Automotive technology

Predictive automotive technology: wide application in the value chain to generate exponential value

Today, the automotive industry is witnessing the significant integration of several advanced technologies in automobiles to improve occupant safety and efficiency. Automakers are leveraging machine learning (ML) and artificial intelligence (AI) to understand driver operating patterns and tendencies and improve the vehicle’s safety factor. ML and AI are set to become an integral part of future vehicles and the automotive industry, while predictive automotive technologies are gaining popularity among all types of automobiles that provide the greatest comfort to the driver. Automakers are focusing on the adoption of connected gadgets and Internet of Things (IoT) in their vehicles that support voice commands and allow UI changes.

Predictive analytics to move towards the connected car industry

IoT in connected cars is the next big digital development in the automotive sector, which will create another revolution thanks to the introduction of autonomous vehicles. These self-driving cars include a sensor management system in which the powerful sensors are attached to the vehicle, making IoT vehicle-to-vehicle communication a reality.

The rapid development of connected cars presents challenges as well as opportunities for the automotive industry. Keeping track of data is one of the biggest challenges manufacturers face. Connected cars Gradually streamline information into the cloud from infotainment systems, telematics systems, and the dizzying array of smart IoT sensors, as each vehicle is likely to produce over 25 gigabytes of information per hour. Thus, the use of predictive analytics and vehicle data analytics remains key to appropriately monitoring the data deluge. Some of the predictive analytics that will ultimately shape the future of connected cars are:

  • Predictive maintenance recognizes vehicle maintenance issues

Predictive maintenance – a popular application of predictive analytics – detects vehicle maintenance issues before they occur. Additionally, predictive data analysis can find meaningful correlations that would be difficult for a human to discover by keeping warranty repair data with current vehicle sensor data.

Predictive maintenance analytics applications extract data from virtually every vehicle of a given model and year and equate this information with warranty repair trends. Additionally, some automakers believe that predictive maintenance is both logical and economically prudent, hoping to further optimize it by adopting machine learning and IoT data techniques. When the data is correctly integrated, these evolutions make it possible to identify with precision and accuracy when the vehicle needs maintenance. Proactively identifying problems in the vehicle can avoid the risk of unexpected vehicle shutdown.

While commercial transportation companies have been enthusiastic about implementing IoT-enabled predictive maintenance, consumers across the global platform are expecting an edge in connected vehicle technology.

  • Predictive collision avoidance

The predictive collision avoidance system is part of the current trend in human-driven vehicles and has been developed more recently in autonomous vehicles. It performs a neutralization function to activate emergency braking in a critical situation depending on the traffic on the road.

Predictive analytics technology in the future could make accidents a thing of the past, with the adoption of fast and big data, advanced sensors and vehicle-to-vehicle connectivity. One relevant example is the predictive collision avoidance warning features in Nissan vehicles. Through the use of sensors in the front of the vehicle, this system can analyze the distance and speed of the vehicle moving exactly in front of this car as well as the next prediction vehicle.

As automakers create apps that improve communications between connected vehicles, more complex and effective advanced collision avoidance systems will emerge in line with the prediction of driver behavior.

Growing Adoption of Predictive Powertrain Control in Heavy-Duty Vehicles

Predictive Powertrain Control (PPC) originated a few years ago, gaining popularity in recent times. Adoption of PPC has taken a bit of time, as automakers have only realized its unique benefits in recent years. The system helps reduce fuel consumption by up to 5% in long-distance traffic. It is a singular cruise control system which helps save money with smart prediction – it uses GPS 3D data and maps to scan a road ahead. The system then automatically adjusts the speed while driving and makes gear changes accordingly. PPC makes this possible by integrating a driving style adapted to the topography into the automatic program.

The PPC can be retrofitted to almost all series of trucks and heavy vehicles. Advances in PPC modernization are well suited to all FleetBoard telematics services, as they are already used in trucks, and all functions are integrated and retained with the new system. Heavy-duty truck manufacturers are actively approaching complementary business units to enhance their product portfolio and gain additional expertise in disruptive PPC trends. Mercedes-Benz PPC technology is now available for retrofitting Antos, Actros and Arcos from Mercedes-Benz partners across Europe. PPC at Mercedes-Benz is now ordered for an average of 64% of long-distance heavy goods vehicles.