A braking system of an industrial vehicle includes an accumulator accumulating hydraulic oil, a hydraulic oil cooler cooling the hydraulic oil, an electromagnetic switch valve switching between an oil channel for the accumulator that allows supplying the hydraulic oil from a hydraulic pump to the accumulator and an oil channel for the hydraulic cooler that allows supplying the hydraulic oil from the hydraulic pump to the hydraulic oil cooler, and a controller controlling the electromagnetic switch valve to switch from the oil channel for the hydraulic cooler to the oil channel for the accumulator with timing of an increase after a drop in an engine speed when a cargo-handling operation is detected while an oil is at a setting pressure value or less and while the engine speed is at a setting engine speed or less.

Vehicles can be operated according to an artificial intelligence model contained in an on-board processor. The AI model can analyze sensor data, such as visible or infrared images of traffic, and determine when a collision is possible, whether it has become imminent, and whether the collision is avoidable or unavoidable using sequences of accelerations, braking, and steering. The AI model can also select the most appropriate sequence of actions from a large plurality of calculated sequences to avoid the collision if avoidable, and to minimize the harm if unavoidable. The AI model can also cause a processor to actuate linkages connected to the throttle (or electric power control), brakes (or regenerative braking), and steering to implement the selected sequence of actions. Thus the collision can be avoided or mitigated by an ADAS system or a fully autonomous vehicle.

Disclosed are systems and methods for autonomous vehicles and vehicles with automatic driver-assistance systems (ADAS) to automatically detect an imminent collision, determine whether the collision is avoidable or unavoidable, and plot a course minimizing the hazard using an artificial intelligence (AI) model. For example, a collision is avoidable if the vehicle can avoid it by steering, braking, and/or accelerating in a particular sequence. The AI model finds the best sequence for collision avoidance, and if that is not possible, it finds the best sequence for minimizing the harm. The harm is based on an estimated number of fatalities, injuries, and property damage predicted to be caused in the collision. The AI-based situation analysis and sequence selection are directly applicable to human-driven vehicles with an emergency-intervention ADAS system, as well as fully autonomous vehicles. With fast electronic reflexes and multi-sensor situation awareness, the AI model can save lives on the highway.

Human drivers generally cannot plan a collision evasion maneuver in the brief interval before impact, other than simply slamming on the brakes and hoping for the best. Often the collision could have been avoided by swerving or other sequence of actions. Therefore, improved collision avoidance and mitigation procedures are disclosed, based on a well-trained artificial intelligence (AI) model that takes over the accelerator, brake, and steering in an emergency. With fast electronic reflexes and AI-based computational power, the AI model can find a more effective avoidance maneuver, or at least an action that would minimize the harm (for example, by swerving to miss the passenger compartment). The AI model can then implement the sequence instantly, without fear or hesitation. The resultfewer collisions and less fatality on our highways.

Among other things, a command is received expressing an objective for operation of a vehicle within a denominated travel segment of a planned travel route. The objective spans a time series of (for example, is expressed at a higher or more abstract level than) control inputs that are to be delivered to one or more of the brake, accelerator, steering, or other operational actuator of the vehicle. The command is expressed to cause operation of the vehicle along a selected man-made travel structure of the denominated travel segment. A feasible manner of operation of the vehicle is determined to effect the command. A succession of control inputs is generated to one or more of the brake, accelerator, steering or other operational actuator of the vehicle in accordance with the determined feasible manner of operation.

A first vehicle in traffic can use machine learning and artificial intelligence to detect an imminent collision with a second vehicle or other object. A well-trained AI algorithm can select a sequence of actions (braking, swerving, or acceleratingdepending on the specific kinetics) to avoid the collision if possible, and to reduce or minimize the harm if unavoidable. With proper training, the AI model may also infer the intent and future actions of the second vehicle, as well as potential interference of other traffic agents. A good algorithm can also infer the intent of the driver of the first vehicle, for example based on prior driving habits. The AI algorithm may be implemented in a processor on the subject vehicle, potentially in communication with another processor at a fixed site such as a local access point or a central supercomputer. With super-fast AI solutions, lives will be saved!

An autonomous or semi-autonomous vehicle can detect an imminent collision according to sensor data and responsively select an action or a sequence of actions to avoid the collision if avoidable, and to reduce or minimize the harm of the collision if unavoidable. An artificial intelligence model may be used to process the sensor data, detect the imminent collision, and select the collision avoidance action or actions, or the harm-reduction or harm-minimization action or actions. For example, when the collision is considered unavoidable, the vehicle may apply the brakes to reduce the vehicle's speed and therefore, the severity of the impact. When the collision is considered avoidable, the vehicle may automatically apply steering to avoid the potential collision, such as when the vehicle is departing a lane and may collide with a vehicle traveling in the same or opposite direction.

Among other things, a command is received expressing an objective for operation of a vehicle within a denominated travel segment of a planned travel route. The objective spans a time series of (for example, is expressed at a higher or more abstract level than) control inputs that are to be delivered to one or more of the brake, accelerator, steering, or other operational actuator of the vehicle. The command is expressed to cause operation of the vehicle along a selected man-made travel structure of the denominated travel segment. A feasible manner of operation of the vehicle is determined to effect the command. A succession of control inputs is generated to one or more of the brake, accelerator, steering or other operational actuator of the vehicle in accordance with the determined feasible manner of operation.

A system and method to avoid collisions on highways, and to minimize the fatalities, injury, and damage when a collision is unavoidable. The system includes sensor means to detect other vehicles, and computing means to evaluate when a collision is imminent and to determine whether the collision is avoidable. If the collision is avoidable by a sequence of controlled accelerations and decelerations and steering, the system implements that sequence of actions automatically. If the collision is unavoidable, a different sequence is implemented to minimize the overall harm of the unavoidable collision. The system further includes indirect mitigation steps such as flashing the brake lights automatically. An optional post-collision strategy is implemented to prevent secondary collisions, particularly if the driver is incapacitated. Adjustment means enable the driver to set the type and timing of automatic interventions.

A computer is programmed to receive a message from a second vehicle indicating a fault in a second vehicle component. The computer is further programmed to modify an area of control of the first vehicle to include a location of the second vehicle, and to provide a control instruction to the second vehicle.