“Big Data” is everywhere. It powers business solutions as well as drives economic opportunity. Is it possible that “Big Data” will become the next major utility? By utility, I don’t mean its usefulness to businesses. Can data be a utility like electricity, gas or water which is distributed reliably through major cities for customer demand? With the Smart City initiatives, that certainly appears to becoming more and more a reality, but smart cities programs do not necessarily build the B2C model that major utilities do. Autonomous vehicles (AV) and Machine Learning (ML) may fill the gap that makes “Big Data” a utility. One possible business model includes customers who pay for how much data they use and the times they use it. Since AV technology will have data from internal and external sensors to evaluate road conditions and anomalies, the utility business model may come into play as a way to pay for such computation and classification. Machine learning algorithms will help create reinforcement of anomaly and object detection scenarios for AV.
Currently, cars on the market have Advanced Driver Assistance Systems (ADAS) development and includes driver assist technology such as accident avoidance sensors, drowsiness warnings, pedestrian detection, and lane departure warnings. Today’s driver-less cars are actually vehicles that are retrofitted with components that allow drivers to remove their hands from the steering wheel. To have fully autonomous vehicles, there must be a supply of historical and near real-time data to train ML models that will guide future AV. Like the generation of electrical power from a turbine, there has to be a supply and distribution approach to ML systems that is continuously providing reinforcement learning to AV. The generation of AV data must be ongoing every hour of the day for years in order to continuously train the ML models to build reliability in future AV algorithms and models.
The future on Autonomous Vehicles
CASE stands for Connected, Autonomous, Shared, Electrification (Vehicles). In many regards, its the evolution of modern transportation: A vehicle that doesn’t need a human operator, but transports people or goods to different destinations effectively, safely and efficiently with little or no impact on the environment. But not only will this vehicle be able to transport, but it will serve as a data collector and generator that could be used to determine road conditions, connect with businesses and establish business to customer or customer to business relationships.
The development of AV must be based on electrification (electric vehicles). Direct digital control and feedback systems of electrical consumption is ideal for clean and efficient generation of power. The autonomous capabilities of vehicles would not only control direction and speed but also the granularity of electrical consumption needed by the AV that would be imperceptible to a live human operator. Metrics could then be displayed to the passenger, owner or the manufacturer of the AV as feedback of its efficiency.
The main focus of the future generation of fully autonomous vehicles will be the ability keep a driver safe and successfully navigate any condition or obstacle as the AV transports its passengers to their destination…from leaving their home to getting into the vehicle, to walking into the destination. Services will be available to businesses that will allow AVs to follow exact directions where the business is and have approved parking spaces that the vehicle will navigate to. Most interfacing will be conducted through the passenger(s) smart phone(s).
Here is an example. David picks up his smart phone and clicks on an app to request reservations at a restaurant for his wedding anniversary. The service request is paired with an AV smart phone application that also sends the request to the cloud and the restaurant reservation API. The ML system in the cloud then programs the AV to navigate to the restaurant as well as park in a designated parking space (no valet needed). When the dinner is complete, David clicks on the app to pick up him and his wife and return home.
Future autonomous vehicles will not have manual overrides or speed up to make it to that movie on time.
In order for autonomous vehicles to build trust within the driving community, it must maintain consistent patterns and make decisions that ensure the safety and comfort of all its passengers. What you don’t want is the AV to immediately speed up to make a light or make sharp or quick turns to avoid oncoming traffic. This mean the automobile needs to have AI and machine learning capabilities that obeys all traffic laws and makes correct predictions on any anomaly or object. Future AV and CASE will not have steering wheels or brake pedals because that represents a manual override which in turn erodes trust with the occupants.
The future generations of AV should not have steering wheels. Most modern cars rely on a steering system that includes a “rack and pinion” assembly by which a live operator (driver) can turn the car right or left when needed. Removing the steering mechanism will allow for passenger only occupancy and create a system that is principally controlled by computerized systems instead of mechanisms that require human intervention. In the event that the vehicle requires override control by an operator, that operator will be in a vehicle control and command operations center (VOC). The center will be maned by trained commercial drivers. Such command operation centers would be third-party, provided by the manufacturer of the vehicle, or by a municipality.
Future autonomous vehicles will be fully connected mobile platforms.
Think of a smart phone and everything that it does. Now, imagine an autonomous vehicle as essentially a large smart phone that can transport passengers who are connected to what’s happening outside the car. These riders will expect to map the course to their destination through connected devices, data, cloud computing and sensors that will then be shared with businesses and users before, during and after they reach their destination. The applications for such connectivity are tremendous.
The impact of Big Data on autonomous vehicles.
As 5G wireless networks come online, smart cities and autonomous vehicles will fully utilize data to the cloud and back. 5G will facilitate unprecedented communication speed from the vehicle to the outside world allowing sensing and tracking of nearly 5,000 GBs of data per vehicle per day, making vehicles more efficient and safe. New computer processor architectures will test, train and build Machine Learning and Deep Learning models faster than in the past and help train AVs to become better equipped to conditions in cities and on highways.
Maintaining a competitive advantage has become a important business strategy.
One of the things I love about data science and data analytics is that most of the innovation done in this area has been shared in open data and open source communities. Internet sites like Kaggle, Amazon and Google have offered public data to anyone wanting to perform Machine Learning, Predictive Analysis and Deep Learning (see my review of DataSciCon.Tech). Open Source software and platforms has grown quickly as well.
This is not the case for vendors invested in the future of AV. The data collected from sensors and IoT devices in the vehicle as well as in big data cloud systems are a well guarded secret. Development SDKs for AV technology is accessible only to clients of these AV manufacturers and their partners. What this will mean to the future for AV innovation is still up for debate; However, companies certainly have the right to safeguard their proprietary research in this area. It’s not completely known what impact this strategy will have on long-term adoption of AV.