A method for controlling a vehicle travelling along a route is provided. The method includes obtaining a first value of a balance parameter, indicative of a balance between a cost for operating the vehicle along at least a part of the route, and a time of arrival at a position along the route, establishing, in dependence on the first balance parameter value, a plurality of desired position and time correlations for the travel of the vehicle along at least a part of the route, when the vehicle travels along the route, determining a progress deviation comprising a deviation, for a point in time, of an actual position of the vehicle from a desired position according to the desired position and time correlations, or a deviation, for a position of the vehicle, of an actual point in time from a desired point in time according to the desired position and time correlations, when the vehicle travels along the route, obtaining a second balance parameter value, different from the first balance parameter value, the second balance parameter value being dependent on the progress deviation, and controlling the vehicle in dependence on the second balance parameter value.

Embodiments of the disclosed systems and methods provide systems and techniques for improving reference route and/or trajectory information for autonomous vehicles that may allow for better operation and/or deployment. In certain embodiments, various optimization techniques may be employed for generating higher quality reference route and/or trajectory information based on initial reference route and/or trajectory information captured by an autonomous vehicle. Various embodiments of the disclosed systems and methods may improve reference route and/or trajectory information through processes that may involve editing and/or otherwise modifying initial route and/or trajectory information, smoothing path curves associated with initial reference route and/or trajectory information, modifying initial route and/or trajectory information based on vehicle-specific dynamics and/or parameters, and/or modifying velocities for improved passenger comfort.

A computer-implemented method for controlling a vehicle system of a host vehicle merging into a lane. The method includes determining an actual distance between the host vehicle and the one or more remote vehicles. The actual distance is a longitudinal distance between the host vehicle and the one or more remote vehicles. The method includes determining a safe distance for merging into the lane based on a relative position of the host vehicle to the one or more remote vehicles, a speed of the host vehicle, and a speed of the one or more remote vehicles. The safe distance is a second longitudinal distance between the host vehicle and the one or more remote vehicles. The method includes controlling the vehicle system of the host vehicle to assist a merge maneuver by the host vehicle according to the actual distance and the safe distance.

Among other things, techniques are described for expressive vehicle systems. These techniques may include obtaining, with at least one processor, data associated with an environment, the environment comprising a vehicle and at least one object; determining an expressive maneuver including a deceleration of the vehicle such that the vehicle stops at least a first distance away from the at least one object and the vehicle reaches a peak deceleration when the vehicle is a second distance away from the at least one object; generating data associated with control of the vehicle based on the deceleration associated with the expressive maneuver; and transmitting the data associated with the control of the vehicle to cause the vehicle to decelerate based on the deceleration associated with the expressive maneuver.

A traveling control apparatus is mounted on a vehicle that includes an electric motor and an internal combustion engine as power sources. The traveling control apparatus includes an electronic control unit configured to create a speed profile obtained by predicting speed of the vehicle at each time, derive, based on at least the speed profile, a coefficient profile that is a coefficient at each time used at the time of predicting an amount of regenerative energy recoverable by regenerative braking of the electric motor, approximate the speed profile with a predetermined approximation model and estimate a predicted amount of regenerative energy based on an approximation result and the coefficient profile, and determine the power source used for traveling based on the predicted amount of regenerative energy.

A driving assistance apparatus includes an estimator and a controller. The estimator estimates a first estimated vehicle speed and a second estimated vehicle speed when there are a first deceleration target and a second deceleration target in a course ahead of a vehicle, and when a driver of the vehicle releases an accelerator pedal. Wherein the first estimated vehicle speed is an estimated vehicle speed of the vehicle at a first target position corresponding to the first deceleration target, and the second estimated vehicle speed is an estimated vehicle speed of the vehicle at a second target position corresponding to the second deceleration target. The controller controls the vehicle to automatically decelerate toward the second target position when the first estimated vehicle speed is greater than a first predetermined value, and when the second estimated vehicle speed is less than a second predetermined value.

A device for controlling travel of a vehicle includes: a sensor that acquires information on a surrounding region of the vehicle, and a controller that generates a speed profile based on the information on the surrounding region of the vehicle, calculates an average acceleration in the speed profile based on a current vehicle speed and a vehicle speed at a predetermined time point, and calculates a required acceleration at a time point at which a difference between the speed profile and the average acceleration is greatest, and performs travel control based on at least one of the average acceleration or the required acceleration. The device allows a longitudinal control to be performed based on the speed profile generated by the vehicle, thereby improving an accuracy of autonomous driving.

A system for providing a speed profile of a self-driving vehicle includes a vehicle driving information prediction device, and a speed profile generation device, wherein the vehicle driving prediction device includes a navigation unit configured to set information on a drive route and a target travel time, a 3D map information provision unit configured to search for gradient information of the drive route set by the navigation unit, and a vehicle driving information provision unit, and wherein the speed profile generation device includes a vehicle energy consumption calculation unit configured to calculate energy consumption at a current speed of the vehicle when the vehicle runs along the set drive route, and a speed profile calculation unit configured to calculate a distance-based target speed profile by executing a dynamic programming algorithm.

Various embodiments of the invention enable an ADV to dynamically adjust its behaviors to emulate behaviors of a vehicle operated by a human driver when the ADV encounters an obstacle. A dynamic cost function can be used to collect real-time values of a set of parameters, and use the real-time values to constantly adjust a preferred safety distance where the ADV can be stopped ahead of the obstacle. An method includes determining a first distance to the obstacle in response to detecting an obstacle ahead of the ADV; and for each of a number of iterations, collecting a real-time value for each of a set of parameters, determining an offset to the first distance using the real-time value for each of the set of parameters, calculating a second distance based on the first distance and the offset, and controlling the ADV in view of the second distance using an expected value of each of the set of parameters, such that the ADV can stop at a point having the second distance to the obstacle.

This application relates to a travel speed control method, an apparatus, a computing device, and a storage medium. The method includes: determining a sampling interval matching a current traveling speed; selecting, starting from a current location, sampling points on an expected traveling route according to the sampling interval; determining a target curvature according to curvatures of the expected traveling route at the respective sampling points; determining, according to the target curvature, a speed limit of traveling on the expected traveling route; and controlling a traveling speed according to the speed limit.