Techniques for performing a sensor calibration using sequential data is disclosed. An example method includes receiving, from a first camera located on a vehicle, a first image comprising at least a portion of a road comprising lane markers, where the first image is obtained by the camera at a first time; obtaining a calculated value of a position of an inertial measurement (IM) device at the first time; obtaining an optimized first extrinsic matrix of the first camera by adjusting a function of a first actual pixel location of a location of a lane marker in the first image and an expected pixel location of the location of the lane marker; and performing autonomous operation of the vehicle using the optimized first extrinsic matrix of the first camera when the vehicle is operated on another road or at another time.

A roadmanship system comprises a computational device and a vehicle comprising a plurality of sensors and a vehicle control system in communication with the computational device and the plurality of sensors. The computational device can be configured to: (i) receive driving data from a group of vehicles; (ii) calculate a regression curve based on the driving data; (iii) calculate a threshold value of an engineering parameter based on the regression curve and a predetermined roadmanship level; and (iv) output the threshold value to the vehicle control system. The vehicle control system can be configured to: (a) receive the threshold value from the computational device; (b) receive operational information associated with at least one of the vehicle and a driving environment surrounding the vehicle from the plurality of sensors; and (c) cause the vehicle to perform a vehicle maneuver based on the threshold value and the operational information.

A method of determining a drivable space trajectory of an ego vehicle is described. The method includes determining a set of vehicle trajectories corresponding to a same semantic driving maneuver during motion planning of the ego vehicle. The method also includes identifying the drivable space trajectory to perform the same semantic driving maneuver. The method further includes performing a vehicle control action to maneuver the ego vehicle along the drivable space trajectory.

To provide a vehicle control system that is capable of planning a trajectory that can ensure more visibility and enables safe traveling when an invisible range of a sensor exists.

A vehicle control system that plans a target trajectory of a vehicle based on recognition information from an external environment sensor, the vehicle control system including a recognizing unit that recognizes an object at a periphery of the vehicle based on the recognition information; and a trajectory planning unit that plans the target trajectory such that an actual detection range of the external environment sensor becomes wide when the recognizing unit recognizes the object.

A laser transceiver system, a LiDAR, and an autonomous driving apparatus are provided. The laser transceiver system is applied to a LiDAR, including an emission module and a plurality of receiving modules corresponding to the emission module. The emission module is configured to emit an outgoing laser; the receiving module is configured to receive an echo laser; and the echo laser is a laser returning after the outgoing laser is reflected by an object in a detection region.

A route generation device includes: an autonomous route generator configured to generate, based on surrounding information around an own vehicle detected by a vehicle-mounted detector, an expected autonomous route along which the own vehicle is to travel; a map route acquirer configured to acquire an expected map route along which the own vehicle is to travel based on map data; and an integrated route generator configured to generate an integrated route using the autonomous route and the map route.

A matching system that matches a first vehicle requiring substitution when being at least either loaded into or unloaded from a parking place and a remote driver driving the first vehicle as a substitute through remote operation includes a terminal and a server. The terminal transmits substitution request information to the server. The server that has received the request information transmits waiting time information to the terminal. The terminal notifies a user or a staff of the received waiting time information, accepts a waiting time information approval or additional fee payment instructions, and settles the additional fee through cooperation with the server, upon receiving the payment instructions. The server changes the turn of the first vehicle in a queue for the remote operation service such that the first vehicle is prioritized more than a second vehicle that has not paid the additional fee, upon completing the additional fee settlement.

Aspects of the disclosure provide for generating distributions for hypothetical or potentially occluded objects. For instance, a location for which to generate one or more distributions may be identified. Observations of road users by perception systems of a plurality of autonomous vehicles may be accessed. Each of these observations may identify a characteristic of one of the road users. A distribution of the characteristic for the location may be determined based on the observations. The distribution may be provided to one or more autonomous vehicles in order to enable the one or more autonomous vehicles to use the distribution to generate a characteristic for a hypothetical occluded road user and to respond to the hypothetical occluded road user.

Provided are systems and methods for controlling a vehicle based on a map that designed using a factor graph. Because the map is designed using a factor graph, positions of the road can be modified in real-time while operating the vehicle. In one example, the method may include storing a map which is associated with a factor graph of variable nodes representing a plurality of constraints that define positions of lane lines in a road and factor nodes between the variable nodes on the factor graph which define positioning constraints amongst the variable nodes, receiving an indication from the road using a sensor of a vehicle, updating positions of the variable nodes based on the indication and an estimated location of the vehicle within the map, and issue commands capable of controlling a steering operation of the vehicle based on the updated positions of the factor nodes.

A device and a method for controlling autonomous driving control a speed of an autonomous vehicle before downhill travel. The device and method calculate a travel resistance of an autonomous vehicle on a travel-intended-route, including a downhill route, a main braking pressure required to travel at a constant speed, and a brake temperature based on braking. The device and method determine whether to reduce the main braking pressure based on the calculated brake temperature and calculates a decreased amount of the main braking pressure and an increased amount of a speed of the autonomous vehicle based on the decreased amount of the main braking pressure on the travel-intended-route when determining to reduce the main braking pressure. The device and method limit a maximum speed of the autonomous vehicle before entering the travel-intended-route based on the increased speed amount.