Autonomous Vehicles

Autonomous vehicles (AVs) that can drive themselves from point A to point B without human intervention are one of the most disruptive technologies of the twenty-first century, although the concept isn't new. People recognized that driving is a laborious and risky activity as automobiles spread and supplanted horses in city traffic.

General Motors sponsored a Futurama World's Fair exhibit in 1939, which purported to show a glimpse into the year 1959. Although we would find the show mundane in modern times—it focused on the importance of an interstate highway system and single-direction roads for high-speed travel—it did show a vision of a future with an automated highway system, ostensibly to address issues such as city pollution and the rising death toll from automobile accidents. 

Autonomous vehicles are now considered a futuristic technology, yet they were formerly supposed to be only twenty years away. We're sixty years behind schedule.
Let’s dig into what makes the landscape of Autonomous Vehicles and what we can do with it.
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Focusing solely on autonomous human transportation vehicles loses out on much of the current revolution. Pit mining equipment is becoming increasingly automated. The automotive and petroleum industries, as well as related supply chains, are being disrupted by electric vehicles. Ride-sharing is altering car ownership culture, as well as regulations and city development. This shift will be accelerated by the use of autonomous vehicles (AVs). Drones that transfer packages autonomously on the ground and in the air are boosting last-mile delivery (i.e. FedEx and Amazon). Physically handicapped people will be able to move around freely. Vehicles that are self-driving will save lives. AV opens up more opportunities than might appear at first glance. 

Automobiles are responsible for the deaths of an estimated 13 million people each year, with a twenty-fold increase in injuries. This amount outnumbers deaths from wars, narcotics, and violent crime combined in the modern era. Accidents involving automobiles are the leading cause of death among teenagers and young adults. In fact, in the time it took you to read this article, five individuals were injured or died in a car accident. We'd conduct unending vigils and politicians would run on platforms asking for their eradication if any disease or military strike caused such huge death tolls.

However, there may be a solution. Allowing distractible, simian-brained individuals to run cars is an issue that can be solved. People have a long history of being removed from unsafe or hazardous tasks and replaced by machines. The arrival of self-driving cars is yet another example of human creativity.

In a lifetime, the average driver may travel over 800,000 miles and be involved in an accident once every 200,000 miles. An intelligent digital driver with the combined experience of a fleet of cars could log billions of miles in the real world, trillions in simulations, and take part in more unusual scenarios than any other person in history. Every year, the computers that control autonomous vehicles get smarter, and unlike a fifteen- or sixteen-year-old with a learner's permit, they don't have to start over with each new driver. Every new accident or event makes the system smarter as a whole. The system continuously trains an Al model and distributes updates to the entire fleet on a regular basis. Transportation has become commoditized as a result of self-driving cars.

AVs should exist for this reason alone, regardless of any other advantages. Autonomous vehicles, like any other general-purpose technology, have the potential to add more.

Personal transportation is the most basic use case for autonomous vehicles. When we first hear about autonomous vehicles (AVs) that drive, steer, and navigate on their own, our thoughts usually go to self-driving cars (SDC). Many of the advantages of using AV technology to develop SDCs are already being realized. SDCs will make these services more profitable or less expensive. As a result, ride-hailing companies like Uber and Lyft are struggling to make a profit in the early 2020s and are still burning through capital. In the long run, these business models will increasingly rely on SDCs to compete with the low cost of self-driving cars or current alternatives such as public transportation or taxis. When autonomous vehicles and ride-sharing are coupled, the cost of personal transportation can be reduced from $1.50 to 254 per mile. Such savings will dramatically lower the incentives to purchase a car in favor of fractional payments based on per-use factors like the number of trips, distance, or timelines.

The capacity to commute from anyplace to anywhere instantly will shift where people choose to reside, potentially resulting in a renewed suburban flight. It's possible that the skyline will shift as well. Landscape advertising, such as billboards, begins to lose value as there are fewer eyes on the road.

According to Budapest University of Technology and Economics' calculations, complete adoption of AVs will result in a 20% increase in traffic flow and an even bigger increase in traffic density. SDCs can react faster than humans, resulting in shorter reaction times. In addition, they can plot and adjust course in real time.

As SDCs become the primary mode of personal transportation, most of the traffic management infrastructure may be phased out. Autonomous vehicles (AVs) are effective drivers. When you combine that efficiency with low-power wireless transmitters that allow vehicles to communicate at the speed of light with other AVs, we'll find that AVs will be able to negotiate their intentions to turn or drive through an intersection. Traffic signs and lights will become obsolete once the speed limit is defined in a shared digital map that all AVs can access. When cars are programmed to never exceed a legal limit, why bother with speed cameras or traffic cops? Cities will save millions of dollars each year by eliminating the need to maintain all of this infrastructure. These savings could compensate for the significant reduction in municipal fees due to parking and speeding violations.

Self-driving cars are simply better and more fuel-efficient drivers. Hypermilers are a subculture of people that optimize their driving by employing strategies such as scientific route planning, slower driving, and drafting from other vehicles to reduce fuel usage. AI-assisted vehicles can maintain and develop these positive driving practices on a large scale. Consider this: your everyday commute might need a gallon of gas, but an AV could make the same trip on half a tank of gas, saving you money and lowering carbon emissions.

New technology and AVs might cut annual CO2 emissions from transportation by 6.5 billion tonnes, reducing worldwide human carbon production by 17%. Only approximately a fifth of the savings are due to the use of alternative fuels; the rest is due to the growth of autonomous vehicles. The efficiency with which automation can combat climate change in the transportation sector will far outweigh any particular conversion from gas to electric or hydrogen vehicles (HV). While alternative fuels are important for a variety of reasons, if governments are serious about reducing carbon emissions, the best transportation investment they can make is to fund the deployment of autonomous vehicles.

Artificial Intelligence and Autonomous Vehicles

Artificial intelligence was the missing piece in making AVs work. While numerous technologies have converged to make AVs viable—from better sensors to totally electronic driving systems to high-definition maps—human-like perception will be required to solve the problems. A human driver can easily distinguish between a person crossing the road and a bus stop poster with a picture of a person on it. There is no simple technological system that can tell the difference between a puppy dashing onto the roadway and a harmless tumbleweed. The perceptual skills of any child have always been lacking in AVs.

Without a reliable AI that can identify objects and predict what they will do, there is no way to predict what they will do. Autonomous vehicles (AVs) are deadly murder machines that careen down the road, mostly blind to the environment around them. Attempts to create AVs without AI in the past have necessitated significant infrastructure investments, such as sensors to indicate what speed a car should be travelling, when it should stop, and lane markers to tell the car when it's in the lane. Pedestrians are also prohibited from entering the driving space of these vehicles because they cannot see humans.

We haven't been clear on what it means for a vehicle to be "autonomous" thus far. When we talk about autonomous vehicles, we usually mean a step up to complete autonomy. According to the Society of Automotive Engineering (SAE), this leap would be level 5, the highest degree on the autonomous scale. Level 5 automation is still a few years away by 2020, but substantial initiatives are already underway to achieve it. One side advocates the notion that full autonomy may be attained by working one's way up the automation ladder. Starting with partial automation (level 2), progressing to conditional automation (level 3), then to level 4, and finally to level 5.This strategy is exemplified by Tesla, but it is not without risk. There's a lot of evidence that when people believe they're being helped, they pay less attention to the work at hand, which increases the chances of making a mistake. Even at level 3, this alone should inhibit the idea of consumer-wide automation.

The majority of other AV startups, led by Waymo and Cruise, are attempting to move straight to level 5 autonomy. As a stopgap, AV companies are operating level 4 vehicles on public roads under the supervision of qualified professional drivers who take over when they meet unexpected scenarios, such as severe weather, and limit themselves to certain geofenced zones. Remote monitoring is a variation of this strategy, with humans ready to disable autopilot if necessary.

Since the winter of 2018, Waymo has been operating a fleet of level 4 autonomous vehicles for paying clients in Phoenix, Arizona. As with any ride-sharing service, the cars are summoned to a pickup place and arrive automatically. The user enters, and the vehicle transports them to their desired location. A safety technician is installed in the vehicle to take over in unusual edge instances known as disengagements. Technically, level 4 has the same threats as level 3 (due to human inattention), but they occur less frequently. As a car progresses from level 4 to 5, constant human care is essential, at least until the incident rates reduce to acceptable levels.

Every 180,000 miles, the average driver is involved in an accident. We want AVS to improve, so if we set a goal of 500,000 miles per disengagement for an AI driver, it's just a question of driving cars around with human technicians until the fleet averages half a million miles per disengagement. For all intents and purposes, we can consider the AV to be level 5 at that point, meaning it is suitable for consumer usage and safer than human drivers. This alone should cut casualties in half, and technological advancements can be systemic, moving from 2 times safer to 4 times, 8 times, 16 times, and so on. The escape velocity of safety will eventually reach what no human driver could match, thus crowning AVs with safety supremacy.

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AV Technology

The following is a high-level list of what human drivers do automatically or with some training: navigate to a destination, control the car's speed and direction, adjust their driving based on feelings like tyre skid, visually perceive the world around them, and predict the likely movement of other agents and react accordingly.

These inputs and outputs must be regulated by an array of sensors and controllers that feed data into a system of filters and artificial intelligence decision makers in order for an AV to function. Fundamentally, all of these technologies exist to assist answer the pressing issue, "How quickly and in which direction should I go?" in real time. It's possible to deconstruct the solution.

To begin, we must analyze how a computer can even operate an automobile. It doesn't matter how advanced perceptual technology is if a car can't move. Electromechanical actuators were necessary to push the accelerator, brake pedals, and steering wheel in early attempts at AV, such as cars in the inaugural DARPA Grand Challenge. They acted as substitutes for human driver feet and landings. Modern AVs integrate directly into drive systems with software that manages a control system, since modern automobiles have become increasingly computerized. The PID (proportional-integral-derivative) control system is an example of a control system that operates as a continuous feedback loop to smooth out basic operations like cruise control. These are in addition to the required car telematics for monitoring fundamental parameters such as if the battery needs to be replaced or whether the windshield wiper fluid level is low.
AV Technology

The following is a high-level list of what human drivers do automatically or with some training: navigate to a destination, control the car's speed and direction, adjust their driving based on feelings like tyre skid, visually perceive the world around them, and predict the likely movement of other agents and react accordingly.

These inputs and outputs must be regulated by an array of sensors and controllers that feed data into a system of filters and artificial intelligence decision makers in order for an AV to function. Fundamentally, all of these technologies exist to assist answer the pressing issue, "How quickly and in which direction should I go?" in real time. It's possible to deconstruct the solution.

To begin, we must analyze how a computer can even operate an automobile. It doesn't matter how advanced perceptual technology is if a car can't move. Electromechanical actuators were necessary to push the accelerator, brake pedals, and steering wheel in early attempts at AV, such as cars in the inaugural DARPA Grand Challenge. They acted as substitutes for human driver feet and landings. Modern AVs integrate directly into drive systems with software that manages a control system, since modern automobiles have become increasingly computerized. The PID (proportional-integral-derivative) control system is an example of a control system that operates as a continuous feedback loop to smooth out basic operations like cruise control. These are in addition to the required car telematics for monitoring fundamental parameters such as if the battery needs to be replaced or whether the windshield wiper fluid level is low.

Localization, or determining a car's position on Earth, where it is on the road, what direction it is looking, bearings, velocity, and other factors, is one of the most basic requirements for operating an automobile. Localization impairment is what makes a drunk driver such a bad driver. The car's physical position, orientation, and velocity are compared to a high-resolution global map to determine its location (containing data such as roads, speeds, intersections, and stop lights).

Satellite photos are used to create high-definition maps. The maps are then supplemented with more detailed aero plane photography (think B52s). Then, similarly with Google Maps automobiles, 360-degree details are supplied by vehicles that travel around the world and map every street. These maps are then updated with real-time data from millions of drivers' smartphones via applications like Waze, as well as public and private traffic and construction information. All AVs in a fleet share streams of sensor data to keep these maps up to date.

On board, there's a handy collection of older navigational technology known as specialized short-range communications (DSRC). This is how automobiles connect with one another, either vehicle to vehicle (V2V) or vehicle to infrastructure (V2I) communication (V2I). DSRC is a technology that was first envisioned in Futurama and is still being researched in many departments of transportation. DSRC has a new sense of urgency when it comes to connecting with more electric cars on a large scale. The occupancy grid is a computerised depiction of the world and the car's presence in it that combines localization and high-definition mapping. The next phase is to educate a vehicle to traverse the environment on its own.

Inertial Navigation System

Inertial navigation systems use a lot of the same fundamental technologies that you'd find in a smartphone. Any electrical store can sell you a mix of technologies such an odometer, accelerometer, gyroscope, compass, and global positioning technology for a few dollars. These technologies keep track of the vehicle's position, orientation, and speed. Consider an IMU to be the inner ear of a human, keeping the automobile centered and balanced.

The global navigation and satellite system (GNSS) is the most complicated of the bunch, owing to the fact that it utilizes satellites. The car's geographical position on the earth may be determined using GNSS. The most well-known example is the US military's global positioning system (GPS), although other governmental and private geospatial systems, such as BeiDou and GLONASS, can also be employed. Because an AV may be constructed to use any or all of these systems, we simply refer to it as GNSS.

To plan and manage the AV's journey from one site to another, the IMU, navigation, and control systems all come together. However, if we came to a halt there, our car would be self-driving and quite unsafe. We must teach it how to function in a dynamic environment filled by other items such as automobiles and people.

Artificial Perception

After control, orientation, and navigation, artificial perception is required, which necessitates the use of several vision systems stitched together using a method known as sensor fusion. While there is still some disagreement about how sophisticated a vision system should be, all AV work presupposes the use of human-level cameras. Many roadside markers are based on visual acuity. A motorist must pass a vision test before reacting to a speed limit or stop sign, and AVS are no exception. However, some electromagnetic sensors, like LIDAR (light detection and ranging), provide AVs superhuman perception of the environment. Many industry experts believe that AVS will someday outperform any human driver on the planet thanks to these additional sensory technologies.

While people can only see in one direction at a time, LIDAR can detect 360 degrees surrounding the automobile, even in the presence of occlusions like fog or dust, and it can even function at night. Non-laser based RADAR is also used by AVs for forward collision warning (FCW) and avoiding large objects, although it is less effective at identifying smaller things such as pedestrians or bicycles. Parking assist sensors, the type that beep when you're going to reverse into a fire hydrant, employ the same technology. All of this sensor data is put into an Extended Kaplan Filters sensor fusion system, which provides increasing degrees of recognition from signals to characters to symbols, with each level offering a more comprehensive picture of the world. These sensors work together to form a seamless whole: an ever-shifting image of the environment surrounding the car, just the way human brains do when they piece together a conscious storey from snippets of observation.

Training an Al to function confidently and accurately inside a cone of uncertainty is part of the technological challenge of constructing autonomous cars. This goes beyond sensor data alignment to allow movement on a high-definition map. "Cars will likely stay on the road, bikes will be off to the side, and pedestrians will be on the sidewalk," the AI must recognize what other objects are doing and estimate their most likely course. We all know that each of these rules might change at any time, thus the AV must be able to identify other options as well. Then there are the unspoken driving rules and subtle cues. Humans expect to observe human drivers slowly creeping towards an intersection as a signal to others who feel it is their turn to go. Humans frequently wave cars on, and when a traffic light is out, a police officer is required to guide traffic. Before we can credibly term an AV a level 5 fully autonomous vehicle, we must verify that it is educated and capable of responding to all of these circumstances plus thousands more.
Future of AV

Before level 3 AV can realize its full potential, we still have a long way to go on a number of fronts. We must clarify technical requirements and legal ramifications, as well as strive to discover answers to certain severe forecasts, such as what to do if millions of professional drivers lose their employment overnight. While autonomous vehicles are one of the most disruptive technologies in transportation history, the disruptive iceberg below the waterline will have the greatest impact.

Educating AI

In computer science, there's a bad joke called the go/go, in which the first 90% of the work accounts for the first 10% of the time, while the final 10% of the work accounts for the remaining 90% of the time. Because the consequences of failures may be so severe, autonomous cars are dubbed "Al's greatest issue." Few artificial intelligence problems necessitate such speed and precision when lives are on the line, and when a model that is inaccurate less than 1% of the time is nonetheless engaged in everyday mishaps. It may require 10x more work to train an Al model from 99 percent accuracy to 99.5 percent accuracy, and 100x more effort to get from 99.5 percent to op percent accuracy, and so on. This is the primary reason why, in 2020, AVs appear to have reached a stalemate at Level autonomy. Improving the Al's ability to drive safely for 500,000 miles between collisions is far more challenging than improving the Al's ability to travel safely for 100,000 miles. The longer a car is on the road, the more likely it is to run into uncommon edge scenarios, and Al must be prepared for the majority of them. Here are a few scenarios to consider.


Then there's the matter of the weather. While AVS operate effectively in dry settings, any minor adverse weather makes it much harder. There are basic weathers, such as rain, and more complicated weathers, such as snow and ice. When confronted with a tornado in Oklahoma, what should an AV do? We'll never get to the point when the Al powering an AV makes flawless judgement in every circumstance, and it's not always a terrible thing to want some human control over the decision-making process. A human can assess possibilities in severe instances. Should they, for example, drive through high water or wait for the flood to worsen?

Moravec's Paradox

Moravec's paradox captures problems that are relatively easy for a one-year-old to determine but complex for a computer to solve; AVs must predict other people's actions. Is that runner preparing to cross the street or simply stretching at the crosswalk? Is that a cop standing in the middle of the road? If that's the case, are such hand gestures used to guide traffic? Is it important to consider the context of a faulty traffic light?
This absence of common sense on a human level manifests itself in a variety of ways.
In 2019, it was highlighted by AVs being unable to detect stopped automobiles or having difficulty making left turns. For example, if an Aptiv car encounters a line of unexpectedly parked cars in the street, it may halt because it assumes they are all waiting to make a right turn. Making left turns is a difficult move that even human drivers have difficulty with. Cruise, a GM-backed AV business, has made some headway in this area by focusing on this specific difficulty, but any new player in the AV field will have to continue to put in herculean efforts. Alternatively, a new cottage industry will be required to offer pre-trained Al models that are ready to use.


Protection is always a problem with any computer system, but the requirement for effective security is even higher with a computer network that manages a fleet of one-ton terrestrial projectiles carrying people and goods. Consider a combination of military-grade security and medical-grade testing. From stealing supplies to redirecting movement to kidnapping to remote killing of high-ranking officials by creating automobile accidents, there are a million awful scenarios for illegal access to a vehicle. The risk of transporting narcotics and victims is further reduced because human agents are no longer required. These genuine possibilities must be avoided. We'll also need a solid infrastructure that allows the appropriate authorities to obtain information about an accident.

Few individuals in the world are capable of developing AV, and as a result, a cottage industry has sprung up to help others come up to speed. Udacity is an online training programme that teaches engineers the fundamentals of vital technologies, such as how to construct and use artificial intelligence models and how to improve the millions of lines of code required to create a basic AV. These initiatives are vital, and opportunities on the fractal frontiers of the AV sector will continue to increase.

What do we do as a society when AVs become increasingly automated and driving professions become obsolete? With nearly three million individuals involved in industrial transportation in the United States alone, whole logistical operations are likely to be automated, resulting in widespread unemployment. AVS will undoubtedly generate new professions and businesses that we aren't aware of now, but many people's skills will become obsolete in the meanwhile. As a society, we must prepare for the day when the abilities that millions of individuals have spent a lifetime honing are no longer in demand. "Cars first, people second," as New York City Traffic Commissioner Samuel Schwartz reportedly stated, "is an attitude that has been difficult to overcome." Now is the moment to make a mental shift.

Automobile production is another area affected by AVS. Car and truck ownership will decline if the promise of always-on, on-demand AV fleets comes true. While fewer automobiles on the road is beneficial for the environment and for customers, manufacturers will sell fewer vehicles, forcing reductions in assembly, component production, materials, and other supply chains.

You're sure to observe a few things if you drive through any little American town. Gas stations, auto mechanics, muffler shops, and oil charge stations are all places where you may fill up your tank. Many businesses will have few job possibilities remaining as they are consolidated owing to diminishing margins and new technologies such as electric automobiles. Municipalities that rely on traffic and parking fines to balance their operating budgets would lose those advantages, in addition to the money and taxes lost by small enterprises. This unexpected cash shortage will have a wide range of consequences, including a reduction in the number of police officers the city can hire and cuts to parks and leisure.

Perils, like any developing technology, must be weighed against benefits. The number of automobiles and trucks on the road will be reduced by autonomous vehicles, making travel safer. However, the system may be manipulated: empty "zombie" automobiles may circle the block to avoid paying parking fees, cutting revenue for many cities and towns while also raising pollution. The trucking sector employs 74 million people in the United States alone. Approximately 5% of total labor is accounted for. In twenty-nine states, "truck driver" is the top employment, and millions of support jobs are also in jeopardy. For instance, 1.7 million automated drivers won't eat at a truck stop pancake house. Throw in warehouse drivers, chauffeurs, train and boat operators. and AVs will have a marked impact on one of the last well paying jobs that can be done with only a high school education

Accidents and Death

The most significant potential for AVS is to reduce the 1.3 million yearly fatalities caused by automotive accidents. While a decrease in road deaths is clearly beneficial, there are still drawbacks. The vast majority of organs for transplantation originate from healthy persons who die in car accidents. The death toll for patients on the organ transplant waiting list will rise if the traffic death toll falls.

Consider a situation in which an AV is traveling on an icy patch of ground or is otherwise obstructed by a person. How would a computer handle this issue if the carat had to choose between murdering the pedestrian or driving the vehicle off the bridge, killing the passenger? What would a person do in this situation? Depending on who the pedestrian was, humans would respond differently. We might be more inclined to hit a single adult, but we'd rather run the car off the bridge than hit an adult carrying a little child. It's unnerving to consider all of the possible solutions to this dilemma. While it's understandable that you wouldn't want to hit a family, what if your own children were in the car? The Trolley Problem is a long-standing ethical thought experiment about human readiness to exchange life. While the original purpose of these thought exercises was to freak out freshmen philosophy students, they now have a new urgency. While humans are hesitant to rank how human lives should be valued on paper, we'll have to if we expect a machine to make comparable rapid decisions, preferably in a transparent manner.

The Trolley Problem

While there are many advantages to using AVs, we must not be fooled by the benefits and overlook the risks. Autonomous vehicles must not "suffer a victory," as journalist Alexander Kabakov put it when the Soviet Union fell apart. It's still early enough that we may choose to emphasize the advantages while minimizing the negatives. The good news is that each setback provides us with another opportunity to take control of our destiny and create the finest possible conclusion. AVs, like any new technology, are neither good nor evil fundamentally, but rather a potential to transform the world. Let us endeavor to bend that transformation in the direction of justice for the benefit of more people.


AVs will happen at scale, and in some form, despite the secret aspirations of luddites worldwide. The economic benefits are simply too tremendous. However, it's likely that the value we see now may be restricted to a few niche applications until we achieve the holy grail of self-driving cars capable of safely transporting a child to soccer practice. "We may wake up fifty years from now to find a world where Level 5 AVs never existed," Sertac Karaman, an autonomy researcher at MIT, once said. However, there are a variety of less autonomous transportation solutions that can nonetheless cause considerable economic disruption. Long-haul shipping, geofenced transportation, such as airports, and consumer fleets run remotely are all occurring now. We know that with appropriate infrastructure, we can construct automobiles that can drive in designated high-speed lanes without being watched. However, fully autonomous cars capable of navigating in all traffic circumstances would need a significant increase in effort. And until that happens, much of the AV industry will continue to invest billions of dollars on faith.


Consider a future in which automobiles were delivered on demand and ownership was unnecessary. Those stranded in cities with underfunded public transit may benefit from personal, direct transportation at a fraction of the current fees of 25 cents per mile, allowing them to pursue more employment and educational options. It is a grave injustice to need ownership of a costly and fast deteriorating transportation asset merely to participate in the economy.

We might anticipate urban and suburban real estate to change as people's work and home lives become less intertwined. It's no surprise that the University of Waterloo in Canada discovered a clear correlation between commuting duration and overall life happiness. Commuting isn't everyone's cup of tea. Furthermore, when the human population grows but land does not, a significant portion of land currently used for parking spots can be recovered for human use. Many vacant lots and garages in city centers may be converted into parks and residences, therefore enhancing quality of life and lowering living costs. And how many residences outside of cities give up perfectly decent square footage for a garage? The good news is that because millennials value convenience above ownership, the very existence of ride sharing is removing automobile ownership as a prerequisite for middle-class membership in America.

Aside from the conveniences of daily living, the cost of transporting goods will also decrease. This will expand the supply chain's possibilities. Last-mile transportation at low cost and autonomous robotic cars in warehouses can help unleash much of Industry 4.0's promise. For example, more quick, small-batch shipments can help with just-in-time bespoke manufacturing. The rate of production will increase, the volume of inventory will decrease, and the cost of transporting items will decrease. When this is combined with personal and business conveniences enabled by personal logistics and autonomous cars, the things we buy will arrive sooner, fresher, and for less money.

With the advancements in autonomous vehicles and ride-share fleets, we can finally take a step back and consider if we ever truly desired cars and trucks or just the freedom to move and move things. Transportation that is both safe and readily available is a cornerstone of liberty in the twenty-first century and beyond. Our ancestors will be perplexed as to how we managed to endure this bronze era of human-powered mobility and why it took us so long to disconnect our simian minds. This advanced technology cannot come fast enough for those of us who have lost friends and family members in car accidents. We can undoubtedly tame our own robots if we can conquer the planet on the backs of a few well-trained quadrupeds.

There's still much to do in the realm Autonomous Vehicles . If you are a researcher in the field of Autonomous Vehicles you are at the right place.

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