A hybrid deterministic override to cloud based probabilistic advanced driver assistance systems. Under default driving conditions, an ego vehicle is controlled by a probabilistic controller in a cloud. An overall gap between the ego vehicle and a leading vehicle is divided into an emergency collision gap and a driver specified gap. The vehicle sensors monitor the overall gap. When the gap between the ego vehicle and the leading vehicle is less than or equal to the emergency collision gap, a deterministic controller of the ego vehicle overrides the cloud based probabilistic controller to control the braking and acceleration of the ego vehicle.

A vehicle is operable in a first operating mode in which the vehicle travels autonomously inside the traffic lane based on a detection of lane markings of a traffic lane and in a second operating mode in which the vehicle autonomously follows a vehicle driving in front while ignoring lane markings, and a method of its operation includes operating the vehicle in a first of the two operating modes, detecting a vehicle environment, and switching from the first operating mode to the other of the two operating modes as a function of the detected vehicle environment. A device can execute the method and a computer program can be executed by a device for performing the method.

Methods and systems for determining risk associated with operation of autonomous vehicles using autonomous communication are provided. According to certain aspects, autonomous operation features associated with a vehicle may be determined, including features associated with autonomous communication between vehicles or with infrastructure. This information may be used to determine risk levels for a plurality of features, which may be based upon test data regarding the features or actual loss data. Expected use levels and autonomous communication levels may further be determined and used with the risk levels to determine a total risk level associated with operation of the vehicle. The autonomous communication levels may indicate the types of communications, the levels of communication with other vehicles or infrastructure, or the frequency of autonomous communication. The total risk level may be used to determine or adjust aspects of an insurance policy associated with the vehicle.

Among other things, a vehicle having autonomous driving capabilities is operated in a mixed driving mode.

Systems and methods for controlling an autonomous vehicle are provided. In one example embodiment, a computer-implemented method includes receiving data indicative of an operating mode of the vehicle, wherein the vehicle is configured to operate in a plurality of operating modes. The method includes determining one or more response characteristics of the vehicle based at least in part on the operating mode of the vehicle, each response characteristic indicating how the vehicle responds to a potential collision. The method includes controlling the vehicle based at least in part on the one or more response characteristics.

A method provides driver assistance in a motor vehicle in particularly dense and confusing traffic conditions in the low-speed range. It is possible to adjust the distance in dense traffic so that it is not too great whilst at the same time ensuring that the driver does not always have to vary the position of the accelerator pedal. The accelerator is controlled in accordance with the distance and thus the speed or accelerator is automatically throttled as the distance decreases.

A safety system for a baggage tractor is provided that addresses the problems associated with tipping over or flipping of vehicles due to excessive speed around turns. Additionally, the safety system for a baggage tractor is provided that is fully integrated to ease replacement of a combustion engine in a baggage tractors with an electric motor and automated safety control system.

A distributed safety lockout system for a vehicle, such as a recreational vehicle (RV), that includes a plurality of networked devices communicatively coupled via a communications network, and that is configured to implement a method for controlling an electromechanical operation of an electromechanical device based on a safety lockout condition determined through use of a consensus protocol in which a safety lockout status is agreed upon by the networked devices. The safety lockout status may be escalated by a safety lockout condition detection device that detects a safety lockout condition, such as movement of the RV. The safety lockout status may be de-escalated through a network contention mode of the consensus protocol in which each of the networked devices agree to de-escalate the safety lockout status.

An autonomous driving controller includes: a processor to collect driving data when a vehicle is traveling and calculate a steering override reference value, which is a criterion of determining an override mode, based on the collected driving data; and a storage to store the collected driving data and a set of instructions executed by the processor to calculate the steering override reference value. In particular, the processor controls autonomous driving by varying the steering override reference value based on the collected driving data or information regarding a driver of the vehicle.

This driving assistance device includes a target acceleration correcting unit configured as follows: if there was input, from a coupling detection unit, of detection results indicating that a trailer has been coupled, the target acceleration correcting unit outputs a target acceleration, output from an ACC unit, as-is to a drive system; and if there was input of detection results indicating that a trailer (2) has not been coupled, the target acceleration correcting unit corrects to a smaller value the target acceleration, output from the ACC unit, and outputs said corrected target acceleration to the drive system.