Cognitive-based traffic incident snapshot triggering

A system comprising:

• a plurality of local sensors located on a vehicle;
• a memory located on the vehicle;
• and
• a processing unit located on the vehicle, the processing unit communicatively coupled to
• each of the plurality of local sensors and to the memory, wherein the processing unit is configured to execute a first software agent configured to acquire data from each of the plurality of local sensors in timeframe increments having a first size, wherein the first software agent is configured to delete older timeframe increments of data as newer timeframe increments of data are acquired such that only a pre-determined number of timeframe increments of data are stored based on when the timeframe increments of data are acquired;
• wherein the processing unit is further configured to execute a second software agent configured to acquire data from each of a subset of the plurality of local sensors in timeframe increments having a second size;
• wherein the processing unit is further configured to:
• detect a pattern in the data acquired via the second software agent from the subset of the plurality of local sensors, the pattern indicating a traffic incident;
• in response to detecting a pattern indicating the traffic incident, aggregate all data acquired via the first software agent from a time when the pattern was detected until motion of the vehicle stops with the pre-determined number of timeframe increments of data stored at the time when the pattern was detected, wherein the first software agent is configured to not delete any of the pre-determined number of timeframe increments of data stored at the time when the pattern was detected in response to aggregating the data acquired via the first software agent from the time when the pattern was detected until motion of the vehicle stops;
• and
• output one or more recommendations related to the traffic incident to one or more users based on analysis of the aggregated data.

A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed by a processor, causes the processor to:

• acquire data, via a first software agent, from each of a plurality of local sensors located on a vehicle in timeframe increments having a first size;
• store only a pre-determined number of timeframe increments of data acquired via the first software agent based on when the timeframe increments of data are acquired, wherein older timeframe increments of data are replaced by newer timeframe increments;
• acquire data, via a second software agent, from each of a subset of the plurality of local sensors in timeframe increments having a second size;
• detect a pattern in the data acquired via the second software agent from the subset of the plurality of local sensors, the pattern indicating a traffic incident;
• in response to detecting a pattern indicating the traffic incident, aggregate the pre-determined number of timeframe increments of data stored at the time when the pattern was detected with data acquired via the first agent from a time when the pattern was detected until motion of the vehicle stops, wherein none of the pre-determined number of timeframe increments of data stored at the time when the pattern was detected are replaced by the data acquired via the first agent from the time when the pattern was detected until the motion of the vehicle stops;
• acquire data from one or more external sensors via a network connection from the time when the pattern was detected until motion of the vehicle stops, in response to detecting a pattern in the data acquired via the second software agent;
• aggregate the data acquired from the one or more external sources to the data acquired from the plurality of local sensors via the first software agent;
• determine a traffic incident type indicated by the pattern is a collision;
• collect data regarding one or more neighbor vehicles in response to determining that the traffic incident type is a collision;
• collect data from a traffic signal system in response to determining that the traffic incident type is a collision;
• embed weights into data inputs based on the determined traffic incident type;
• and
• output a different recommendation to each of a plurality of users based on a respective user type of each of the plurality of users and analysis of the weighted data inputs.