A vehicle having one or more cameras, configured to record one or more images of a driver of the vehicle. The camera(s) can be configured to send biometric image data derived from the image(s). The vehicle can include a computing system configured to receive the biometric data and to determine a risk score of the driver based on the received biometric data and an AI technique, such as an ANN or a decision tree. The received biometric data or a derivative thereof can be input for the AI technique. The computing system can also be configured to transmit the risk score of the driver to the customer so that the customer can decide whether to book the vehicle for a ride.

A method of monitoring for circumvention of an ignition interlock system is described herein including detecting an electrical parameter associated with an electrical power state of a vehicle electrical system in a vehicle comprising an ignition interlock device that includes at least a relay device and a controller device electrically interconnected within the vehicle electrical system, measuring a rate of degradation associated with the electrical parameter of the vehicle electrical system, and comparing the electrical parameter to a threshold condition. The method further includes comparing the rate of degradation of the electrical parameter to a threshold rate. Depending on the rate of degradation, a violation state may be generated, a violation state may be reversed, a violation state may be maintained, a log entry may be generated, or more than one of these may occur.

Systems and methods for securing limited drivability of a vehicle by impaired drivers using blockchain are provided. The vehicle system uses blockchain to protect and disclose such vehicle deactivation, prevent false enabling/disabling of a vehicle, and saves this information to a shared ledger. A sensor system located on the vehicle, e.g., alcohol interlock sensors, interior sensors, and exterior sensors, may have access to this information along with fleet managers, OEM, and/or users. For example, when the alcohol interlock sensor is activated, it transmits a test request. Subsequently, the other sensors may identify the request and look for a known person inside or in the proximity of the vehicle. In a similar manner, whether the test has been conducted, as well as the results of the test may be verified by the other nodes, e.g., sensors/modules in the vehicle. Upon confirmation that the driver is impaired, the vehicle may be deactivated.

A method of providing safety in a level 3 autonomous vehicle by mounting a plurality of cameras in a vehicular cabin to detect edges; translating the edges into motions of a human or a biological entity; and monitoring safety conditions for the human or biological entity.

Systems and methods for improving vehicular safety are provided. According to certain aspects, an electronic device may receive and analyze image data depicting an individual located within a vehicle. The electronic device may also access certain data related to a condition of the individual, and may accordingly determine whether the individual is fit to operate the vehicle. If the individual is unfit to operate the vehicle, the electronic device may alter autonomous operation of the vehicle.

This patent application discloses methods and systems for alerting computerized motor-vehicles about predicted accidents. In an example method, a motor vehicle alerts another motor vehicle about a predicted accident, even though that accident is between the alerting car and a third motor vehicle—for example, the alert is transmitted by non-visual electromagnetic (EM) radiation. When an adjacent motor vehicle receives such accident alert and determines it might itself be hit, it will react so as to minimize its chances of being hit or at least to minimize the damage if it is being hit. Optionally, one or more of the motor vehicles has an onboard device for measuring a blood-alcohol level of a human driver thereof. The measured blood-alcohol level may be used to compute a probability of an occurrence of an accident and/or may be included in one or more of the transmitted accident alerts.

A system in a vehicle can have a camera and/or a sensor. Such a camera can be configured to record a visual feature of a user in the vehicle and send data derived from the visual feature. Such a sensor can be configured to sense a non-visual feature of the user in the vehicle and send data derived from the non-visual feature. The system can have a computing system configured to receive such data from the camera and the sensor. The computing device can also be configured to determine a state of the user based on the received data derived from visual and non-visual features, as well as an AI system. The computing device can also be configured to enable or disable a function of the vehicle based at least partially on the state of the user, which the AI system can infer from the received data.

A road information exchange system includes a plurality of Guided Autonomous Information Network (GAIN) units (102) installed on a road. Each GAIN unit (102) communicates with another GAIN unit (102) of the plurality of GAIN units (102) to divide the road into virtual lanes by formation of microgrids and further communicates with a vehicle passing through the road information exchange system (100).

Exhaustive driving analytical methods, systems, are apparatuses are described. The methods, systems, are apparatuses relate to utilizing partially available data associated with driver and/or driving behaviors to determine safety factors, identify times to react to events, and contextual information regarding the events. The methods, systems, and apparatuses described herein may determine, based on a systematic model, reactions and reaction times, compare the vehicle behavior (or lack thereof) to the modeled reactions and reaction times, and determine safety factors and instructions based on the comparison.

Approaches for an advanced AI-assisted vehicle can utilize an extensive suite of sensors inside and outside the vehicle, providing information to a computing platform running one or more neural networks. The neural networks can perform functions such as facial recognition, eye tracking, gesture recognition, head position, and gaze tracking to monitor the condition and safety of the driver and passengers. The system also identifies and tracks body pose and signals of people inside and outside the vehicle to understand their intent and actions. The system can track driver gaze to identify objects the driver might not see, such as cross-traffic and approaching cyclists. The system can provide notification of potential hazards, advice, and warnings. The system can also take corrective action, which may include controlling one or more vehicle subsystems, or when necessary, autonomously controlling the entire vehicle. The system can work with vehicle systems for enhanced analytics and recommendations.