Cloud Grid Servers for Real-Time Vehicle Collision Prediction
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Solution Overview
Problem
Current assistive driving technologies, such as lane departure warning and collision detection, are expensive and not widely available, and dedicated infrastructure solutions like DSRC are costly and slow to implement, limiting their widespread adoption.
Innovation Solution
A cloud service using a network of grid servers to process trajectory data from mobile devices to predict potential collisions and lane departures, sending alerts to vehicles, leveraging existing mobile devices and cloud computing to provide affordable and scalable safety enhancements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If stand-alone sensor-based assistive technologies are implemented in vehicles, then driver safety is improved through collision detection and lane departure warning, but the cost becomes prohibitively high and availability is limited to high-end cars
Solution Approach 1:
The patent introduces a cloud-based server as an intermediary that processes trajectory data from multiple vehicles to provide safety alerts. Instead of each vehicle having expensive embedded sensor systems, the cloud server acts as a mediator that receives trajectory information from vehicles and sends back collision warnings, thereby reducing the cost burden on individual vehicles while maintaining safety functionality.
Solution Approach 2:
The patent uses mobile devices (smartphones, tablets) as copies or substitutes for dedicated embedded vehicle sensors. These existing mobile devices with cameras and GPS capabilities are leveraged to capture trajectory data, replacing the need for expensive purpose-built sensor systems in each vehicle.
2Reliability
If dedicated roadside infrastructure like DSRC is deployed for vehicle-to-vehicle and vehicle-to-infrastructure communications, then inter-vehicle communication safety is improved, but the implementation cost becomes very high and deployment is slow
Solution Approach 1:
The patent enables vehicles to self-report their trajectory data to the cloud server using their existing mobile devices and communication capabilities. Each vehicle independently contributes its own trajectory information without requiring external infrastructure to actively monitor or communicate with other vehicles, thereby eliminating the need for expensive dedicated roadside infrastructure.
Solution Approach 2:
The patent leverages existing mobile devices and general-purpose communication networks (cellular data networks) to perform the specialized function of vehicle trajectory monitoring and collision detection. These universal platforms serve multiple purposes including navigation, entertainment, and now safety monitoring, eliminating the need for dedicated single-function infrastructure.
3Productivity
If cloud-based processing is used to analyze trajectory data from multiple vehicles, then the system can serve a large number of vehicles with high throughput, but data processing latency must be minimized to ensure real-time safety alerts
Solution Approach 1:
The patent segments the cloud-based processing system into multiple server instances that can independently process trajectory data from different vehicles or vehicle groups. This segmentation allows parallel processing of multiple data streams simultaneously, increasing overall throughput while maintaining low latency for individual vehicle alerts through distributed computation.
Data Source
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AI summary
Described is a technology by which driver safety technology such as collision detection is implemented via mobile device (e.g., smartphone) sensors and a cloud service that processes data received from vehicles associated with the devices. Trajectory-related data is received at the cloud service and used to predict collisions between vehicles and/or lane departures of vehicles. To operate the service in real-time with low latency, also described is dividing driving areas into grids, e.g., based upon traffic density, having parallel grid servers each responsible for only vehicles in or approaching its own grid, and other parallel / distributed mechanisms of the cloud service.