Systems including one or more sensors, coupled to a vehicle, may detect sensor information and provide the sensor information to another computing device for processing. A system includes one or more sensors, coupled to a vehicle and configured to detect sensor information, and a computing device configured to communicate with one or more mobile sensors to receive the mobile sensor information, communicate with the one or more sensors to receive the sensor information, and analyze the sensor information and the mobile sensor information to identify one or more risk factors.

Aspects of the present disclosure include a navigation system and computer-implemented methods for detecting traffic disruption events based on an analysis of input component data obtained from navigation-enabled devices of vehicles near a particular location. Traffic disruption events are events such as accidents, construction road closures, police and speed traps, or road hazards that cause a decrease in the flow of traffic along a particular route and thus, added time delays for occupants of vehicles traveling along those routes. The navigation system scores the input component data associated with each vehicle and aggregates the scored input component data to obtain a frustration score associated with the vehicle. The navigation system may detect traffic disruption events based on a number of vehicles near a particular area having associated frustration scores above a certain threshold.

This document describes methods by which a system determines a pickup/drop-off zone (PDZ) to which a vehicle will navigate to perform a ride service request. The system will define a PDZ that is a geometric interval that is within a lane of a road at the requested destination of the ride service request by: (i) accessing map data that includes the geometric interval; (ii) using the vehicle's length and the road's speed limit at the destination to calculate a minimum allowable length for the PDZ; (iii) setting, start point and end point boundaries for the PDZ having an intervening distance that is equal to or greater than the minimum allowable length; and (iv) positioning the PDZ in the lane at or within a threshold distance from the requested destination. The system will then generate a path to guide the vehicle to the PDZ.

Some embodiments of the invention provide a novel prediction engine that (1) can formulate predictions about current or future destinations and/or routes to such destinations for a user, and (2) can relay information to the user about these predictions. In some embodiments, this engine includes a machine-learning engine that facilitates the formulation of predicted future destinations and/or future routes to destinations based on stored, user-specific data. The user-specific data is different in different embodiments. In some embodiments, the stored, user-specific data includes data about any combination of the following: (1) previous destinations traveled to by the user, (2) previous routes taken by the user, (3) locations of calendared events in the user’s calendar, (4) locations of events for which the user has electronic tickets, and (5) addresses parsed from recent e-mails and/or messages sent to the user. In some embodiments, the prediction engine only relies on user-specific data stored on the device on which this engine executes. Alternatively, in other embodiments, it relies only on user-specific data stored outside of the device by external devices/servers. In still other embodiments, the prediction engine relies on user-specific data stored both by the device and by other devices/servers.

A method for determining a risk boundary in response to the plurality of indications of hard braking events wherein the risk boundary is indicative of a plurality of speed flow pairs at which a risk of a hard braking event is below a threshold value, determining, at a road segment level, a set of speed flow pairs of average speed and vehicle count and a plurality of indications of hard braking events , determining a host vehicle speed, and performing at least one of reducing the host vehicle speed and increasing a host vehicle following distance in response to the host vehicle speed exceeding the risk boundary for the vehicle flow density.

A ride positioning service providing method includes: by service providing server, receiving starting position and destination along with call request from user terminal, receiving non-preference option for specific road type from driver terminals, determining each of the driver terminals as walking ride group or general ride group according to whether a road to which the starting position belongs is the non-preference option, determining the starting position as general ride point of the taxi, and one position selected from an area within a certain range based on the starting position as a walking ride point of the taxi, and requesting a call to the driver terminal forming at least one group among the walking ride group and the general ride group based on at least one ride point among the walking ride point and the general ride point based on weather information of a position of the user terminal.

A system comprises an autonomous vehicle (AV) and an operation server operably coupled with the AV. The operation server accesses environmental data associated with a road traveled by the AV. The environmental data is associated with a time window during which the AV is traveling along the road. The operation server compares the environmental data with map data that comprises expected road conditions ahead of the AV. The operation server determines whether the environmental data comprises an unexpected road condition that is not included in the map data. In response to determining that the environmental data comprises the unexpected road condition that is not included in the map data, the operation server determines a location coordinate of the unexpected road condition, and communicates a command to the AV to maneuver to avoid the unexpected road condition.

The described technology is generally directed towards generating a simulated virtual experience that represents predicted interaction of a user/vehicle with traffic in a traffic zone. A user who is considering entering a traffic zone (e.g., that charges a fee for usage) can request a simulated virtual experience of what is likely to occur if the user decides to enter. Based on the simulated virtual experience, which can be a graphical visualization in 3D, the user can make an informed decision as to whether to enter and pay, or not enter. User-specific data such as user preferences and other provided criterion can be used with respect to generating the simulated virtual experience. For current users about to enter the zone, current traffic data is used along with historical data in generating the simulated virtual experience.

Various technologies described herein pertain to autonomous vehicle consumption of real-time public transportation data to guide curb access and usage. An autonomous vehicle receives a trip request for a ride specifying a requested pullover location. The autonomous vehicle receives public transportation data specifying an expected arrival time of a public transportation vehicle at a reserved zone within proximity of the requested pullover location. The autonomous vehicle evaluates availability of the reserved zone during an expected occupancy time of the reserved zone by the autonomous vehicle based on the expected arrival time of the public transportation vehicle at the reserved zone. The autonomous vehicle selects an actual pullover location for the ride in the autonomous vehicle based on the availability of the reserved zone during the expected occupancy time. The autonomous vehicle stops at the actual pullover location for the ride in the autonomous vehicle.

A method for improving the ride comfort of a transportation vehicle including planning a first driving route by a navigation system; automatically detecting at least one road parameter of the first driving route by a sensor system of the transportation vehicle; automatically evaluating the first driving route in view of the ride comfort of the first driving route by taking into account the road parameter; and in response thereto using the first driving route or planning an alternative driving route.