Abstract:
Described herein is a system and method for predicting the extent and cost of repair resulting from a vehicle accident. The estimates can be based on one or more of in-vehicle sensor measurements during the accident, external observations such as weather and traffic and road conditions, and manually or digitally input accident reports. The gathered information is compared to information in a database from historical accidents and the resulting damage and costs for those. The information is classified according to impact force, direction and location along with the specific type of vehicle. Maintaining and refreshing the information and predictive models in the system is also part of the invention.
Abstract:
Embodiments of this invention relate to a method of determining the risk of driving a vehicle on a road network as a function of, for example, location, time of driving, weather, road conditions, driver ability, and traffic density. Historical information for the above is statistically analyzed to come up with a predictive model. Results can be displayed or presented to a driver while driving or otherwise or another person.
Abstract:
Described herein is a system and method for predicting the extent and cost of repair resulting from a vehicle accident. The estimates can be based on one or more of in-vehicle sensor measurements during the accident, external observations such as weather and traffic and road conditions and manually or digitally input accident reports. The gathered information is compared to information in a database from historical accidents and the resulting damage and costs for those. The information is classified according to impact force, direction and location along with the specific type of vehicle. Maintaining and refreshing the information and predictive models in the system is also part of the invention.
Abstract:
Embodiments of this invention relate to a method of determining the risk of driving a vehicle on a road network as a function of, for example, location, time of driving, weather, road conditions, driver ability, and traffic density. Historical information for the above is statistically analyzed to come up with a predictive model. Results can be displayed or presented to a driver while driving or otherwise or another person.
Abstract:
Described herein is a system and method of use for a vehicle diagnostic distributed database. One or more central servers are configured with a database containing diagnostic information pertaining to vehicles and relative to input received by the central server/s from client devices. The central server is configured to upload and download information with in-vehicle and external to vehicle diagnostic systems. These tasks are performed by first having the central server/s broadcast a message over open airways (for example, FM sidebands) to all potential client devices of interest. The message contains information identifying specific characteristics of client devices that should respond and further information about the information that is desired to be uploaded to the central server/s or for downloaded to the clients of interest. If clients meet the broadcast criteria, they then establish two-way communication with the central server/s and fulfill the request.
Abstract:
A system to monitor vehicle accidents using a network of aerial based monitoring systems, terrestrial based monitoring systems and in-vehicle monitoring systems is described. Aerial vehicles used for this surveillance include manned and unmanned aircraft, satellites and lighter than air craft. Aerial vehicles can also be deployed from vehicles. The deployment is triggered by sensors registering a pattern in the data that is indicative of an accident that has happened or an accident about to happen.
Abstract:
A system to monitor vehicle accidents using a network of aerial based monitoring systems. terrestrial based monitoring systems and in-vehicle monitoring systems is described, Aerial vehicles used for this surveillance include manned and unmanned aircraft, satellites and lighter than air craft. Aerial vehicles can also be deployed from vehicles. The deployment is triggered by sensors registering a pattern in the data that is indicative of an accident that has happened or an accident about to happen.
Abstract:
Described herein is a system and method for predicting the extent and cost of repair resulting from a vehicle accident. The estimates can be based on one or more of in-vehicle sensor measurements during the accident, external observations such as weather and traffic and road conditions, and manually or digitally input accident reports. The gathered information is compared to information in a database from historical accidents and the resulting damage and costs for those. The information is classified according to impact force, direction and location along with the specific type of vehicle. Maintaining and refreshing the information and predictive models in the system is also part of the invention.
Abstract:
A system to monitor vehicle accidents using a network of aerial based monitoring systems, terrestrial based monitoring systems and in-vehicle monitoring systems is described. Aerial vehicles used for this surveillance include manned and unmanned aircraft, satellites and lighter than air craft. Aerial vehicles can also be deployed from vehicles. The deployment is triggered by sensors registering a pattern in the data that is indicative of an accident that has happened or an accident about to happen.
Abstract:
A system to monitor vehicle accidents using a network of aerial based monitoring systems, terrestrial based monitoring systems and in-vehicle monitoring systems is described. Aerial vehicles used for this surveillance include manned and unmanned aircraft, satellites and lighter than air craft. Aerial vehicles can also be deployed from vehicles. The deployment is triggered by sensors registering a pattern in the data that is indicative of an accident that has happened or an accident about to happen.