Connected Car Data, an Overview

Connectivity features are now becoming a standard in modern cars as every brand is now introducing these features in their cars. This has improved the driving experience and made traveling much easier and enjoyable.

Along with this the connected car presents huge opportunities with the amount of data it gathers, processes and generates. Experts predict that in coming years the data generated by the cars is only going to increase creating entirely new services and business models. According to Intel, each autonomous vehicle will be generating approximately 4,000 GB – or 4 terabytes – of data a day. By 2020, the number of Connected Vehicles is expected to reach a Quarter Billion according to a report by Gartner. Therefore the amount of data generated by cars is going to increase exponentially in the future.

This ‘explosion’ of data is expected to further increase the pace of innovation and totally transform our world. This data being generated is valuable and through the application of technology like analytics can give way to insights that can be utilized by automotive manufacturers and other members of the automotive ecosystem to not only hugely enhance end-user experience but also generate revenue for themselves. But there are also complex challenges in this path as there are issues like user privacy, data management processes, built-in data security mechanisms, are involved which have not been the forte of the incumbent players and will be a challenge for them to change themselves on how they operate.

Opportunities

Application of analytics to data can be used by the companies to provide an array of innovative services which will, on one hand, increase the revenue pool and on the other improve customer service enhancing brand loyalty for the companies.

Predictive maintenance is one such application that identifies vehicle maintenance issues before they occur. It leverages data from warranty repairs and vehicle sensors to finds a meaningful correlation. Data from different vehicles can be collected and analyzed by the companies to find anomalies in their product and help them to correct them. The analysis of data can also help in the development of new business models.

Predictive collision avoidance system is another application of vehicle data. By the use of data from sensors, car-to-car connectivity, and analytics the situations that may lead to accidents can be predicted and hence avoided. Some companies have already started implementing this technology. Nissan has introduced a Predictive Forward Collision Warning feature that utilizes sensors on the front of the vehicle, the system is able to analyze the speed and distance to the vehicle traveling ahead of the vehicle, as well as that of the next preceding vehicle. In case of any of the proceeding two vehicles behaving in a manner that can be regarded as dangerous is alerted to the driver in form of a visual alert and audible signal. A signal is also sent to temporarily lock the seat belts in case of impact. Mercedes too has COLLISION PREVENTION ASSIST uses data from radar to constantly monitor closing speeds between the car and the moving vehicles around it. If the system determines that a collision is likely, it can help you apply the ideal level of braking.

The car data can also be utilized to develop services that combine advanced location analytics, leading software technology, and a driver’s personal preferences to make driving more informed, safer and enjoyable. Companies are using location-based intelligence to direct the customers to the nearest store location. The data can also be utilized to provide roadside assistance companies provide an app that allows them to track your exact location without the need in case of any accidents. Utilizing the location data the companies or authorities can deliver real-time information, such as traffic updates or weather reports. The data can also be utilized for proximity-based marketing allowing the companies to push ads only to individuals within the same geographic location.

Autonomous vehicles require demand richer, more up-to-date, more accurate map. The connected car data can be used to achieve this, data from onboard sensors in different cars can help generate real-time information on road condition that can be used to develop maps that other drivers or autonomous vehicles can use.

Connected vehicles are vulnerable to cyber attacks and that can be very catastrophic in this case as the lives of the passengers are directly involved. In this context, predictive analytics can play a big role in preventing cyber attacks by predicting its occurrence by warning the users of it. Using analytics the intruder's behavior is read and if it differs from that of the recorded pattern of the original user, they can be warned to take action.

Recent Initiatives:

·       J.D. Power with HARMAN plans to go beyond measuring consumer insights to help automakers around the world better measure and understand how their evolving products are satisfying customer needs. Both the companies will provide functional-level insights into how consumers are interacting with the systems and what they may want from the in-car experience.

 ·       Toyota Motor Corporation (Toyota), with Toyota City, is to start Japan’s verification testing for road maintenance inspections using vehicle data obtained from connected cars. The verification testing will enable assessment of whether the degree of road deterioration index values computed from the car’s behavior data and actual road conditions are consistent, and validate these findings on more typical regional roads. Toyota also aims to further advance its technology toward supporting administrative services that implement road maintenance and inspection work in Toyota City more accurately and appropriately.

 ·       Dash and VINchain have entered into a partnership, to leverage their joint interest in using data to improve vehicle ownership and maintenance. Dash Dash is a Vehicle Intelligence Platform which offers smart driving products and VINchain is a tamper-proof and decentralized vehicle data platform that offers a decentralized blockchain-based vehicle history report, to authenticate vehicle maintenance, repair and ownership.The partnership aims to integrate VINchain’s technology into the core Dash products, thereby enabling users to add their real-time driving data into Vinchain’s infrastructure – this will create a ledger of how the car has performed and been maintained.

 ·       Otonomo has announced the Consent Management Hub, a new capability within its neutral automotive data services platform, which provides simple, secure data access and transforms data into actionable insights for services such as predictive maintenance, emergency services, on-demand fueling, in-vehicle delivery, insurance, and smart cities. The Consent Management Hub provides an efficient way for connected car drivers to take control over the sharing of their personal automotive data.

 ·       Waycare has announced a data-sharing partnership with Waze, the free, real-time crowdsourced traffic and navigation app. The partnership is designed as a two-way data share of municipal and road traffic data, Waycare traffic insights, and aggregated road traffic data from Waze. The partnership will enable cities to communicate back with drivers and warn of dangerous roads, hazards, and incidents ahead.

·       Moovit, transit data and mobility analytics company and transit app Moovit has receiced investmenst from Intel, BMW etc. The Israeli startup combines information from public transit operators and authorities with live information from its user community and offers transit riders a real-time picture, including the best route for the journey.

 ·      INRIX is working on new offering by that combines real-time traffic, incident, and parking data with machine learning and predictive analytics, to efficiently guide the drivers to open parking spots. When drivers are approaching their destination INRIX pulls real-time data to calculate the best path to take to find parking that minimizes both drive time, walk time and the cost of parking. Drivers will also have a more accurate estimated time of arrival (ETA) that incorporates parking search time.

·       Volvo Cars and Volvo Trucks will share real-time data to expand coverage of the companies’ connected safety technology, a cloud-based system that allows vehicles to communicate with each other and alert drivers of nearby hazards.

 Challenges:

Although the connected car data presents us with many opportunities but there are challenges as well in which data privacy, data quality and security are at the forefront. This has never been the forte of the traditional incumbent players therefore as the industry changes the companies will have to adopt and change according to these.

There has been a demand for connectivity features in the cars but at the same time a significant portion of the consumers have expressed their anxiety about the digital safety and data privacy issues through different polls and surveys.

If data is stored in the vehicle for some period personal privacy as well as the privacy of the other parties connected to the users can be compromised in case of any breach. Recording of data related to the trips of the customers can also lead to compromise in their security. Moreover, connected vehicles also creates scenarios for unwanted third-party access to that data, increasing the risk of a cyberthreat. A hacked vehicle could not only have fatal consequences for the driver and passengers but for anyone or anything physically present around the self-driving car.

In 2015, some ethical hackers to show the vulnerability of these vehicles they infiltrated into cellular connectivity of a Fiat Jeep and were able to compromise the backbone of the car’s electronics, CANBus, through it they were able to control starting, stopping, accelerating, and steering, taking complete control over the car.

Therefore with each degree of connectivity a variety of legal regimes, ranging from expectations of privacy and security emanating from common law and numerous other regulations are implicated.

Taking this into consideration there will be a need of single regulation that governs the handling and securing of all types of sensitive personal information. Absence of such regulation impedes the usage of connected car data. Another hurdle to the development of an overarching regulation covering connected vehicles is that the technologies are still in development. In such a scenario the industry would prefer self-regulation but still some form of federal pre-emption will be necessary in order to avoid the patchwork of laws. There are also questions involving the ownership of the data that needs to be addressed.

There was an initiative taken in this direction by NHTSA that published a paper entitled “Cybersecurity Best Practices for Modern Vehicles.” in which it laid down some “best practices” that need to be followed by the companies to ensure cybersecurity. It talked about five principles namely, identify, protect, detect, respond and recover. It also recommended stricter implementation of standards like ISO 27000. However, these practices were “non-binding guidance” but gave a direction in which the industry needs to work.

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The article also published as Lead Story in SmartAutomotive Magazine September-October Issue

Updates based on Press releases by the companies