The Technology behind Autonomous vehicles

Autonomous vehicles are able to function and navigate using sophisticated technology. There are several technologies that provide the vehicle with the ability to function properly. We will look at a few below.

GPS: A mapping system provides the foundation for the directions an autonomous vehicle has to take to reach its final destination. This map is used alongside cameras to navigate through the roads.

Laser Illuminating Detection and Ranging (LIDAR): LIDAR creates a 3D map, which allows the autonomous vehicle to detect its surroundings. A laser beam is used to map out objects near the vehicle.

Radar: Radars are usually mounted in pairs at the front and rear of an autonomous vehicle. Radar enables the vehicle to sense the relative motion of surrounding cars and other moving objects. This enables the vehicle to essentially understand when to stop, start and change its speed in response to the constantly changing environment.

Sonar: Sonar technology enables the autonomous vehicle to respond swiftly to its environment by understanding the relative motion of other moving objects near by. It’s capable of determining when the brakes should be applied and when to steer away to avoid hazards.

Cameras: Cameras are used alongside the numerous other technologies to help the autonomous vehicle understand its surroundings. The cameras help the vehicle navigate by providing accuracy of nearby objects up to 30 meters.

Further investigation and analysis of all of these technologies is required to fully understand how they function. We will look further into LIDAR.

How is it used: Similar to how Bats use sound to navigate through their surroundings, LIDAR uses laser light to help the autonomous vehicle travel. The reflection of the light rays on surrounding objects enables the vehicle to understand the object’s relative distances.

Pros: LIDAR can be used without limitations of its surrounding environment. It is not dependent on the on the time of day, as it emits its own light. LIDAR technology provides the vehicle with high-resolution results which enables the vehicle to produce a 3D map.

Cons: The cost of this technology is quite high given several restrictions. LIDAR is only able to emit its lights up to 70 meters. LIDAR is also has difficulty understanding reflected light when there is smog or fog.

Future Potential: LIDARs can be improved by enhancing the data retrieval of the technology. It has been noted that LIDAR is generally slower in refreshing its data and it has difficulty sensing and recording objects that are in motion relative to the vehicle. LIDARs are powerful tools but still have room to improve.


Patkar, Mihir, Dan Price, and Bryan Clark. “How Self-Driving Cars Work: The Nuts and Bolts Behind Google’s Autonomous Car Program.” MakeUseOf. N.p., 21 Feb. 2015. Web. 14 May 2017.

Brad Templeton Cameras or Lasers? N.p., n.d. Web. 14 May 2017

2017 CDIO Calgary, AB

2017 CDIO Calgary, AB

I am honored to be a participant at the 13th International CDIO conference in Calgary, Alberta.

The question being asked at the 2017 CDIO Academy is:

What is the biggest challenge facing autonomous vehicles, and what may a solution be?

I will begin my first blog post by covering basic facts of autonomous vehicles, their applications, their feasibility and current models being tested today.

There are several applications for autonomous vehicles. They may provide disabled and handicapped people an opportunity to travel more accessibly. An autonomous vehicle has the power to prevent accidents that happen with reckless or distracted drivers. They can also ensure vehicles are operating at safe driving conditions within the speed limit. There is a lot of time spent driving especially in highly populated areas; an autonomous vehicle will enable the passenger to complete other tasks during the duration of the drive.

An autonomous vehicle can be more clearly defined by considering various levels for various functionalities. SAE defines Levels 0-5 as various classifications for autonomous vehicles.

There are ultimately three various ranges where we can define the human driver as being in control of the driving. An increase in a level results in a decrease in human control

Level 0: No Automation- The human driver is in full control.

Level 1: Driver Assistance- The system plays a role in steering and acceleration/deceleration.

Level 2: Partial Automation- This system is in full control of the steering and acceleration/deceleration.

Levels 3-6 is categorized as its own group since it involves the system monitoring the driving environment

Level 3: Conditional Automation- The system controls the steering, acceleration/deceleration and monitors the driving environment.

Level 4: High Automation- The system controls the steering, acceleration/deceleration, monitors the driving environment and is in control of the dynamic driving.

Level 5: Full Automation- The system controls the steering, acceleration/deceleration, the dynamic driving, monitors the driving environment and is fully capable of driving in all modes.

There have been several autonomous vehicle prototypes, some of which have been even tested in public roads. Two such vehicles are discussed below

Vehicle: Spirit of Berlin

University: Freie Universität Berlin

SAE Classification Level: 4

Characteristics/Behaviors: These vehicles use advanced sensors along with previously defined GPS maps to navigate. The vehicles are able to drive through public roads, where traffic, pedestrians and other roadside obstacles are present. It is interesting to note that these vehicles are being tested to become semi-autonomous. This gives us the power to remotely control the car using an iPhone, for example.

Tests: The vehicles are frequently tested and are in fact licensed to navigate in the roads of Germany. The German Federal Ministry of Education and Research provides the means to test the vehicles.

Vehicle: Waymo

Company: Google Inc and Alphabet Inc.

SAE Classification Level: 4

Characteristics/Behaviors: With the assistance of a Velodyne 64 beam-laser, these vehicles are able to generate a 3D map of their surroundings. The generated maps along with previously defined GPS data are combined to create models of the vehicles’ surroundings. These maps become the eyes of the vehicle allowing it to navigate in the real world. The mapping information stored in the car’s software has defined speed limits for all routes, ensuring the car obeys the limit at all times. However, there is much room for improvement as the vehicles have difficulty identifying miscellaneous objects such as garbage, which do not need to be steered around.


These vehicles have been frequently tested in labs as well as on public roads. In fact, they have even driven over the Golden Gate Bridge! While the cars have been able to drive autonomously over 160 000 miles, they have been involved in a few collisions.13 of the 14 collisions occurred while a human operated the vehicle. The other collision occurred due to a software issue. While these vehicles have indeed been tested at great distances it should be noted that they have not been tested under all conditions. For example, the vehicles have not been tested in heavy rain or snow.

For more information please visit:

Click to access automated_driving.pdf