Systems and methods use cameras to provide autonomous navigation features. In one implementation, a method for navigating a user vehicle may include acquiring, using at least one image capture device, a plurality of images of an area in a vicinity of the user vehicle; determining from the plurality of images a first lane constraint on a first side of the user vehicle and a second lane constraint on a second side of the user vehicle opposite to the first side of the user vehicle; enabling the user vehicle to pass a target vehicle if the target vehicle is determined to be in a lane different from the lane in which the user vehicle is traveling; and causing the user vehicle to abort the pass before completion of the pass, if the target vehicle is determined to be entering the lane in which the user vehicle is traveling.

Among other things, techniques are described for receiving, from at least one sensor of a vehicle, sensor data associated with a surface along a path to be traveled by a vehicle; using a surface classifier to determine a classification of the surface based on the sensor data; determining, based on the classification of the surface, drivability properties of the surface; planning, based on the drivability properties of the surface, a behavior of the vehicle when driving near the surface or on the surface; and controlling the vehicle based on the planned behavior.

A racing coach device stores a first path of travel along a racetrack over a first time period and a second path of travel along the racetrack over a second time period. The racing coach device identifies, for each of a plurality of geolocations along the racetrack, one of the first path of travel or the second path of travel that is associated with a shorter duration of time over which the user traversed a segment of the path of travel associated with each of the plurality of geolocations. The device determines an optimal path of travel along the racetrack based on the identified first and second path of travel for each segment of the path of travel at each of the plurality of geolocations that results in a calculated lap time to traverse the racetrack that is less than the first time period and the second time period.

A racing coach device stores a first path of travel along a racetrack over a first time period and a second path of travel along the racetrack over a second time period. The racing coach device identifies, for each of a plurality of geolocations along the racetrack, one of the first path of travel or the second path of travel that is associated with a shorter duration of time over which the user traversed a segment of the path of travel associated with each of the plurality of geolocations. The device determines an optimal path of travel along the racetrack based on the identified first and second path of travel for each segment of the path of travel at each of the plurality of geolocations that results in a calculated lap time to traverse the racetrack that is less than the first time period and the second time period.

An information processing device (20) includes a route acquisition unit (202) and an automatic driving section determination unit (204). The route acquisition unit (202) acquires route information indicating a moving route of a mobile body. The automatic driving section determination unit (204) acquires adaptation coefficients for a plurality of sections included in the moving route indicated by the route information, with reference to an adaptation coefficient storage unit (206) that stores automatic driving adaptation coefficients set for the respective sections. Further, the automatic driving section determination unit (204) determines the automatic driving sections of the mobile body in the moving route, based on the acquired adaptation coefficients.

A computer-implemented method of adaptively controlling an autonomous operation of a vehicle is provided. The method includes steps of (a) in a critic network in a computing system configured to autonomously control the vehicle, determining, using samples of passively collected data and a state cost, an estimated average cost, and an approximated cost-to-go function that produces a minimum value for a cost-to-go of the vehicle when applied by an actor network; and (b) in an actor network in the computing system and operatively coupled to the critic network, determining a control input to apply to the vehicle that produces the minimum value for the cost-to-go, wherein the actor network is configured to determine the control input by estimating a noise level using the average cost, a cost-to-go determined from the approximated cost-to-go function, a control dynamics for a current state of the vehicle, and the passively collected data.

Aspects of the disclosure relate to distributing vehicles to perform scouting. This may involve receiving a request for a scouting objective for a vehicle, and in response, identifying a set of scouting objectives that the vehicle is eligible to visit. Each scouting objective of the set is associated with one or more scouting quests, and each scouting quest is associated with a plurality of scouting objectives. For each given scouting objective in the set of scouting objectives, an overall weight may be determined using combined weights for the given scouting objective and any scouting quests with which the given scouting objective is associated. One or more scouting objectives of the set of scouting objectives may be selected using the determined overall weights. The one or more selected scouting objectives may be provided to the vehicle.

In some examples, a controller receives information of a route of a vehicle, and selects a first parameter set from among a plurality of parameter sets based on the route of the vehicle, the plurality of parameter sets corresponding to different conditions of usage of the vehicle, where each parameter set of the plurality of parameter sets includes one or more parameters that control adjustment of one or more respective adjustable elements of the vehicle. The controller causes application of the first parameter set to control a setting of the one or more adjustable elements of the vehicle.

A vehicle configured to operate in an autonomous mode can obtain sensor data from one or more sensors observing one or more aspects of an environment of the vehicle. At least one aspect of the environment of the vehicle that is not observed by the one or more sensors could be inferred based on the sensor data. The vehicle could be controlled in the autonomous mode based on the at least one inferred aspect of the environment of the vehicle.

A road surface evaluation apparatus includes a microprocessor configured to perform: acquiring driving information of each of vehicles, including a position and an acceleration of each of the vehicles while traveling, and a map information including road information on a road where the vehicles travel; evaluating a surface roughness of the road based on acquired accelerations of the vehicles; estimates a surface change location where the surface roughness has changed, based on a difference between a first road surface information including the evaluated surface roughness evaluated based on the acceleration of the vehicles acquired within a past predetermined period and a second road surface information including the evaluated surface roughness based on the acceleration of the vehicles acquired later than the past predetermined period; and outputting a road surface change information including the estimation result, in association with the road information.