A system includes a pattern recognizing module that identifies a pattern based on at least one of: (i) a movement of a driver of a vehicle, (ii) an object in front of the vehicle, (iii) a status of the vehicle, and (iv) an action of the vehicle. The pattern corresponds to a pattern response. A safety module compares the pattern response to a safe maneuver database. The pattern response is classified as safe in response to the pattern response matching at least one safe pattern response of the safe maneuver database. A pattern integration module integrates the pattern and the pattern response into a pattern database in response to the pattern response matching the at least one safe pattern response of the safe maneuver database. A vehicle control module performs the pattern response in response to the pattern recognizing module identifying the pattern.

System, methods, and other embodiments described herein relate to transitioning a vehicle from an autonomous to a manual driving mode. One embodiment analyzes data from one or more vehicle sensors to detect, at a current vehicle position, features in a first detection region and a second detection region ahead of the vehicle; determines, for each of one or more hypothetical vehicle positions, which features detected at the current position, if any, lie within the first detection region at that hypothetical position; identifies, among the one or more hypothetical positions, at least one localization-failure position at which localization of the vehicle will fail due to insufficient features being detected within the first detection region at the at least one localization-failure position; and initiates a transition from the autonomous driving mode to the manual driving mode based, at least in part, on the at least one localization-failure position.

The technology relates to determining general weather conditions affecting the roadway around a vehicle, and how such conditions may impact driving and route planning for the vehicle when operating in an autonomous mode. For instance, the on-board sensor system may detect whether the road is generally icy as opposed to a small ice patch on a specific portion of the road surface. The system may also evaluate specific driving actions taken by the vehicle and/or other nearby vehicles. Based on such information, the vehicle's control system is able to use the resultant information to select an appropriate braking level or braking strategy. As a result, the system can detect and respond to different levels of adverse weather conditions. The on-board computer system may share road condition information with nearby vehicles and with remote assistance, so that it may be employed with broader fleet planning operations.

An autonomous driving apparatus and method, in which the apparatus includes a sensor unit detecting a surrounding vehicle around an ego vehicle that autonomously travels, an output unit, a memory storing map information, and a processor controlling the autonomous driving of the ego vehicle based on the map information. The processor is configured to generate an actual driving trajectory and expected driving trajectory of the surrounding vehicle based on driving information of the surrounding vehicle detected by the sensor unit and the map information, determine whether a driving mode of the surrounding vehicle is an autonomous driving mode and an autonomous driving risk of the ego vehicle based on a trajectory error between the actual driving trajectory and expected driving trajectory of the surrounding vehicle, and output a warning to a passenger through the output unit at a level corresponding to the determined autonomous driving risk.

A driving assist device includes a first sensor, a second sensor, and a control device. The control device does not execute an inter-vehicle distance control under a predetermined first condition upon determination that at least one preceding object is detected based on the output of one of the first sensor and the second sensor without being detected based on the output of the other of the first and second sensors; and an environment of a non-detection sensor that is the other of the first and second sensors satisfies a first requirement for determination of a reliability of the output of the non-detection sensor; and the control device executes the inter-vehicle distance control under a predetermined second condition upon determination that the environment of the non-detection sensor satisfies a second requirement for determination of the reliability of the output of the non-detection sensor.

The present technology relates to a signal processing apparatus, a signal processing method, and a program that enable more appropriate control. The signal processing apparatus includes: a safety determination unit configured to determine safety of a preceding vehicle on a basis of sensor-related information related to a sensor provided in the preceding vehicle, the sensor being relevant to a safety function; and a control signal generation unit configured to generate, on a basis of a result of the determination of the safety, a control signal for controlling a host vehicle. The present technology can be applied to vehicles.

A mobility device that can accommodate speed sensitive steering, adaptive speed control, a wide weight range of users, an abrupt change in weight, traction control, active stabilization that can affect the acceleration range of the mobility device and minimize back falls, and enhanced redundancy that can affect the reliability and safety of the mobility device.

An in-vehicle life detection system and detection method thereof are provided. The system includes a control unit, an electromagnetic wave detection module, and a warning module. The method includes following steps: vehicle condition identifying step, life form detecting step, and warning step. Upon receiving an engine off signal and a driver absence signal, the control unit emits a detection activation signal, activating the electromagnetic wave detection module to emit an electromagnetic wave for detecting a life form. When the life form is detected, the warning module sends a warning signal, indicating that the life form is left in the vehicle when the vehicle is in the engine off status with the doors closed. Thus, the tragedy of a life form remaining inside the vehicle incapable of calling for help is avoided.

A warning zone system and method is disclosed. The warning zone system can comprise an object detection system, a zone configuration system, and an electronic data processor. The object detection system is arranged on a work vehicle and is configured to detect and classify one or more object obstructions located at a worksite. The zone configuration system is configured to associate position data with the one or more object obstructions and generate object models of the object obstructions based on the associated position data. The electronic data processor is communicatively coupled to each of the object detection system and the zone configuration system and is configured to generate and associate warning zones with each of the object models for display on a user display in near real-time.

An autonomous driving apparatus including a sensor unit, a memory, and a processor. The processor is configured to extract one or more valid measurement values within the validation gate of an estimate of the location of a target object, generated based on a measurement value of the location, among one or more measurement values output by the sensor unit, to form a track of the target object by taking into consideration a probability that each of the extracted valid measurement values corresponds to a measurement value of the location of the target object at a current timing, to track the target object using the track, and to extract the valid measurement values by adjusting the size of the validation gate based on time period during which the tracking of the target object is maintained and surrounding environment information of an ego vehicle being autonomously driven.