A robotic cart platform with a navigation and movement system that integrates into a conventional utility cart to provide both manual and autonomous modes of operation. The platform includes a drive unit with drive wheels replacing the front wheels of the cart. The drive unit has motors, encoders, a processor and a microcontroller. The system has a work environment mapping sensor and a cabled array of proximity and weight sensors, lights, control panel, battery and on/off, “GO” and emergency stop buttons secured throughout the cart. The encoders obtain drive shaft rotation data that the microcontroller periodically sends to the processor. When in autonomous mode, the system provides navigation, movement and location tracking with or without wireless connection to a server. Stored destinations are set using its location tracking to autonomously navigate the cart. When in manual mode, battery power is off, and back-up power is supplied to the encoders and microcontroller, which continue to obtain shaft rotation data. When in autonomous mode, the shaft rotation data obtained during manual mode is used to determine the present cart location.

A rollover alarming system, a rollover risk prediction method, and a rollover alarming method. An axle housing strain measurement unit measures strain values on both sides of an axle housing of a vehicle body. A roll angle measurement unit measures a roll angle of the vehicle body. A collection control unit is configured to collect the strain values on both sides of the axle housing of the vehicle body and the roll angle of the vehicle body, calculate a strain difference between the strain values according to the strain values on both sides of the axle housing of the vehicle body, and output a corresponding alarm control signal according to the strain difference between both sides of the axle housing of the vehicle body and the roll angle of the vehicle body. An alarm unit is configured to output a corresponding alarm signal according to the received alarm control signal.

A grip force sensing and shape-changing steering wheel configured to serve as an intuitive means of communication between a human driver and automatic driving system or driver assist system.

Provided is a travel evaluation method of making an evaluation related to travel of a vehicle capable of traveling in a leaning position, the method including: obtaining a tire force which is an external force exerted on a wheel of the vehicle from a ground surface; and deriving an evaluation index related to travel of the vehicle. The evaluation index includes a positive evaluation index as a rating of a positive evaluation related to travel of the vehicle. In deriving the evaluation index, the positive evaluation index is set higher as the tire force increases, and the evaluation index is corrected based on an influential parameter other than the tire force.

Respectively a rider of the autonomous scooter may select a manual drive mode to drive without any assistance, or the rider may control the autonomous scooter remotely by a smartphone when riding or not aboard via a smartphone APP whereby the rider may engage a user interface system providing virtual driving control settings linked with an autonomous drive system to control the autonomous scooter, or the rider can manually control the autonomous scooter. Primarily elements of the autonomous scooter may comprise a platform defined by a front end and a rear end, a deck section to place the rider's feet thereon, and having a base supporting a steering column. Accordingly the steering column is rotatably connected by a motorized wheel adapter configured to turn a suspension fork arrangement containing at least one motorized wheel thus steering and balance control of the autonomous scooter, or the steering column is connected to a truck arrangement containing two motorized wheels, whereby the two motorized wheels provide balance and differential propulsion for steering the autonomous scooter. The motorized wheel adapter and the motorized wheels are systematically controlled by an autonomous drive system adapted to control the autonomous scooter during autonomous drive mode setting.

A smart driver safety system for a vehicle is described. The system includes a drowsy driver detector, an attention diversion monitor, an automatic mirror adjustment subsystem, and a plurality of actuators. The drowsy driver detector determines a head position of the driver and detects an eye position of the driver's eyes. When the driver's eyes are closed, the drowsy driver detector determines a time duration of an eye closure and compares the time duration to a drowsiness threshold. When the eye closure exceeds the drowsiness threshold, the drowsy driver detector generates a drowsiness alert signal. The attention diversion monitor detects an attention diversion based on the eye position and the eye closure and generates an attention diversion alert signal. The automatic mirror adjustment subsystem adjusts a side mirror of the vehicle based on the eye position and the head position.

The present invention is directed to a passenger alerting device. The passenger alerting device includes a weight sensor configured for placement on a passenger seat. The device further includes an alarm panel. The alarm panel is in communication with the weight sensor in such a manner that an audible alarm will become energized in the event that the passenger vehicle is placed in park while a passenger may have been left behind. The device is useful for detecting the presence of passengers, particularly young students, and alerting to their presence so they will not be left behind.

A rollover alarming system, a rollover risk prediction method, and a rollover alarming method. An axle housing strain measurement unit measures strain values on both sides of an axle housing of a vehicle body. A roll angle measurement unit measures a roll angle of the vehicle body. A collection control unit is configured to collect the strain values on both sides of the axle housing of the vehicle body and the roll angle of the vehicle body, calculate a strain difference between the strain values according to the strain values on both sides of the axle housing of the vehicle body, and output a corresponding alarm control signal according to the strain difference between both sides of the axle housing of the vehicle body and the roll angle of the vehicle body. An alarm unit is configured to output a corresponding alarm signal according to the received alarm control signal.

A system may have sensors that gather information on users. The users may have portable electronic devices such as wristwatches, cellular telephones, and computers. The sensors may include facial recognition image sensors, fingerprint sensors, voice sensors configured to identify users by voice, and other biometric sensors. Pressure sensors may be used to measure the weight of users to help identify the users and/or to determine their age. Using the sensors, user identities and user positions may be ascertained. The system may have equipment such as adjustable seats, climate control systems, media systems, and other components that can be customized based on the identities and user positions.

A driving assistance apparatus to be applied to a vehicle includes a traveling state detector, an occupant monitoring detector, an emotion determination processor, an environment recognizer, and a driving assistance processor. The emotion determination processor determines an emotion of an occupant of the vehicle, based on outputs of the traveling state detector and the occupant monitoring detector. The driving assistance processor performs driving assistance control including one or both of information presentation to the occupant and traveling assistance control on the vehicle, in accordance with an output of one or more of the traveling state detector, the emotion determination processor, and the environment recognizer. The emotion determination processor determines multiple kinds of emotions less suitable for driving than a normal emotion. The driving assistance processor varies a control operation included in the driving assistance control, depending on a kind of the emotion determined by the emotion determination processor.