The present disclosure relates to a method and system for integrated path planning and path tracking control of an autonomous vehicle. The method includes: obtaining five input control variables and eleven system state variables of an autonomous vehicle at current time; constructing a vehicle path planning-tracking integrated state model according to the obtained variables at the current time; enveloping external contours of two autonomous vehicles using elliptical envelope curves to determine elliptical vehicle envelope curves of the two autonomous vehicles, respectively; determining time to collision (TTC) between the vehicles according to elliptical vehicle envelope curves and vehicle driving states; establishing an objective function of a model prediction controller (MPC) according to the model; and solving the objective function based on the TTC, and determining input control variables to the MPC at the next time. Autonomous vehicle collision avoidance can be achieved according to the present disclosure.

The technology relates to predicting that an object is going to enter into a trajectory of a vehicle. This may include receiving sensor data identifying a first location of the object in an environment of the vehicle at a first point in time and receiving sensor data identifying a second location of the object in the environment at a second point in time. In addition, a boundary of the trajectory is determined by defining at least a two-dimensional area through which the vehicle is expected to travel in the future. A first distance between the boundary and the first location and a second distance between the trajectory and the second location are determined. The first distance and the second distance are used to determine that the object is going to enter into the trajectory at a future point in time.

The vehicle control device sets a region including a stationary object on a road, calculates a passing position at which a host vehicle and an oncoming vehicle pass each other in accordance with a velocity of the host vehicle and a position and a velocity of the oncoming vehicle, calculates a first score that is a larger value as the velocity of the oncoming vehicle is greater, calculates a second score that is a larger value as an acceleration rate of the oncoming vehicle is greater, integrates the first score with the second score so as to calculate an integration score, and causes the host vehicle to decelerate when the integration score is greater than or equal to a predetermined value or causing the host vehicle to keep the velocity or accelerate when the integration score is smaller than the predetermined value.

Dynamic braking capability of a combination vehicle including a tractor and at least one trailer is provided based on a distribution of the load carried by the combination vehicle. Load distribution is determined directly using load sensors disposed at wheel pairs of the tractor and trailer(s) or indirectly by using a load sensor located at the drive axle of the tractor together with engine torque and vehicle speed signals for determining gross vehicle mass. A database having sub-databases therein each storing stopping distance calculation results for a corresponding combination vehicle type e.g. 5-axle single or 8-axle double, is indexed by using the determined load distributions for providing the dynamic braking capability based on the vehicle type and its load distribution. The database may also be indexed using Axle Load Allocation Factor that is calculated based on a mathematical combination of drive, steering, and gross trailer axle loading.

Method, apparatus, and computer-readable medium for performing a braking operation of a vehicle when an object is detected in front of the vehicle. The method includes acquiring at least one image of an external environment of the vehicle, determining a road condition of a road of the external environment of the vehicle based on the acquired at least one image, obtaining, based on the determined road condition and from memory, a braking table of one or more braking tables including distances and corresponding vehicle speeds at which the braking operation is performed, acquiring a speed of the vehicle and a distance between a preceding object and the vehicle, comparing the acquired speed of the vehicle and the acquired distance between the preceding object and the vehicle to the braking table, and sending, based on the comparison, an instruction to perform the braking operation of the vehicle.

In one embodiment, a vehicle merge control system generates sensor data that indicate a detected vehicle in an environment of the ego vehicle, identifies a conflict based at least in part on the sensor data indicating that the detected vehicle and the ego vehicle are traveling: 1) in adjacent lanes that will merge into a single lane, and 2) at respective speeds that will result in the detected vehicle entering within a threshold range of the ego vehicle, determines, upon identification of the conflict, merge position assignments for the ego vehicle and the detected vehicle based at least in part on a game theory cost function applied to game theory actions that result in the merge position assignments exclusively being either a lead vehicle or a follower vehicle, and outputs an acceleration rate to achieve the merge position assignment for the ego vehicle.

A travel assistance method and a travel assistance device for a vehicle is capable of avoiding any risk that may arise. The method includes obtaining a risk potential of an object detected by the vehicle, associating the risk potential of the object with an encounter location at which the object is encountered, accumulating the risk potential at the encounter location, and using the accumulated risk potential to obtain a primary estimated risk potential of the object predicted to be encountered at the encounter location. The primary estimated risk potential is lower than the risk potential obtained when detecting the object. The method further includes obtaining a secondary estimated risk potential using a predicted travel movement of another vehicle that avoids a risk due to the primary estimated risk potential, and when traveling at the encounter location again, autonomously controlling travel of the vehicle using the secondary estimated risk potential.

An automatic reverse driving controller includes a control unit. The control unit includes a traveling information input unit, a traveling information storage unit, an automatic reverse traveling instruction input unit, and a processing unit. The traveling information input unit inputs information on a traveling trajectory of the vehicle and a road surface condition.

The traveling information storage unit stores the inputted information on the traveling trajectory and the road surface condition. The automatic reverse traveling instruction input unit receives an input of an instruction to switch from traveling by a driving operation of a driver of the vehicle to automatic reverse traveling by the control unit. The processing unit corrects, in response to the input of the instruction, a traveling trajectory of an outward route on the basis of the road surface condition to determine a traveling route for a return route, and control reverse traveling of the vehicle.

A vehicle control system and method includes obtaining a size of a vehicle system, identifying locations of different portions of the vehicle system, and determining one or more of a) whether the vehicle system is disposed within or across an intersection of routes or b) a predicted time of arrival at which the vehicle system will be disposed within or across the intersection based on the size of the vehicle system and the locations of the different portions of the vehicle system.

A vehicle drive assist device includes an ECU. The ECU determines whether an object recognition condition meets a predetermined condition, which means that a driver of the vehicle recognizes the presence of an object ahead of the vehicle, based on the state of an operation of an operator of the vehicle by the driver. The ECU executes deceleration control when the collision index value is smaller than a second index value smaller than a first index value and the ECU determines the object recognition condition does not meet the predetermined condition. The ECU does not execute the deceleration control when the ECU determines the object recognition condition meets the predetermined condition even when the collision index value is smaller than the second index value.