# US 2019/0377352 A1 · Method and system for assisting an operator of an ego-vehicle in controlling the ego-vehicle by determining a future behavior and an associated trajectory for the ego-vehicle > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2019/0377352 A1 - Document ID: US20190377352A1 - Status: Published application - Kind: A1 - Application number: 16/433,403 - Filed: 2019-06-06 - Published: 2019-12-12 - Earliest claimed: 2018-06-06 - Assignees: Honda Research Institute Europe GmbH - Applicants: Honda Research Institute Europe GmbH - Inventors: Thomas WEIßWANGE; Sven REBHAN; Jens SCHMÜDDERICH - Web page: https://patentgrep.com/patent/US20190377352A1 ## CPC - B60W 60/00276: {for two or more other traffic participants} - G08G 1/167: {Driving aids for lane monitoring, lane changing, e.g. blind spot detection} - B60W 30/0956: {the prediction being responsive to traffic or environmental parameters} - B60W 60/0011: {involving control alternatives for a single driving scenario, e.g. planning several paths to avoid obstacles} - B60W 60/0027: {using trajectory prediction for other traffic participants} - B60W 2420/403: Image sensing, e.g. optical camera - B60W 2420/408: Radar; Laser, e.g. lidar - B60W 2420/54: Audio sensitive means, e.g. ultrasound - B60W 2520/10: Longitudinal speed - B60W 2554/4045: Intention, e.g. lane change or imminent movement - B60W 2554/406: Traffic density - B60W 2554/802: Longitudinal distance - B60W 2554/804: Relative longitudinal speed - B60W 2555/20: Ambient conditions, e.g. wind or rain - B60W 2555/60: Traffic rules, e.g. speed limits or right of way - B60W: CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT - G08G: TRAFFIC CONTROL SYSTEMS (guiding railway traffic, ensuring the safety of railway traffic B61L; arrangement of road signs or traffic signals E01F9/00; radar or analogous systems, sonar systems, lidar systems specially adapted for traffic control G01S13/91, G01S15/88, G01S17/88; {radar or analogous systems, sonar systems, lidar systems specially adapted for anti-collision purposes G01S13/93, G01S15/93, G01S17/93}) ## Abstract A method and vehicle for assisting in controlling an ego-vehicle determines a situation currently encountered by the ego-vehicle comprising the ego-vehicle and another vehicle. Probabilities of future behaviors of the other vehicle are computed based on the current situation. Potential future behaviors of the ego-vehicle are determined and probabilities of a various possible future situations are computed based on combinations of the predicted future behaviors of the other vehicle and the potential future behaviors of the ego-vehicle. Trajectories for associated behaviors are optimized for the ego-vehicle for some of these possible future situations and a trajectory is selected based a future situation probability. Since each trajectory is associated with one potential future behavior of the ego-vehicle, selection of a trajectory means a selection of a particular behavior. A control signal to output information to the driver about the selected trajectory or to control actuators of the ego-vehicle is generated. ## Claims ### Claim 1 A method for assisting an operator of an ego-vehicle in controlling the ego-vehicle by determining a future behavior and an associated trajectory for the ego-vehicle to be executed, comprising: determining a situation currently encountered by the ego-vehicle, the current situation comprising the ego-vehicle and at least one other vehicle; computing probabilities of future behavior of the at least one other vehicle based on the current situation for predicting future behavior of the at least one other vehicle; determine potential future behaviors of the ego-vehicle; compute probabilities of a plurality of future situations possibly evolving from the current situation based on combinations of future behaviors of the at least one other vehicle and the potential future behaviors of the ego-vehicle; optimize at least one trajectory for the ego-vehicle for at least one of the possible future situations; select a trajectory based at least on one future situation probability; and generate a control signal to inform the driver about the selected trajectory or to control actuators of the ego-vehicle so that the ego-vehicle follows the selected trajectory. ### Claim 2 (depends on 1) The method according to claim 1, wherein the computation of the probabilities of the future behaviors of the at least one other vehicle takes into account potential future changes of the behavior of its surrounding vehicles. ### Claim 3 (depends on 1) The method according to claim 1, wherein the computation of the probabilities of future behaviors of the at least one other vehicle is performed once with the assumption of each possible future behavior of the ego-vehicle. ### Claim 4 (depends on 2) The method according to claim 2, wherein the computation of the probabilities of the future behaviors of the at least one other vehicle taking account of potential future behaviors of its surrounding vehicles is done by changing the current situation for its surrounding vehicles an a way that simulates the execution of the possible behaviors by its surrounding vehicles. ### Claim 5 (depends on 1) The method according to claim 1, wherein the predicted behavior of the at least one other vehicle and the potential future behavior of the ego-vehicle is one of: lane change to the left, lane change to the right, driving straight, braking, accelerating. ### Claim 6 (depends on 1) The method according to claim 1, wherein each future situation that is constructed corresponds to a unique combination of future behaviors of the other vehicles and one of the potential future behaviors of the ego-vehicle. ### Claim 7 (depends on 1) The method according to claim 1, wherein for constructing relevant future situations, related future behaviors of other vehicles in the vicinity of the ego-vehicle are combined with each other and with potential future behaviors of the ego-vehicle. ### Claim 8 (depends on 6) The method according to claim 6, wherein only behaviors of the other vehicles or the ego-vehicle are considered for construction of the future situations, that are applicable in the current situation and that comply with applicable traffic rules. ### Claim 9 (depends on 1) The method according to claim 1, wherein for constructing relevant future situations, each potential behaviour of the ego-vehicle is combined only with predicted behaviors of other vehicles in the vicinity of the ego-vehicle and conditioned on the respective potential behavior of the ego-vehicle. ### Claim 10 (depends on 1) The method according to claim 1, wherein the probability for a future situation is computed by multiplying the probabilities or conditional probabilities of the associated future behaviors of every vehicle. ### Claim 11 (depends on 1) The method according to claim 1, wherein future situations that only differ in states of vehicles that do not influence the related ego-vehicle behavior are fused be further processed as one single future situation. ### Claim 12 (depends on 1) The method according to claim 1, wherein a parameter space of parameters defining possible trajectories which implement the situation-associated ego-vehicle behaviour is evaluated and a trajectory that results in minimum cost or maximum quality is selected as optimized trajectory. ### Claim 13 (depends on 12) The method according to claim 12, wherein the trajectories are represented as piecewise linear representations, polynomials of third or higher order, splines based on third order polynomials or higher, for example C2-splines, B-splines. ### Claim 14 (depends on 12) The method according to claim 12, wherein the cost of the ego-vehicle's trajectory is defined by a combination of cost-terms influenced by control points that represent parameters to be optimized. ### Claim 15 (depends on 1) The method according to claim 1, wherein the cost-terms take it least 1 of the following aspects at a given time or is combination of its values over the trajectory duration into account: headway to other vehicles with respect to a selected set-headway ego-vehicle velocity with respect to a selected set-speed maximum or minimum acceleration jerk, which is a derivative of acceleration with respect to time required reaction of other vehicles with respect to the ego-vehicle's trajectory timing of the lane-change. ### Claim 16 (depends on 1) The method according to claim 1, wherein the optimization of the trajectories is done only within predefined limits for the trajectory parameters. ### Claim 17 (depends on 1) The method according to claim 1, wherein the trajectories are optimized by determining values for control points which lead to minimum cost using an optimization algorithm, which preferably is a derivative-free gradient descent method. ### Claim 18 (depends on 1) The method according to claim 1, wherein the optimization process for determining an optimized trajectory is sequentially done for each situation according to a predefined order of the situations until a stop criterion is reached. ### Claim 19 (depends on 1) The method according to claim 1, wherein selection of a trajectory and a respective behaviour is based on at least two of: future situation probability, trajectory cost, traffic rules, driver preferences. ### Claim 20 (depends on 1) The method according to claim 1, wherein the control signal is output only if the selected trajectory and associated behavior has cost not exceeding a threshold or the selected trajectory and associated behaviour lie within given constraints. ### Claim 21 (depends on 1) A vehicle including at least one sensor for sensing an environment of the vehicle and a processor configured to carry out the method according to claim 1, wherein the control signal is output to a human machine interface for communicating the selected behaviour and associated trajectory to the vehicle operator or to one or more controllers of vehicle actuators to operate the vehicle to follow the selected trajectory.