Connected vehicle ecosystems will help with safer driving and reduce stress

Telematics Wire in discussion with Yaseen M, Director, Telematics Division, Toyota Connected India; explores how the connected vehicle ecosystem will lead to safer and convenient driving.

Q. How are you leveraging data for safer driving?

We constantly evaluate new approaches for using vehicle sensor data and ecosystem data to enhance both the safety and convenience aspects of driving. Active safety systems like in-vehicle ADAS are well known and commonplace now, and these primarily try to minimize the adverse impacts of driver error and lapses in attention towards emerging situations on the road. We are also exploring ways to utilize historical connected vehicle and connected ecosystem data to influence safer route selection and provide active and passive alerts and warnings to draw the driver’s attention towards emerging road safety conditions.

Q. How are analytics and insights into these data making a difference?

Connected vehicle data provides very interesting insights into how vehicles traverse various types of traffic and road conditions. This is still very much an evolving field of study and to me this is a promising area that can unlock exciting possibilities in the field of crash prevention, route selection, streamlining traffic flows and increasing the overall safety for road users. Another key area we get insights into is how various in-vehicle safety systems and connected systems are performing over time through the analysis of telematics data. This really helps in identifying anomalies and predicting component and sub-system failures and over time this data helps us fine tune the effectiveness and reliability of these systems.

Q. How do you see connected vehicles enhancing safety through real-time data and communication?

This is very much an evolving science. Real time (or near real time) data enables connected vehicle ecosystems to enhance safety through predictive analysis models that flag impending safety concerns. 

Data about vehicle systems/sub-systems that are performing within their operating limits (or outside their desired ranges) can be used for predictions about impending failures (sometimes catastrophic like brake failures, steering failure, etc.) with serious safety implications. 

It is also possible to analyse road conditions, speed, location from the vehicle in combination with other external information to predict dangerous road conditions and perhaps specific routes that should be avoided.

Q. How does Toyota Connect help customers with predictive analytics? Based on your data do you see predictive analysis making roads safer by preventing accidents or increasing vehicle uptime by mitigating major failure?

Predictive analytics definitely play a major role in making our vehicles safer as well as helping our customers to drive more safely and on safer routes where possible.

We already use data and predictive analytics to get insights into components that require maintenance or show excessive wear due to unusual driving patterns or poor road conditions. One aspect of this is to make vehicles more reliable and prevent breakdowns to systems that are critical to vehicle and occupant safety. The other aspect are things that we exploring in terms of using ecosystem information to make the daily commute (or a long road trip) safer by using data and predictive analytics for recommending better routes, time of travel, etc. With increasing maturity in predictive models, a combination of vehicle data and external data that feeds these models will result in more accurate analysis of prevailing road conditions, traffic patterns, weather, hazards and road closures, etc. to deliver a variety of in-vehicle warnings/alerts and recommendations that will help improve driver awareness and safety.

Q. Is ACN active for the India region? How has been the response to ACN? Any incident from the ground where ACN saved a life or helped the vehicle occupants? 

ACN – or automated collision notifications are already available in the latest generation of Toyota vehicles on sale today in India. Customers have welcomed these safety features. Overall, we see a strong positive response to the safety feature suite (that includes the ACN feature)

We also provide emergency services despatch as part of our safety services suite. We definitely have instances involving ambulance despatches in severe collision cases that triggered an ACN. Customer privacy policies prevent me from sharing specific details, but our emergency safety services have certainly helped vehicle occupants in life threatening situations arising from severe collisions.

Q. Do you think ACN would be more of a use for insurance telematics?

ACN is primarily meant as a safety feature to provide emergency assistance to vehicle occupants, notify owner and emergency contacts and generally save lives in the event of a severe collision.

While ACN data may be of use to insurance companies to verify a crash/collision damage claim, that is not its primary intention.

Q. Going forward how do you visualize the predictive analytics for vehicles 3-5 years down the lane? 

In the long term, I believe predictive analytics will likely make vehicles more dependable, safer and improve the overall usage and convenience of operating a vehicle. I believe data will be used to predict all sorts of things pertaining to road conditions and traffic patterns.

In the future predictive analytics will probably tell you the best time to depart for your daily commute (or a long road trip), the best route to take, precautions to take along the route, etc. You may get recommendations around safety and convenience (like avoid certain roads and your favourite restaurants along your route). Connected vehicle ecosystems will help with safer driving and reduce stress, for example keep track of road signs and speed limits to prevent over-speeding violations, speed cameras. 

An increasing number of sensors and the data they generate will be processed by big data models that will predict when your vehicle needs preventive maintenance, or a premature failure of components. This is not just limited to the vehicle. The data from connected ecosystems will bring external data into these predictive model to provide meaningful recommendations around route navigation and driving behaviour, to cite just two examples. The limit is only your imagination.

Q. Any data/updates which you can share about the use of your “stolen vehicle locator” feature? 

This is a feature that allows an owner to track the live location of their vehicle in cases of suspected theft. We definitely see the feature being used.

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