Predictive Automotive Technology: Wide Application Across Value Chain to Generate Exponential Value

Today, the automotive industry is witnessing significant incorporation of several advanced technologies in automobiles to enhance safety and efficiency of occupants. Automobile manufacturers are leveraging machine learning (ML) and artificial intelligence (AI) to comprehend the operating patterns and trends of the driver and enhance safety factor of the vehicle. ML and AI are set to become an integral part of future vehicles and automotive industry, while predictive automobile technologies are gaining significant popularity among all auto types which provide the foremost convenience to the driver. Automakers are focusing on adoption of connected gadgets and Internet of things (IoT) in their vehicles that support voice commands and allow to alter the user interface.

Predictive Analytics to Steer Towards Connected Car Industry

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

Rapid development of connected cars provides challenges as well as opportunities for the automotive industry. Keeping a track of data is one of the major challenges that manufacturers are experiencing. Connected cars progressively streamline the information into the cloud from infotainment systems, telematics systems, and the dizzying group of smart IoT sensors, as each vehicle is apt to produce over 25 gigabytes on information per hour. Thus, using predictive analytics and vehicle data analytics remain the key to monitor the deluge of data appropriately. 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 issues related to vehicle maintenance before they occur. Additionally, predictive data analytics can find meaningful correlations that would be difficult for a human to discover through holding data from warranty repairs with current vehicle sensor data.

 

Predictive maintenance analytics applications virtually extract data from every vehicle of a given model and year and equate that information with warranty repair trends. Additionally, some of the automakers believe that predictive maintenance is both logically and economically prudent, expecting to further optimize it by adopting machine learning and IoT data techniques. When the data is integrated correctly, these developments allow them to precisely and accurately pinpoint whenever the vehicle needs maintenance. Identifying issues in the vehicle proactively can avert the risk of vehicle being unexpectedly out of commission.

 

As the commercial transportation companies have been enthusiastic to implement IoT-enabled predictive maintenance, consumers at the global platform are expecting an advantage in connected vehicle technology.

 

  • Predictive Collision Avoidance

Predictive collision avoidance system is among the ongoing trend in human-operated vehicles and more recently developed in autonomous vehicles. It performs an override function to actuate emergency braking in a critical situation according to the traffic on the road.

 

Predictive analytics technology in future may make accidents a thing of the past, with the adoption of fast & big data, advanced sensors, and vehicle-to-vehicle connectivity. One of the relatable instances is the predictive collision avoidance warning characteristics in Nissan’s vehicles. The utilization of sensors on the front of the vehicle, this system can analyze the distance and speed of the vehicle traveling exactly ahead of this car along with the next predicting vehicle.

 

As automakers make applications that enhance communications between vehicles that are connected, more intricate and better effective advanced collision avoidance systems will occur in accordance with predicting drivers’ behavior.

 

Growing Adoption of Predictive Powertrain Control in Heavy Vehicles

Predictive powertrain control (PPC) came into existence a few years ago, only to gain popularity in recent times. Adoption of PPC took a little time, as automakers understood its unique benefits just in recent years. The system helps in reducing fuel consumption by up to 5% in long distance traffic. It is a unique cruise control system that helps in saving money through intelligent prediction – it uses GPS data and 3D maps to scan a road ahead. The system then automatically adjusts the speed while rolling and making gear changes accordingly. PPC makes this possible by integrating a driving style to match the topography into the automatic program.

PPC can be retrofitted in almost all series of trucks and heavy vehicles. Advancements in PPC retrofit are well-suited with any FleetBoard telematics services, as they are already being used in the trucks, and all functions are integrated and retained with the new system. Manufacturers of heavy trucks are actively approaching complementary business units to enhance their product portfolio and gain additional expertise into disruptive PPC trends. Mercedes-Benz PPC technology is now available for retrofitting in Antos, Actros, and Arcos by Mercedes-Benz partners throughout Europe. PPC in Mercedes-Benz is now ordered for an average of 64% of the heavy vehicles in long-distance traveling.

 

Posted by Alice Mutum

Alice Mutum is an experienced content writing professional, who has contributed to a number of blogs and magazines. At Future Market Insights (FMI), she works closely with research teams to help businesses around the world meet their unique market intelligence needs. She holds an interesting portfolio, with a substantial experience in delivering her content related to technology, food & beverage, automotive, packaging, consumer goods, and wide spectrum of other industry verticals.