Systems and methods for using risk profiles based on previously detected vehicle events to quantify performance of vehicle operators

1. A system configured for recommending route changes to vehicle operators based on risk profiles of a fleet of vehicles that are operated by the vehicle operators, wherein the fleet of vehicles is networked through an electronic communication network, wherein the risk profiles characterize values representing likelihoods of occurrences of vehicle events, the system comprising:

the fleet of vehicles, wherein individual vehicles in the fleet are configured to detect vehicle events, and wherein the individual vehicles in the fleet are further configured to electronically transfer vehicle event information regarding previously detected vehicle events, through the electronic communication network, to the system; and

one or more hardware processors configured by machine-readable instructions to:

obtain a first risk profile, a second risk profile, and vehicle event characterization information, wherein the first risk profile is specific to a certain context for detecting the vehicle events, wherein the certain context includes locations where the vehicle events have been detected, wherein the first risk profile characterizes a first set of values representing likelihoods of occurrences of vehicle events matching the certain context, wherein the second risk profile is specific to a set of vehicle operators, wherein the second risk profile characterizes a second set of values representing likelihoods of occurrences of vehicle events involving the set of vehicle operators, wherein the vehicle event characterization information characterizes one or more types of vehicle events to be used in determining performance levels by particular vehicle operators, and wherein the first set of values and the second set of values are based on the vehicle event information for the previously detected vehicle events;

receive, from a particular vehicle through the electronic communication network, particular vehicle event information for particular vehicle events that have been detected by the particular vehicle, wherein the particular vehicle event information includes information representing routes traversed by the particular vehicle, wherein the particular vehicle has a particular vehicle type and is operated by a particular vehicle operator, wherein the particular vehicle event information includes particular locations of the particular vehicle events, and wherein the particular vehicle event information further includes particular types of the particular vehicle events;

estimate, based on at least the second risk profile, expected occurrences of expected vehicle events during traversal of a particular route by the particular vehicle;

determine aggregated metrics that quantify performance levels of the set of vehicle operators, wherein determination is based on the estimated expected occurrences of the expected vehicle events;

determine one or more metrics that quantify a performance level of the particular vehicle operator for the traversal of the particular route by the particular vehicle, wherein the determination of the one or more metrics is based at least in part on the received particular vehicle event information;

perform a comparison of the one or more metrics for the particular vehicle operator with the aggregated metrics that quantify the performance levels of the set of vehicle operators;

select a suitable route from a set of routes for the particular vehicle operator based on the comparison, wherein the performance level of the particular vehicle operator for the traversal of the particular route is expected to be outperformed by the particular vehicle operator traversing the suitable route;

determine a recommendation based on the comparison, wherein the recommendation includes changing the particular route of the particular vehicle to the suitable route as selected; and

present the recommendation via a user interface to a user of the system, wherein the recommendation includes traversing the suitable route.

2. The system of claim 1 , wherein the first set of values and the second set of values are based on the vehicle event information, wherein the previously detected vehicle events have been detected by the fleet of vehicles, wherein the vehicle event information includes the certain context for the previously detected vehicle events and the operators for the previously detected vehicle events.

3. The system of claim 1 , wherein the certain context for detecting vehicle events further includes one or more of local weather, heading of one or more vehicles, and/or traffic conditions.

4. The system of claim 1 , wherein the certain context for detecting vehicle events further includes one or more of objects on roadways during detection of vehicle events, other incidents within a particular timeframe of detection of vehicle events, time of day, lane information, and/or presence of autonomously operated vehicles within a particular proximity.

5. The system of claim 1 , wherein the particular vehicle operator is an autonomous driving algorithm.

6. The system of claim 1 , wherein the one or more hardware processors are further configured by machine-readable instructions to:

present, via the user interface, information regarding the driving scenario, wherein the information reflects advice on improving the one or more metrics for the particular vehicle operator.

7. The system of claim 1 , wherein the set of vehicle operators include a first operator and a second operator, wherein the first operator is a human and the second operator is an autonomous driving algorithm;

wherein the one or more hardware processors are further configured by machine-readable instructions to determine a combined value representing a likelihood of occurrences of vehicles events involving a team of vehicle operators cooperatively operating the same vehicle, wherein the team includes the first vehicle operator and the second vehicle operator; and

wherein the one or more hardware processors are further configured by machine-readable instructions to present, via the user interface, a second recommendation regarding suitability of the team for cooperative operation of the same vehicle, wherein cooperative driving includes a first driver acting as the primary operator, and a second driver acting as the back-up operator that can take over driving responsibilities from the primary operator, and wherein the second recommendation is based on the combined value.

8. The system of claim 7 , wherein the one or more hardware processors are further configured by machine-readable instructions to:

determine when the second driver should take over driving responsibilities from the first driver, wherein the determination is based on a first value representing a first expectation of a particular type of vehicle event occurring if the first driver continues driving a current route, as compared to a second value representing a second expectation of the particular type of vehicle event occurring if the second driver drives the current route.

9. A method for recommending route changes to vehicle operators based on risk profiles for of a fleet of vehicles that are operated by the vehicle operators, wherein the fleet of vehicles is networked through an electronic communication network, wherein the risk profiles characterize values representing likelihoods of occurrences of vehicle events, the method comprising:

detecting, by individual vehicles in the fleet of vehicles, vehicle events;

electronically transferring, by the individual vehicles in the fleet of vehicles, through the electronic communication network, vehicle event information regarding previously detected vehicle events;

obtaining a first risk profile, a second risk profile, and vehicle event characterization information, wherein the first risk profile is specific to a certain context for detecting the vehicle events, wherein the certain context includes locations where the vehicle events have been detected, wherein the first risk profile characterizes a first set of values representing likelihoods of occurrences of vehicle events matching the certain context, wherein the second risk profile is specific to a set of vehicle operators, wherein the second risk profile characterizes a second set of values representing likelihoods of occurrences of vehicle events involving the set of vehicle operators, wherein the vehicle event characterization information characterizes one or more types of vehicle events to be used in determining performance levels by particular vehicle operators, and wherein the first set of values and the second set of values are based on the vehicle event information for the previously detected vehicle events;

receiving, from a particular vehicle through the electronic communication network, particular vehicle event information for particular vehicle events that have been detected by the particular vehicle, wherein the particular vehicle event information includes information representing routes traversed by the particular vehicle, wherein the particular vehicle has a particular vehicle type and is operated by a particular vehicle operator, wherein the particular vehicle event information includes particular locations of the particular vehicle events, and wherein the particular vehicle event information further includes particular types of the particular vehicle events;

estimating, based on at least the second risk profile, expected occurrences of expected vehicle events during traversal of a particular route by the particular vehicle;

determining aggregated metrics that quantify performance levels of the set of vehicle operators, wherein determination is based on the estimated expected occurrences of the expected vehicle events;

determining one or more metrics that quantify a performance level of the particular vehicle operator for the traversal of the particular route by the particular vehicle, wherein the determination of the one or more metrics is based at least in part on the received particular vehicle event information;

performing an analysis of the one or more metrics for the particular vehicle operator for a driving scenario that contributes disproportionately to a difference between the one or more metrics for the particular vehicle operator and the aggregated metrics;

performing a comparison of the one or more metrics for the particular vehicle operator with the aggregated metrics that quantify the performance levels of the set of vehicle operators;

selecting a suitable route from a set of routes for the particular vehicle operator based on the analysis and the comparison;

determining a recommendation based on the analysis and the comparison, wherein the recommendation includes changing the particular route of the particular vehicle to the suitable route as selected; and

presenting the recommendation via a user interface to a user, wherein the recommendation includes traversing the suitable route.

10. The method of claim 9 , wherein the first set of values and the second set of values are based on the vehicle event information, wherein the previously detected vehicle events have been detected by the fleet of vehicles, wherein the vehicle event information includes the certain context for the previously detected vehicle events and the operators for the previously detected vehicle events.

11. The method of claim 9 , wherein the certain context for detecting vehicle events further includes one or more of local weather, heading of one or more vehicles, and/or traffic conditions.

12. The method of claim 9 , wherein the certain context for detecting vehicle events further includes one or more of objects on roadways during detection of vehicle events, other incidents within a particular timeframe of detection of vehicle events, time of day, lane information, and/or presence of autonomously operated vehicles within a particular proximity.

13. The method of claim 9 , wherein the particular vehicle operator is an autonomous driving algorithm.

14. The method of claim 9 , further comprising:

presenting, via the user interface, information regarding the driving scenario, wherein the information reflects advice on improving the one or more metrics for the particular vehicle operator.

15. The method of claim 9 , wherein the set of vehicle operators include a first operator and a second operator, wherein the first operator is a human and the second operator is an autonomous driving algorithm, the method further comprising:

determining a combined value representing a likelihood of occurrences of vehicles events involving a team of vehicle operators cooperatively operating the same vehicle, wherein the team includes the first vehicle operator and the second vehicle operator; and

presenting, via the user interface, a second recommendation regarding suitability of the team for cooperative operation of the same vehicle, wherein cooperative driving includes a first driver acting as the primary operator, and a second driver acting as the back-up operator that can take over driving responsibilities from the primary operator, and wherein the second recommendation is based on the combined value.

16. The method of claim 15 , further comprising:

determining when the second driver should take over driving responsibilities from the first driver, wherein the determination is based on a first value representing a first expectation of a particular type of vehicle event occurring if the first driver continues driving a current route, as compared to a second value representing a second expectation of the particular type of vehicle event occurring if the second driver drives the current route.

17. A system configured for recommending changes in driving responsibilities of a team of a first vehicle operator and a second vehicle operator for cooperative operation of a first vehicle based on risk profiles of a fleet of vehicles that are operated by vehicle operators, wherein the fleet of vehicles is networked through an electronic communication network, wherein the risk profiles characterize values representing likelihoods of occurrences of vehicle events, the system comprising:

the fleet of vehicles, wherein individual vehicles in the fleet are configured to detect vehicle events, and wherein the individual vehicles in the fleet are further configured to electronically transfer vehicle event information regarding previously detected vehicle events, through the electronic communication network, to the system; and

one or more hardware processors configured by machine-readable instructions to:

obtain a first risk profile, a second risk profile, and vehicle event characterization information, wherein the first risk profile is specific to a certain context for detecting the vehicle events, wherein the certain context includes locations where the vehicle events have been detected, wherein the first risk profile characterizes a first set of values representing likelihoods of occurrences of vehicle events matching the certain context, wherein the second risk profile is specific to a set of vehicle operators including the first vehicle operator and the second vehicle operator, wherein the second risk profile characterizes a second set of values representing likelihoods of occurrences of vehicle events involving the set of vehicle operators, wherein the vehicle event characterization information characterizes one or more types of vehicle events to be used in determining performance levels by particular vehicle operators, and wherein the first set of values and the second set of values are based on the vehicle event information for the previously detected vehicle events;

receive, from the first vehicle through the electronic communication network, particular vehicle event information for particular vehicle events that have been detected by the first vehicle, wherein the particular vehicle event information includes information representing routes traversed by the first vehicle, wherein the first vehicle is operated by the team of the first vehicle operator and the second vehicle operator such that the first vehicle operator acts as primary operator and the second vehicle operator acts as back-up operator that can take over the driving responsibilities from the primary operator, wherein the particular vehicle event information includes particular locations of the particular vehicle events, and wherein the particular vehicle event information further includes particular types of the particular vehicle events;

estimate, based on at least the second risk profile, expected occurrences of expected vehicle events during traversal of a particular route by the first vehicle with the first vehicle operator acting as the primary operator and the second vehicle operator acting as the back-up operator that can take over the driving responsibilities from the primary operator;

determine aggregated metrics that quantify performance levels of the set of vehicle operators, wherein determination is based on the estimated expected occurrences of the expected vehicle events;

determine one or more metrics that quantify one or more performance levels of the team for the traversal of the particular route by the first vehicle, wherein the determination of the one or more metrics is based at least in part on the received particular vehicle event information;

perform a comparison of the one or more metrics for the team with the aggregated metrics that quantify the performance levels of the set of vehicle operators;

determine a recommendation that recommends the second vehicle operator taking over the driving responsibilities from the first vehicle operator, wherein the recommendation is based on the comparison; and

present the recommendation via a user interface to a user of the system.