Dynamic rideshare service behavior based on past passenger experience data

Abstract

The present technology provides solutions for optimizing rideshare services, and more specifically for improving user rideshare itineraries using ride experience data. A process of the disclosed technology can include steps for collecting ride experience data from one or more sensors of an autonomous vehicle for a portion of a carpool ride traveled while a user is in the autonomous vehicle, evaluating the biometric data derived from the user, and determining, from the biometric data, that a facial expression of the user indicates that the user was unhappy during at least a portion of the carpool ride. In some aspects, the process can further include determining an optimal itinerary for the user based on the facial expression of the user. Systems and machine-readable media are also provided.

1 . (canceled) 
     
     
         2 . A computer-implemented method comprising:
 collecting ride experience data from one or more sensors of an autonomous vehicle for a portion of a carpool ride traveled while a user is in the autonomous vehicle, wherein the ride experience data includes biometric data;   evaluating the biometric data derived from the user, wherein the biometric data is collected from the one or more sensors of the autonomous vehicle;   determining, from the biometric data, that a facial expression of the user indicates that the user was unhappy during at least a portion of the carpool ride; and   determining an optimal itinerary for the user based on the facial expression of the user, wherein the optimal itinerary comprises a stop restriction specifying a maximum number of pick-up and drop-off stops for future carpool rides.   
     
     
         3 . The computer-implemented method of  claim 2 , further comprising:
 determining that the ride experience data indicates that the carpool ride included greater than an average number of pick up and drop-off stops for an average carpool ride of a fleet associated with a rideshare service.   
     
     
         4 . The computer-implemented method of  claim 3 , further comprising:
 restricting the autonomous vehicle from adding pickup or drop-offs to the carpool ride via the rideshare service.   
     
     
         5 . The computer-implemented method of  claim 2 , wherein the ride experience data is based on a number of accelerations above a predetermined threshold. 
     
     
         6 . The computer-implemented method of  claim 2 , wherein the ride experience data is based on a number of stops involving a deceleration above a predetermined threshold. 
     
     
         7 . The computer-implemented method of  claim 2 , wherein the optimal itinerary comprises providing a reduced fare on future carpool rides to users with at least one unhappy experience. 
     
     
         8 . The computer-implemented method of  claim 2 , wherein the optimal itinerary comprises prioritizing users with at least one former unhappy experience over users with no former unhappy experience. 
     
     
         9 . A computing system comprising:
 at least one storage including computer-readable instructions stored thereon; and   at least one processor configured to execute the computer-readable instructions which cause the computing system to:
 collect ride experience data from one or more sensors of an autonomous vehicle for a portion of a carpool ride traveled while a user is in the autonomous vehicle, wherein the ride experience data includes biometric data; 
 evaluate the biometric data derived from the user, wherein the biometric data is collected from the one or more sensors of the autonomous vehicle; 
 determine, from the biometric data, that a facial expression of the user indicates that the user was unhappy during at least a portion of the carpool ride; and 
 determine an optimal itinerary for the user based on the facial expression of the user, wherein the optimal itinerary comprises a stop restriction specifying a maximum number of pick-up and drop-off stops for future carpool rides. 
   
     
     
         10 . The computing system of  claim 9 , wherein the computer-readable instructions further cause the computing system to:
 determine that the ride experience data indicates that the carpool ride included greater than an average number of pick up and drop-off stops for an average carpool ride of a fleet associated with a rideshare service.   
     
     
         11 . The computing system of  claim 10 , wherein the computer-readable instructions further cause the computing system to:
 restrict the autonomous vehicle from adding pickup or drop-offs to the carpool ride via the rideshare service.   
     
     
         12 . The computing system of  claim 9 , wherein the ride experience data is based on a number of accelerations above a predefined threshold. 
     
     
         13 . The computing system of  claim 9 , wherein the ride experience data is based on a number of stops involving a deceleration above a predetermined threshold. 
     
     
         14 . The computing system of  claim 9 , wherein the optimal itinerary comprises providing a reduced fare on future carpool rides to users with at least one unhappy experience. 
     
     
         15 . The computing system of  claim 9 , wherein the optimal itinerary comprises prioritizing users with at least one former unhappy experience over users with no former unhappy experience. 
     
     
         16 . A non-transitory computer-readable storage medium comprising instructions therein, which when executed by one or more processors, cause the processors to perform operations comprising:
 collecting ride experience data from one or more sensors of an autonomous vehicle for a portion of a carpool ride traveled while a user is in the autonomous vehicle, wherein the ride experience data includes biometric data;   evaluating the biometric data derived from the user, wherein the biometric data is collected from the one or more sensors of the autonomous vehicle;   determining, from the biometric data, that a facial expression of the user indicates that the user was unhappy during at least a portion of the carpool ride; and   determining an optimal itinerary for the user based on the facial expression of the user, wherein the optimal itinerary comprises a stop restriction specifying a maximum number of pick-up and drop-off stops for future carpool rides.   
     
     
         17 . The non-transitory computer-readable storage medium of  claim 16 , wherein the operations further comprising:
 determining that the ride experience data indicates that the carpool ride included greater than an average number of pick up and drop-off stops for an average carpool ride of a fleet associated with a rideshare service.   
     
     
         18 . The non-transitory computer-readable storage medium of  claim 17 , wherein the operations further comprising:
 restricting the autonomous vehicle from adding pickup or drop-offs to the carpool ride via the rideshare service.   
     
     
         19 . The non-transitory computer-readable storage medium of  claim 16 , wherein the ride experience data is based on a number of accelerations above a predetermined threshold. 
     
     
         20 . The non-transitory computer-readable storage medium of  claim 16 , wherein the ride experience data is based on a number of stops involving a deceleration above a predetermined threshold. 
     
     
         21 . The non-transitory computer-readable storage medium of  claim 16 , wherein the optimal itinerary comprises prioritizing users with at least one former unhappy experience over users with no former unhappy experience.