A safe-to-proceed system (10) for operating an automated vehicle proximate to an intersection (14) includes an intersection-detector (18), a vehicle-detector (20), and a controller (24). The intersection-detector (18) is suitable for use on a host-vehicle (12). The intersection-detector (18) is used to determine when a host-vehicle (12) is proximate to an intersection (14). The vehicle-detector (20) is also suitable for use on the host-vehicle (12). The vehicle-detector (20) is used to estimate a stopping-distance (22) of an other-vehicle (16) approaching the intersection (14). The controller (24) is in communication with the intersection-detector (18) and the vehicle-detector (20). The controller (24) is configured to prevent the host-vehicle (12) from entering the intersection (14) when the stopping-distance (22) indicates that the other-vehicle (16) will enter the intersection (14) before stopping.

An automatic driving control plan creator creates a plan of an automatic driving section where a subject vehicle is automatically driven, and a plan of a driving switching preparation section for switching the subject vehicle from automatic driving to manual driving. A driving load calculator predicts, for each point of the driving switching preparation section, a driving load applied to a driver when the driver manually drives the subject vehicle. A driving switching permission determiner extracts, from the driving switching preparation section, a switching-inhibited section that is a section where switching from automatic driving to manual driving is not permitted, on the basis of the predicted driving load at each point. A driving switching preparation section compensator changes a start point of the driving switching preparation section so as to lengthen the driving switching preparation section in accordance with the length of the switching-inhibited section.

In one example a system for emotional adaptive driving policies for automated driving vehicles, comprising a first plurality of sensors to detect environmental information relating to at least one passenger in a vehicle and a controller communicatively coupled to the plurality of sensors and comprising processing circuitry, to receive the environmental information from the first plurality of sensors, determine, from the environmental information, an emotional state of the at least one passenger, and implement a driving policy based at least in part on the emotional state of the at least one passenger. Other examples may be described.

A system for operating an autonomous vehicle includes a passenger-detector and a controller-circuit. The passenger-detector is operable to determine a passenger-count of passengers present in a host-vehicle. The controller-circuit is in communication with the passenger-detector and vehicle-controls of the host-vehicle. The controller-circuit is configured to operate the host-vehicle in an autonomous-mode and in accordance with a parameter. The parameter is set to an empty-value when passenger-count is equal to zero, and the parameter is set to an occupied-value different from the empty-value when the passenger count is greater than zero.

Interaction-aware decision making may include training a first agent based on a first policy gradient, training a first critic based on a first loss function to learn goals in a single-agent environment using a Markov decision process, training a number N of agents based on the first policy gradient, training a second policy gradient and a second critic based on the first loss function and a second loss function to learn goals in a multi-agent environment using a Markov game to instantiate a second agent neural network, and generating an interaction-aware decision making network policy based on the first agent neural network and the second agent neural network. The N number of agents may be associated with a driver type indicative of a level of cooperation. When a collision occurs, a negative reward or penalty may be assigned to each agent involved based on a lane priority level of respective agents.

A method for operating a driver assistance system of a vehicle, in which interventions activated by the driver assistance system in a travel mode of the vehicle are at least partially suspended for a predetermined time window when an override intent of a driver of the vehicle is recognized.

A control device is provided for a human-powered vehicle. The control device is basically provided with a controller. The controller is configured to be connected to at least one component of the human-powered vehicle such that the controller is free from executing normal activation of the at least one component in accordance to a first input in a first mode. The controller is configured to operate at least one of an actuator and an indicator in accordance to the first input in a second mode. The first mode is switched into the second mode in accordance to a second input different from the first input.

The present application discloses a method for controlling cruise of a vehicle. The method includes: acquiring a pre-established three-dimensional trajectory map of the vehicle from a starting point to a destination; acquiring current positioning information of the vehicle; intercepting a target trajectory at a preset distance currently ahead of the vehicle from the three-dimensional trajectory map according to the current positioning information; acquiring a target point from the target trajectory according to the current positioning information; acquiring a wheelbase and a current speed of the vehicle, and calculating an angle that front wheels of the vehicle are required to rotate, according to the target point, the current positioning information, the wheelbase, and the current speed; controlling a movement of the vehicle according to the angle.

A motion prediction unit that predicts a motion of a mobile object on the basis of sensor information; a range prediction unit that predicts a virtual obstacle range in which a virtual obstacle is present on the basis of motion prediction information regarding the motion of the mobile object predicted by the motion prediction unit; and a map generation unit that generates a dynamic map reflecting the virtual obstacle range on the basis of information regarding the virtual obstacle range predicted by the range prediction unit.

An autonomous driving method includes: recognizing a target vehicle; determining a first slope of a host vehicle and a second slope of the target vehicle; correcting a result of the recognizing of the target vehicle based on the first slope and the second slope; and controlling the host vehicle based on the corrected result of the recognizing of the target vehicle.