Abstract: An incident management system for managing an incident response may be provided. The incident management system may include an incident management (IM) computing device and a vehicle. The IM computing device may include a processor and memory, the processor may be programmed to receive a notification that an incident has occurred, the notification including sensor data and sub-system data. The processor may analyze the data to determine an incident response, the determination including categorizing the incident based on damage determined from the data. The processor may also identify a responding party based on the incident response and the category of the incident. The processor may further parse the data to generate a set of critical data. The critical data may be based on the responding party. The processor may transmit a message to the responding party including the critical data and the location of the vehicle.

Abstract: Systems and methods are disclosed for estimating slipperiness of a road surface. This estimate may be obtained using an image sensor mounted on a vehicle. The estimated road slipperiness may be utilized when calculating a risk index for the road, or for an area including the road. If a predetermined threshold for slipperiness is exceeded, corrective actions may be taken. For instance, warnings may be generated to human drivers that are in control of driving vehicle, and autonomous vehicles may automatically adjust vehicle speed based upon road slipperiness detected.

Abstract: A computer-implemented method includes receiving a vehicle condition query via a computer network and retrieving condition data corresponding to a vehicle from a vehicle condition database. Further, the method includes determining a condition of the vehicle based on a collective analysis of the condition data, where the condition of the vehicle includes a market value of the vehicle and an overall quality level of the vehicle, and receiving a geographic location of a computing device. Still further, the method includes generating a vehicle condition report, where the vehicle condition report includes an interactive image of a first set of one or more visual condition descriptors indicative of the condition of the vehicle. Moreover, the method includes customizing the vehicle condition report according to the climate associated with the geographic location for the computing device, and communicating the vehicle condition report to the second computing device.

Abstract: Systems and methods relate to, inter alia, calculating a collision risk index for an area based upon historical traffic data. The systems and methods may further generate a notification to automatically engage or disengage an autonomous, or semi-autonomous, vehicle control feature in a vehicle based upon the collision risk index for the area. The systems and methods may further transmit the notification to a device of the vehicle to facilitate automatically engaging or disengaging an autonomous, or semi-autonomous, vehicle control feature in the vehicle as the vehicle approaches the area. As a result, vehicle collisions may be reduced, and vehicle safety enhanced.

Abstract: A system and method for measuring a driver’s actual driving behaviors (e.g., acceleration, deceleration) in a manual driving mode to determine their preferred driving style, and then causing an autonomous or semi-autonomous vehicle to operate itself, within limits, in accordance with the drivers’ driving style when operating in a self-driving mode, thereby providing a more familiar and comfortable driving experience for the driver. Data is collected on the actual driving behavior, any pre-existing data is accessed on the actual driving behavior, and the collected data and the pre-existing data are combined. A custom control is then created based upon the combined data, and the custom control is applied to manage the self-driving behavior of the autonomous or semi-autonomous vehicle in a self-driving mode. Additional data continues to be collected on the actual driving behavior, and the custom control is adjusted based upon the collected additional data.

Abstract: A computer-implemented method includes receiving a vehicle condition query via a computer network and retrieving condition data corresponding to a vehicle from a vehicle condition database. Further, the method includes determining a condition of the vehicle based on a collective analysis of the condition data, where the condition of the vehicle includes a market value of the vehicle and an overall quality level of the vehicle, and receiving a geographic location of a computing device. Still further, the method includes generating a vehicle condition report, where the vehicle condition report includes an interactive image of a first set of one or more visual condition descriptors indicative of the condition of the vehicle. Moreover, the method includes customizing the vehicle condition report according to the climate associated with the geographic location for the computing device, and communicating the vehicle condition report to the second computing device.

Abstract: Systems and methods relate to, inter alia, calculating a collision risk index for an area based upon historical traffic data. The systems and methods may further generate a notification to automatically engage or disengage an autonomous, or semi-autonomous, vehicle control feature in a vehicle based upon the collision risk index for the area. The systems and methods may further transmit the notification to a device of the vehicle to facilitate automatically engaging or disengaging an autonomous, or semi-autonomous, vehicle control feature in the vehicle as the vehicle approaches the area. As a result, vehicle collisions may be reduced, and vehicle safety enhanced.

Abstract: Systems and methods are disclosed for educating vehicle drivers. Auto insurance claim data may be analyzed to identify hazardous areas associated with an abnormally high amount or severity of vehicle collisions. A virtual navigation map of roads within the hazardous areas may be built or generated. A common cause of several vehicle collisions at a hazardous area may be identified, and a virtual reconstruction of a scenario involving the common cause and/or a road map of collisions locations of may be created. The virtual reconstruction of the scenario may be displayed on a driver education virtual simulator to enhance driver education and reduce the likelihood of vehicle collisions.

Abstract: A system and method for measuring a driver's actual driving behaviors (e.g., acceleration, deceleration) in a manual driving mode to determine their preferred driving style, and then causing an autonomous or semi-autonomous vehicle to operate itself, within limits, in accordance with the drivers' driving style when operating in a self-driving mode, thereby providing a more familiar and comfortable driving experience for the driver. Data is collected on the actual driving behavior, any pre-existing data is accessed on the actual driving behavior, and the collected data and the pre-existing data are combined. A custom control is then created based upon the combined data, and the custom control is applied to manage the self-driving behavior of the autonomous or semi-autonomous vehicle in a self-driving mode. Additional data continues to be collected on the actual driving behavior, and the custom control is adjusted based upon the collected additional data.

Abstract: Among other things, techniques are described for a universal calibration target. The universal calibration target includes a core and an outer body. The core is core associated with a first salient property. The outer body is associated with a second salient property. The first salient property and the second salient property are configured to be observed by a sensor modality, and the first salient property and the second salient property correspond to at least one sensor of a vehicle.

Abstract: Systems and methods are disclosed for estimating slipperiness of a road surface. This estimate may be obtained using an image sensor mounted on a vehicle. The estimated road slipperiness may be utilized when calculating a risk index for the road, or for an area including the road. If a predetermined threshold for slipperiness is exceeded, corrective actions may be taken. For instance, warnings may be generated to human drivers that are in control of driving vehicle, and autonomous vehicles may automatically adjust vehicle speed based upon road slipperiness detected.

Abstract: Systems and methods are disclosed for estimating slipperiness of a road surface. This estimate may be obtained using an image sensor mounted on a vehicle. The estimated road slipperiness may be utilized when calculating a risk index for the road, or for an area including the road. If a predetermined threshold for slipperiness is exceeded, corrective actions may be taken. For instance, warnings may be generated to human drivers that are in control of driving vehicle, and autonomous vehicles may automatically adjust vehicle speed based upon road slipperiness detected.

Abstract: A system and method for measuring a driver's actual driving behaviors (e.g., acceleration, deceleration) in a manual driving mode to determine their preferred driving style, and then causing an autonomous or semi-autonomous vehicle to operate itself, within limits, in accordance with the drivers' driving style when operating in a self-driving mode, thereby providing a more familiar and comfortable driving experience for the driver. Data is collected on the actual driving behavior, any pre-existing data is accessed on the actual driving behavior, and the collected data and the pre-existing data are combined. A custom control is then created based upon the combined data, and the custom control is applied to manage the self-driving behavior of the autonomous or semi-autonomous vehicle in a self-driving mode. Additional data continues to be collected on the actual driving behavior, and the custom control is adjusted based upon the collected additional data.

Abstract: A computer-implemented method includes receiving a vehicle condition query via a computer network and retrieving condition data corresponding to a vehicle from a vehicle condition database. Further, the method includes determining a condition of the vehicle based on a collective analysis of the condition data, where the condition of the vehicle includes a market value of the vehicle and an overall quality level of the vehicle, and receiving a geographic location of a computing device. Still further, the method includes generating a vehicle condition report, where the vehicle condition report includes an interactive image of a first set of one or more visual condition descriptors indicative of the condition of the vehicle. Moreover, the method includes customizing the vehicle condition report according to the climate associated with the geographic location for the computing device, and communicating the vehicle condition report to the second computing device.

Abstract: A system and method for measuring a driver's actual driving behaviors (e.g., acceleration, deceleration) in a manual driving mode to determine their preferred driving style, and then causing an autonomous or semi-autonomous vehicle to operate itself, within limits, in accordance with the drivers' driving style when operating in a self-driving mode, thereby providing a more familiar and comfortable driving experience for the driver. Data is collected on the actual driving behavior, any pre-existing data is accessed on the actual driving behavior, and the collected data and the pre-existing data are combined. A custom control is then created based upon the combined data, and the custom control is applied to manage the self-driving behavior of the autonomous or semi-autonomous vehicle in a self-driving mode. Additional data continues to be collected on the actual driving behavior, and the custom control is adjusted based upon the collected additional data.

Abstract: A computer-implemented method includes receiving a vehicle condition query via a computer network and retrieving condition data corresponding to a vehicle from a vehicle condition database. Further, the method includes determining a condition of the vehicle based on a collective analysis of the condition data, where the condition of the vehicle includes a market value of the vehicle and an overall quality level of the vehicle, and receiving a geographic location of a computing device. Still further, the method includes generating a vehicle condition report, where the vehicle condition report includes an interactive image of a first set of one or more visual condition descriptors indicative of the condition of the vehicle. Moreover, the method includes customizing the vehicle condition report according to the climate associated with the geographic location for the computing device, and communicating the vehicle condition report to the second computing device.

Abstract: A method of storing fluid from an oil well includes the steps: providing storage tanks; providing a diversion tank; coupling a fill manifold to the storage tanks and to the diversion tank, the fill manifold having a first control valve controlling flow of the fluid to the storage tanks, the fill manifold having a second control valve controlling flow of the fluid to the diversion tank; associating a sensor with at least one of the storage tanks without accessing a top of any of the storage tanks, the sensor being configured to determine a volume of the fluid within at least one of the storage tanks; associating a control system with the fill manifold and the sensor; and actuating the first and second control valves using the control system in response to at least one detection by the sensor to ensure that the storage tanks are not overfilled.

Abstract: A sand trap for oil and gas extraction includes a cyclonic flow section having a longitudinal axis, an inlet for receiving a high-pressure fluid stream with particulates, an upper portion, a choke area, and a funnel portion narrowing from the upper portion to the choke area. The inlet has an axis generally perpendicular but askew to the longitudinal axis. A vortex finder extends downwardly from a cap and defines a passageway coaxial with the longitudinal axis for fluid to exit. A spherical accumulator extends downwardly from the cyclonic flow section and has a center axis coaxial with the longitudinal axis. Upper and lower ends of the spherical accumulator each have an opening centered along the longitudinal axis, and the spherical accumulator is unobstructed from the upper opening to the lower opening for the particulates to pass unimpeded and accumulate in the accumulator.

Abstract: Systems and methods are disclosed for identifying high risk parking lots. High risk parking lots may be, for example, parking lots that pose a higher than average risk of collisions and/or theft. Auto insurance claim data may be analyzed to identify hazardous areas. A virtual navigation of roads within the hazardous area may be identified. Public parking lots within the virtual navigation map may be defined, with each public parking lot determined as either in a hazardous area or not. A vehicle may be determined to be approaching or parking in a parking lot in a hazardous area, and a nearby public parking lot not associated with the hazardous area may be selected instead. A route from a current position to the nearby public parking lot may be generated, and the vehicle may be routed to the nearby public parking lot. As a result, collisions and thefts may be reduced.