Driving Safer with Smart Driver Scores: An Inside Look at Trip Scoring and Driver Behavior Analysis

 

In my earlier post, I mentioned that I work as a solution architect for a vehicle data platform. In this post, I will discuss how we use trip data information to score driver behavior, using what we call a "smart driver" score. Like a credit score, a driver score is an indicator of a driver's behavior, which can be used for things like usage-based insurance.

The term "smart driver" typically refers to an individual who can optimize their driving behavior to improve safety, fuel efficiency, and comfort. A smart driver might use advanced technologies, such as real-time traffic information or driver-assist features, to make informed decisions about how to operate their vehicle. They might also adjust their driving habits, such as reducing speed, avoiding sudden acceleration and braking, and following a consistent pace, to minimize fuel consumption and emissions.

Smart driver programs and initiatives are often designed to educate drivers about the benefits of safe and efficient driving, and to provide tools and resources to help drivers make informed decisions on the road. Some programs may also offer incentives, such as rewards or discounts, to encourage drivers to adopt safe and efficient driving practices.

In the context of connected and autonomous vehicles, the term "smart driver" may also refer to the vehicle's advanced systems and technologies, which are designed to optimize driving performance and provide a more comfortable and efficient driving experience.

The term "smart driver" is used by a variety of organizations and companies, including automotive manufacturers, government agencies, non-profit organizations, and technology companies.

Automotive manufacturers, such as Tesla and General Motors, may use the term to describe the advanced driver-assist technologies and safety features that they offer in their vehicles.

Government agencies, such as the National Highway Traffic Safety Administration (NHTSA) and the Environmental Protection Agency (EPA), may use the term to describe their initiatives to promote safe and efficient driving practices.

Non-profit organizations, such as the National Safety Council, may use the term to describe their educational programs that aim to promote safe and responsible driving practices.

Technology companies, such as telematics providers and software developers, may use the term to describe their products and services that aim to improve driving performance and provide a more efficient and connected driving experience.

Overall, the term "smart driver" is used to describe individuals and organizations that are focused on optimizing the driving experience, and promoting safe, efficient, and sustainable driving practices.

Core trip concepts, data collection, scoring methodology

When owner is driving vehicle from point A to point B, Ignation ON/OFF cycle,  smart driver system will rate your trip based on various factors such as the duration of the trip, the condition of the road, the traffic, and your driving experience. Here are some examples of factors you might consider when rating a trip:

Drive Time: How long did it take you to complete the trip? Was it faster or slower than expected?

Driving experience: Did you enjoy driving the vehicle? Was it easy to handle, or were there any challenges with maneuvering or controlling the vehicle?

Comfort: Was the trip comfortable? Did you experience any issues with the vehicle, such as discomfort from the seats, or noise from the engine or road?

Road condition: Was the road in good condition? Were there any obstacles, such as potholes or construction, that impacted your trip?

Traffic: Was there a lot of traffic on the road? Did you experience any delays or slowdowns due to congestion?

2023: The Year of Market Uncertainty?

The planet Saturn returns to the same position relative to Earth every 30 years, and it is believed that similar outcomes can be expected as seen in 1993 or 1963. These events may include an abundance of innovation, volatile markets, and instances of death and destruction. This is my first time tracing this phenomenon, and I am eager to see the outcome.

Currently, in USA, we are experiencing various financial conditions, such as high inflation and low employment rates. Need to final outcome.

In 1993, the global financial markets had a positive performance overall. The Dow Jones Industrial Average (DJIA) had a total return of 8.25% for the year, while the S&P 500 had a total return of 4.46%. The NASDAQ also had a positive performance, with a total return of 7.62%. The yield on the 10-year Treasury note also fell during this period, which generally indicates a strong bond market.

In terms of international markets, the Nikkei 225 in Japan had a total return of -0.31%, while the FTSE 100 in the United Kingdom had a total return of 3.57%. The DAX in Germany had a total return of 9.58%.

The U.S. economy continued to expand during this period, with the Gross Domestic Product (GDP) growing by 2.9% in 1993, and the unemployment rate falling to 6.9%. The inflation rate was also relatively low, at 3.0%.

It was worth mentioning that the interest rates were relatively high at that time, with the Federal funds rate at 3.25% by the end of 1993.

Overall, the financial markets in 1993 were characterized by steady growth, low inflation, and a strong bond market.

The Power of Data: Transforming Auto Insurance with Vehicle Management Systems

I am working in vehicle data management system design, development, and support.

While I can not specify fine details, (i.e. data used by specific auto insurance providers), data is being collected heavily and used by many.

1.     Risk assessment: By collecting and analyzing data about a vehicle's usage, insurance companies can better understand the risks associated with insuring that vehicle. For example, data about a vehicle's speed, acceleration, and location can be used to assess the likelihood of an accident occurring.

2.     Premium calculation: Based on the risk assessment, insurance companies can calculate the premium for insuring a vehicle, taking into account the specific risks associated with that vehicle.

3.     Fraud detection: By collecting data from onboard systems and other sources, insurance companies can detect instances of fraud, such as staged accidents or false claims.

4.     Claims management: In the event of a claim, insurance companies can use the data collected by the vehicle data management system to verify the details of the claim and assess the damage to the vehicle.

5.     Usage-based insurance: Insurance companies can offer usage-based insurance plans, which allow drivers to pay premiums based on the actual usage of their vehicles. By collecting and analyzing data about the usage of vehicles, insurance companies can determine the appropriate premium for each driver.

Here are some popular vehicle data signals that are commonly collected and analyzed by vehicle data management systems.

1.     Speed: The speed at which the vehicle is traveling can provide insights into the driving behavior of the driver and the likelihood of an accident occurring.

2.     Acceleration: The rate at which a vehicle accelerates can provide insight into the driving style of the driver and the likelihood of an accident occurring.

3.     Location: By tracking the location of a vehicle, insurance companies can determine the risk associated with insuring that vehicle, based on factors such as the road conditions, traffic density, and likelihood of accidents.

4.     Engine data: Engine data, such as RPM and fuel consumption, can provide insights into the health and performance of a vehicle, which can impact the likelihood of an accident and the cost of repairs.

5.     Brake data: By tracking the usage of a vehicle's brakes, insurance companies can assess the driving behavior of the driver and the likelihood of an accident occurring.

6.     Steering data: Steering data, such as the angle of the steering wheel and the force applied to the steering wheel, can provide insight into the driving style of the driver and the likelihood of an accident occurring.

7.     Fuel data: Fuel data, such as the amount of fuel consumed and the fuel efficiency of a vehicle, can provide insights into the driving behavior of the driver and the likelihood of an accident occurring.