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Method for identifying and displaying accident prone roads on mapping applications Disclosure Number: IPCOM000253198D
Publication Date: 2018-Mar-13
Document File: 2 page(s) / 16K

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Method for identifying and displaying accident prone roads on mapping applications

A driver has no easy way to identify whether the current road of travel has a high rate of accidents. This information may be helpful in allowing the driver to make informed decisions about which road on which to drive or the speed at which to drive.

The novel contribution is an algorithm that provides drivers with a seamless and consistent method for determining which roads have a high rate of accidents. The algorithm and associated system give drivers accurate real time information about roads in the form of a score that represents the frequency of accidents that have occurred on a section of the road. This information allows a driver to make informed decisions about whether to travel on a road or certain sections of a road.

Input for this is a vehicle's GPS location and the current time of day (TOD). Using this information, the algorithm:

1. Pulls similar data points from databases containing insurance records and police records from previous accidents

2. Uses this data to determine the rate of accidents, under similar conditions, on each road from the last five years

3. Compares this rate of accidents on a given road to the national average and determines the percent difference from the national average rate of accidents

4. Uses the calculated percent difference to generate a severity score

The system pulls data from a database that contains insurance and police records from the last five years. It enters new accident information database. Some of the main factors to store include TOD, weather, traffic information, speed of vehicle, and location at the time of the accident. This information is the basis of the rate of accidents.

In an example embodiment, when a driver approaches a new road or enters a new zone within the same road, the system:

1. Retrieves the driver's current GPS location and TOD

2. Queries weather information from existing weather databases

3. Chooses data points similar to the driver's current conditions

4. Constructs a clustering of data that maps the number of accidents and TOD to the section of the road. The system obtains the rate of accidents with the calculation:

rate of accidents = number of accidents that occurred on that road/the number of drivers total on the road over the...