Autonomous Car using IoT

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A driver less car (sometimes called a self-driving car, an automated car or an autonomous vehicle) is a robotic vehicle that is designed to travel between destinations without a human operator. Various techniques will be used to allow vehicles to understand their surrounding environment in a dynamic driving environment, and the vehicle must be able to act in response to specific changes in their environment. Autonomous means self-governance. Many historical projects related to vehicle autonomy have been automated (made to be automatic) due to a heavy reliance on artificial hints in their environment, such as magnetic strips. According to the National Automobile Dealers Association, the average American spends around $30,000 on a new car or light truck.

According to a recent study, “Emerging Technologies: Autonomous Cars—Not If, But When,” IHS Automotive forecasts that the price for the self-driving technology will add between $7,000 and $10,000 to a car’s sticker price in 2025, a figure that will drop to around $5,000 in 2030 and about $3,000 in 2035. Tesla is aiming to have its driverless technology ready by 2018. Uber’s autonomous car is hitting the streets in Pittsburgh. Google has never given a formal deadline, but has suggested it’s working on having the technology ready by 2020.BMW will introduce its self-driving cars in China in 2021.

History of Autonomous car:

1478: Leonardo Da Vinci sketches plans for a three-wheeled driverless cart.
1925: Francis Houdina’s radio-controlled “Phantom Auto” wows passersby as it cruises the streets of New York with no one behind the wheel.
1939: GM’s World’s Fair exhibit predicts driverless cars will be traveling along automated highways by 1960.
1958: Researchers begin experimenting with autonomous cars controlled by signals from cables buried in the pavement.
1994: Two robotic vehicles successfully travel 1,000 kilometers of multilane highways from Munich to Paris.
1997: The Demo ’97 program tests Automated Highway System technology on closed portions of Interstate 15 near San Diego.
2004: Of the 15 competitors in the first Defense Advanced Research Projects Agency (DARPA) Grand Challenge, a government-sponsored contest to develop autonomous vehicles, none manage to traverse more than 8 miles of the 150-mile off-road course.
2005: The second running of DARPA’s Grand Challenge sees five of the 23 entries complete the 132-mile course through the Mojave Desert.
2007: The related DARPA Urban Challenge required competitors to navigate a 60-mile paved course filled with real-world driving situations.
2009: Google begins testing its self-driving cars on Bay Area roads. Over the following five years, program vehicles rack up more than 500,000 accident-free miles.
2010: A driverless Audi sports car travels to the summit of Pikes Peak in 27 minutes, just 10 minutes shy of times set by professional race car drivers competing in the annual hill climb event.
2011: Nevada passes the first legislation specifically approving autonomous car operation on state roadways. Florida and California quickly follow suit.
2012: Nissan debuts autonomous car that can drop you off, park itself and return to pick you up.
2015: The National Highway Traffic Safety Administration (NHTSA) is expected to announce first standards for vehicle-to-vehicle communication.
2020: Date many automakers expect to have their first autonomous (or at least semi-autonomous) models in dealer showrooms.
2035: By this date, experts predict 75 percent of cars on roadways will be autonomous.

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The 6 levels of autonomous driving

Level 0—No Automation

The human driver is in charge full time of all aspects of the dynamic driving tasks, even when the car is enhanced by warning or intervention systems. This still describes almost all cars on the road today.

Level 1—Driver Assistance

This is when a driver is in control of either steering or acceleration/deceleration using information about the driving environment, with the expectation that the human driver performs all remaining aspects of the dynamic driving task. This scenario basically covers current radar-based cruise control.

Level 2—Partial Automation

This level is when a “driving mode” controls both the steering and acceleration/deceleration, but the human driver “performs all remaining aspects of the dynamic driving task.” That means the driver is still responsible for changing lanes, exiting freeways, making turns and such.

Level 3—Conditional Automation

This level is where the “automated driving system” monitors the driving environment. It controls the acceleration, braking and steering but expects that the human in control “will respond appropriately to a request to intervene.”

Level 4—High Automation

Level 4 means that the system controls all aspects of the driving tasks, including when a driver doesn’t respond appropriately to requests to intervene. Recently, both Ford and Volvo have said they will offer a Level 4 car before 2021. We can’t say if those will be ride-sharing vehicles or in what cities they’ll be offered — it might just be around the Ford campus in Dearborn, Michigan.

Level 5—Full Automation

The car is operated full time by an automated driving system and all aspects of the dynamic driving tasks under all roadway and environmental conditions are controlled autonomously. This is what we’re really waiting for. Level 5 is when you can get in your car in the morning, tell it to drive to work and you can take a nap. No automaker has set a timeline for bringing a Level 5 car to market.

Technology  Used
            There are several systems that work in conjunction with each other to control a driverless car. Radar sensors dotted around the car monitor the position of vehicles nearby. Lidar sensors help to detect the edges of roads and identify lane markings by bouncing pulses of light off the car’s surroundings. Autonomous cars use a variety of techniques to detect their surroundings, such as radar, laser light, GPS, odometry and computer vision. Advanced control systems interpret sensory information to identify appropriate navigation paths, as well as obstacles and relevant signage. Autonomous cars must have control systems that are capable of analyzing sensory data to distinguish between different cars on the road.

LIDAR

Laser Illuminating Detection and Ranging – or LIDAR – is used to build a 3D map and allow the car to “see” potential hazards by bouncing a laser beam off of surfaces surrounding the car in order to accurately determine the distance and the profile of that object.

(Image Source: www.cnet.com)

Radar

Its one fatal flaw is in its ability to accurately monitor speed of surrounding vehicles in real time. This is where the four bumper-mounted radar units pick up the slack. With two sensors in the front bumper, and two in the rear.This technology works in conjunction with other features on the car such as inertial measurement units, gyroscopes, and a wheel encoder in order to send accurate signals to the processing unit (the brain) of the vehicle in order to better make decisions on how to avoid potential accidents.

High-Powered Cameras

The actual camera technology and setup on each driverless car varies, but one prototype uses cameras mounted to the exterior with slight separation in order to give an overlapping view of the car’s surroundings. This technology is not unlike the human eye which provides overlapping images to the brain before determining things like depth of field, peripheral movement, and dimensionality of objects.Each camera has a 50-degree field of view and is accurate to about 30 meters. The cameras themselves are quite useful, but much like everything else in the car they are redundant technology that would allow the car to work even if they were to malfunction.

Sonar

The limitations of sonar are its narrow field of view and its relatively short effective range (about 6 meters). However, the inclusion provides yet another redundant system that allows the car to effectively cross-reference data from other systems in real time to apply the brakes, pre-tension seat belts for impact, or swerve to avoid obstacles.

Positioning

The system works alongside the on-board cameras to process real-world information as well as GPS data, and driving speed to accurately determine the precise position of each vehicle, down to a few centimeters all while making smart corrections for things like traffic, road construction, and accidents.

Sophisticated Software

The software processes all of the data in real-time as well as modeling behavioral dynamics of other drivers, pedestrians, and objects around you. While some data is hard-coded into the car, such as stopping at red lights, other responses are learned based on previous driving experiences. Every mile driven on each car is logged, and this data is processed in an attempt to find solutions to every applicable situation.The learning algorithm processes the data of not just the car you’re riding in, but that of others in order to find an appropriate response to each possible problem. Behavioral dynamics are also mapped and this data is used to help recognize situations before they happen, much like a human driver.

 

 

The Advantages of Autonomous Car

  1. Fewer Accidents: Reducing human errors should drastically decrease the number of car accidents.
  2. Better Traffic Flow: Computers have a much better holistic understanding of traffic flow and can drive multiple cars in unison, thus allowing better traffic flow, shorter driving times, and more fuel economy.
  3. Efficiency: Since autonomous cars will be able to drive much closer together to each other, automated cars will furthermore decrease traffic and increasing fuel economy by decreasing vehicle drag.
  4. Time: In my opinion, the biggest benefit of autonomous vehicles is the saved time. People (formerly drivers) will instantly have their commute time freed up for work and leisure activities while stuck in their cars.
  5. Less Stress: Driving can be stressful at times, thus automated driving can and will reduce stress.
  6. Fewer Traffic Guides: Driverless cars do not need street signs, road signs, traffic lights, and even road lights, thus reducing governments’ costs.
  7. Less Parking Spaces: Automated cars can drop people off at the entrance of buildings and more willing to drive an extra distance to find available parking.

The Disadvantages of Autonomous Car

  1. Laws and Regulations: If an automated car is in an accident, who is responsible? Is it the people in the car (if any), the car’s owner(s), the car’s manufacturer(s), or the car’s software creator(s)?
  2. Longer Trips: In my opinion, people would be much more willing to tolerate longer commutes, if their travel time is free and less stressful. As a result, increase fuel consumption and traffic could increase.
  3. Massive Job Loss: Truck drivers, taxi drivers, and even delivery people can and will lose their jobs.
  4. Police: With fewer people violating traffic laws (i.e. speeding) and fewer accidents, fewer people officers will be needed as well as less revenue for the police/government (fewer tickets).
  5. Increased Complexity and Risk: Computers can malfunction, be hacked, spontaneous crash and reboot, and automated cars are heavily reliant on GPS systems. All of these systems are increased risk for safety when using an autonomous vehicle.
  6. Cost: Automated cars will have a higher cost than non-automated vehicles, however this cost maybe offset by fewer cars being maybe needed.

 

 

MeenaG Staff

Internet of Things Enthusiast

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