Route Risk Determination System Using Driver Behavior and Infrastructure Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional vehicle telematics systems fail to assess and recommend routes based on safety factors, leading to a high risk of collisions, as they primarily consider time and distance without accounting for human driving behavior and road infrastructure safety.
Innovation Solution
A method and system that collect and process various inputs, including sensor data and driver behavior, to determine risk scores for routes, enabling informed navigation choices and infrastructure assessments, using a model that aggregates data from multiple drivers to quantify and predict collision risks across different locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional systems recommend routes based on time and distance alone, then navigation efficiency is improved, but collision risk increases due to lack of safety consideration
Solution Approach 1:
The system transforms route recommendation from considering only time and distance parameters to incorporating multiple new parameters including collision risk scores, driver behavior metrics, and road infrastructure safety factors. This parameter expansion allows the system to evaluate routes comprehensively, balancing navigation efficiency with safety by selecting routes that optimize multiple criteria simultaneously.
Solution Approach 2:
The system introduces a route risk assessment model as an intermediary component that evaluates potential routes before recommendation. This model acts as a mediator between the navigation system and the driver, filtering out high-risk routes and presenting only those that meet safety thresholds, thus resolving the contradiction between efficiency and safety.
2Reliability
If route assessment incorporates multiple safety factors and driver behavior data, then collision risk reduction is achieved, but system complexity increases
Solution Approach 1:
The system divides the complex route assessment task into separate modular components: a route risk assessment model that evaluates geographic and infrastructure factors, a driver behavior analysis module that processes telematics data, and a route recommendation engine that synthesizes both inputs. This segmentation allows each component to specialize in specific data types and algorithms, reducing overall system complexity while maintaining comprehensive safety evaluation.
Solution Approach 2:
The system utilizes existing telematics infrastructure and publicly available road data to perform self-assessment of route risks without requiring additional external monitoring systems. By leveraging data already collected during normal vehicle operation and open-source geographic information, the system achieves comprehensive safety evaluation while minimizing the need for additional complex hardware or external services.
Data Source
AI summary
A method for risk determination of a route includes collecting a set of inputs and determining a set of risk scores. Additionally, the method can include any or all of: processing the set of inputs; organizing the set of inputs; determining a model based on the set of inputs; determining a set of risk scores; producing an outputs based on the set of risk scores; and/or any other suitable processes.