solely on how well they perform certain tasks (such as avoiding accidents).

##Cost and Funding Bottlenecks
Self-driving vehicles have the potential to be the future of transportation. But, when you think about it, many things need to happen before this dream becomes a reality.

- Cost is one of these [bottlenecks](https://www.futurebridge.com/uncategorized/autonomy-delay-current-challenges-and-bottlenecks/). For example, self-driving cars are very expensive because they have a lot of high-tech components such as cameras, sensors and computers that make it possible for them to drive themselves without any input from a human driver (although humans can override this at any time). They will become more affordable with mass production, but most people cannot afford them now.
- Another cost factor is self-driving car infrastructure: whether through road construction or retrofitting existing roads with new technology like sensors to detect other vehicles or pedestrians nearby so they can react in case something goes wrong.
- Training costs associated with [teaching](https://www.iotworldtoday.com/2022/04/19/new-gm-tech-could-have-autonomous-cars-teaching-people-how-to-drive/) people how to operate autonomous vehicles safely without error could also present some challenges because if something goes wrong during operation, then those responsible could potentially face legal repercussions due to negligence on their part, which could lead up costing millions in damages paid out by insurance companies too!

##Negative press of crashes of self-driving vehicles
Self-driving vehicles are poised to revolutionise the way we get around. They promise to make roads safer, reduce traffic congestion, and reduce [greenhouse gas emissions](https://www.blickfeld.com/blog/self-driving-cars-environment/). But before these benefits can be realised, some significant roadblocks need to be overcome – and the first is getting people to trust them.

According to an American [survey](https://www.reuters.com/article/us-autos-selfdriving-poll-idUSKCN1RD2QS), half of US citizens lack confidence in the safety of self-driving vehicles. Another [study](https://www.pewresearch.org/internet/2017/10/04/americans-attitudes-toward-driverless-vehicles/) showed that 56 percent  wouldn’t ride in one if given the opportunity. And a recent crash involving an [Uber self-driving vehicle](https://www.bbc.co.uk/news/technology-54175359) has only added fuel to the fire in terms of negative press surrounding these vehicles’ safety records.

For autonomous vehicles to succeed and become widely adopted, we need to address these fears head-on, and start by addressing their safety concerns.

##Self-driving vehicles face many challenges before they can reach the mainstream

Despite the hype, self-driving vehicles have been slow to reach the mainstream. The technology is in its infancy and must overcome several obstacles before success:

- Legal, ethical, and cost issues: The current legal framework surrounding self-driving vehicles is complex and ambiguous. It’s difficult to know what liability will apply in the event of an accident with a human driver at the wheel or whether they are liable if they are injured or killed by a malfunctioning vehicle.
- Artificial Intelligence (AI) and machine learning limitations: AI has made great strides recently, but it still has many limitations when applied to driving conditions. For example, snow can obscure lane markings on roads, making it difficult for cars to interpret accurately enough for safe driving – something humans do effortlessly thanks to our “common sense” understanding of how things work in everyday situations like this one. This limitation could be solved with better sensors but would significantly increase costs, so we need a better way forward before proceeding further down this route.

Many people think that self-driving cars have the potential to transform transportation, even though they are still in the early phases of research. However, they still have to overcome several obstacles before achieving this degree of popularity. These challenges include legal issues, AI and machine learning limitations, ethical considerations around safety concerns and more funding needed for future research and development programs. As experts at caruno assert, “We need more research and answers on the safety and reliability of [self-driving](https://www.caruno.co.uk/) technology, until then we can continue to enjoy cruise control”.