Disclosed are systems and methods relating to providing corridor metrics based on road network data and telematic data.

A vehicle is provided that comprises two or more radio frequency (RF) antennas and two or more RF transceivers to communicate wirelessly sensitive information associated with a user of the vehicle (the two or more RF antennas being at different physical locations on an exterior of the vehicle). The vehicle determines which one of the two or more RF antennas is receiving a strongest signal from a common signal source, selects a first RF transceiver associated with the RF antenna with the strongest signal to send the sensitive information associated with the user to the common signal source, and sends the sensitive information associated with the user to the first RF transceiver for transmission to the common signal source.

A system for imaging and analyzing a vehicle may include a frame having a central passage, wherein the central passage is configured and dimensioned to allow a vehicle to pass through. The frame may include, for example, a pair of substantially vertical legs connected at the top by a cross member, wherein the legs and cross member define the central passage. One or more bollards may be positioned in front of and/or behind the frame. A plurality of cameras within the each leg, cross member, and/or bollard may be directed toward the passage to record video images of a passing vehicle. Integrated LED array panels may provide bands of light to aid in detection of surface anomalies, for example by simultaneous analysis of symmetrical sides of the vehicle.

Embodiments herein can determine an optimal route for an autonomous electric vehicle. The system may score viable routes between the start and end locations of a trip using a numeric or other scale that denotes how viable the route is for autonomy. The score is adjusted using a variety of factors where a learning process leverages both offline and online data. The scored routes are not based simply on the shortest distance between the start and end points but determine the best route based on the driving context for the vehicle and the user.

Embodiments herein can determine an optimal route for an autonomous electric vehicle. The system may score viable routes between the start and end locations of a trip using a numeric or other scale that denotes how viable the route is for autonomy. The score is adjusted using a variety of factors where a learning process leverages both offline and online data. The scored routes are not based simply on the shortest distance between the start and end points but determine the best route based on the driving context for the vehicle and the user.

Described herein is a system and method for predicting when repair and maintenance needs to be performed on a vehicle. The estimates can be based on one or more of in-vehicle sensor measurements during vehicle usage, external observations such as weather and traffic and road conditions and manually or digitally input maintenance and service reports. The gathered information is compared to information in a database from historical maintenance and service and the resulting damage and costs for those. The information is classified by the type of vehicle and the age and usage of the vehicle. Maintaining and refreshing the information and predictive models in the system is also part of the invention.

In some examples, a controller receives information of a route of a vehicle, and selects a first parameter set from among a plurality of parameter sets based on the route of the vehicle, the plurality of parameter sets corresponding to different conditions of usage of the vehicle, where each parameter set of the plurality of parameter sets includes one or more parameters that control adjustment of one or more respective adjustable elements of the vehicle. The controller causes application of the first parameter set to control a setting of the one or more adjustable elements of the vehicle.

A heating system includes at least one electric heater disposed within a fluid flow system and a control device that is configured to determine a temperature of the at least one electric heater based on a model, at least one fluid flow system input, and at least one heater input. The at least one heater input includes at least one physical characteristic of the heating system, the at least one physical characteristic includes at least one of a resistance wire diameter, a heater insulation thickness, a heater sheath thickness, a conductivity, a specific heat and density of the material of the heater, an emissivity of the heater and the fluid flow pathway, and combinations thereof. The control device is configured to provide power to the at least one electric heater based on the temperature of the at least one electric heater.

An overall efficiency of an actuator system can be monitored to determine the health of the actuator system. A ratio between the output power of the actuator system and the input power of the actuator system is monitored over time. Degradation of the efficiency of the actuator system may be observed and corrective action taken before failure of the actuator system.

An input unit 81 receives input of a normal pattern file including information indicating a normal condition of a vehicle, and a fault pattern file including information indicating a sign that a vehicle fault is about to occur. A collection unit 82 collects observation data observed by each device in the target vehicle. A comparison unit 83 compares the content of the normal pattern file with the content of the observation data. when the difference between the content of the normal pattern file and the content of the observation data is greater than a predetermined first threshold value, the comparison unit 83 further compares the content of the fault pattern file and the observation data, and when the difference between the content of the fault pattern file and the observation data is within a predetermined second threshold value, determines that there is the sign of the fault in the target vehicle.