A vehicular driver assistance system includes a front camera module (FCM) disposed at a vehicle. The system, responsive to processing captured image data, generates FCM lane information including information regarding a traffic lane the vehicle is currently traveling along. An e-Horizon module (EHM) generates EHM lane information including information regarding the traffic lane the vehicle is currently traveling along. The vehicular driver assistance system determines an FCM correlation using the FCM lane information and sensor data captured by at least one exterior sensor. The vehicular driver assistance system determines an EHM correlation using the EHM lane information and the sensor data captured by the at least one exterior sensor. Responsive to determining the FCM correlation and the EHM correlation, the system controls lateral movement of the vehicle based on one selected from the group consisting of (i) the FCM lane information and (ii) the EHM lane information.

A driving assistance system and a driving assistance method are provided. The driving assistance system includes a physiological information sensing system, an external physical symptom detection system, and a processing device. The physiological information sensing system is configured to sense physiological information of a driver. The external physical symptom detection system is configured to detect an external physical symptom of the driver. The processing device is coupled to the physiological information sensing system and the external physical symptom detection system. When the physiological information of the driver and the external physical symptom of the driver are abnormal, the processing device initiates an emergency procedure.

Methods and systems are provided for using energy harvesting modules as a means for providing energy to power an electrical load and/or as a means for monitoring an operational state of a component or components to which the energy harvesting module is coupled. In one example, a method includes, via a controller, monitoring an actual amount of energy generated by an energy harvesting module attached to a mounting structure that is used to secure a torque-supplying machine to a frame, comparing the actual amount to an expected amount, and indicating degradation of the mounting structure and/or the torque-supplying machine based on the comparing. In this way, the energy harvesting modules may both power electrical loads and simultaneously serve as a monitor for component degradation.

Mappings of keys to actions can automate various vehicle systems. Some automations can provide lane departure warnings. Keys for lane departure mappings can specify vibration patterns expected when a vehicle drives over lane delineators. These vibration-based mappings can include keys with vibration patterns, e.g., defining vibration frequencies or vibration locations. Keys for emergency light mappings can be based on conditions such as (1) the vehicle being on the road, stopped, not in traffic, and not at a stop signal; (2) components of the vehicle having failed; or (3) weather conditions.

The disclosure includes embodiments for early detection of abnormal driving behavior. A method according to some embodiments includes sensing, by a sensor set of an ego vehicle, a remote vehicle to generate sensor data describing driving behavior of the remote vehicle. The method includes comparing the sensor data to a set of criteria for abnormal driving behavior. The method includes determining that a subset of the set of criteria are described by the sensor data. The subset satisfies a threshold for early detection of abnormal driving behavior. For example, detecting the subset triggers the determination that abnormal driving behavior is detected. The method includes determining that the remote vehicle is engaged in abnormal driving behavior based on satisfaction of threshold. In some embodiments, an abnormal driving behavior is one which satisfies a threshold for abnormality or matches a pattern of an identified abnormal driving behavior.

A method for the geometric representation of a vehicle area (1) of a vehicle for the purpose of collision detection, wherein the vehicle area (1) has a boundary (2), comprising the method steps of performing a medial axis transformation of the vehicle area (1) to generate a vehicle area skeleton (4) and performing a point classification of points of the vehicle area skeleton (4) to determine front corner region points (5, 6) and rear corner region points (7, 8), and a front wheelbase point (9) and a rear wheelbase point (10), and also performing a circle decomposition of the vehicle area (1), wherein each circle of the circle decomposition has a maximum area exceedance value (17).

A system may comprise one or more processors, and a memory storing instructions that, when executed by the one or more processors, causing the system to perform receiving, from a first sensor coupled to a front part of a vehicle, a first set of sensor data that include data of a first edge of a body part, or from a second sensor coupled to the front part of the vehicle, a second set of sensor data that include data of a second edge of the body part. The system may perform calculating, based on the first or second set of the sensor data, location of the first edge or the second edge of the body part relative to the front part, and determining whether the relative location of the first edge or the second edge is within an expected location range. The system may perform sending a notification that driving adjustment of the vehicle is required if the relative location is outside the expected location range.

A road surface state determination apparatus includes a plurality of tire-side devices each of which detects vibration applied to corresponding tire and produces road surface data indicative of a road surface state based on data of the vibration, and a vehicle-body-side system that determines the road surface state based on the road surface data.

A method for augmenting transport services using event detection is provided. The method includes collection of first sensor data generated by various sensors associated with a plurality of vehicles. The first sensor data includes sensor outputs that indicate a plurality of rash driving events. The sensor outputs are augmented based on angular rotation to obtain augmented sensor outputs. A prediction model is trained based on the augmented sensor outputs. Target sensor data associated with a target vehicle is provided as input to the trained prediction model, and based on an output of the trained prediction model an occurrence of a rash driving event is detected in real-time or near real-time. Based on a count of rash driving events associated with the target driver within a cumulative driving distance, a driver score of the target driver is determined.

The present disclosure includes a system, method, and device related to data collection and communication related to after-market and external vehicle systems, such as towing systems, cargo carrying systems, trailer breakaway systems, brake systems, braking control systems, and the like. Data is sensed, processed, shared, and further leveraged throughout the discrete components of the system, and possibly via internet and other communications' links, to effect various beneficial actions with minimal driver/user interaction or intervention. In the same manner, data from the system may be used for diagnostic reasons, safety controls, and other purposes.