Crowdsourced Roadside Assistance Assignment System
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing roadside assistance systems rely solely on proximity for assigning service providers, neglecting other critical factors such as user preferences, service provider skills, and insurance information, leading to inefficient and potentially unsafe service delivery.
Innovation Solution
A computer-implemented method and system that utilizes telematics information and service provider data to prioritize and assign roadside assistance service providers based on proximity, user preferences, service provider skills, and insurance information, incorporating sensors and a mobile application for real-time communication and payment processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If roadside assistance service providers are assigned solely based on proximity to distressed vehicle, then assignment speed is improved, but service quality and safety are worsened
Solution Approach 1:
The system changes the assignment parameters from a single factor (proximity) to multiple factors including proximity, service provider skills, user preferences, and insurance information. This multi-parameter approach resolves the contradiction by maintaining fast assignment through proximity while ensuring service quality through additional criteria evaluation.
Solution Approach 2:
The invention adds new dimensions to the assignment process by incorporating service provider skills, user preferences, and insurance information alongside proximity. This dimensional expansion allows the system to consider both speed (proximity) and quality (additional factors) simultaneously, resolving the contradiction between assignment speed and service quality.
2Reliability
If multiple factors are considered for service provider assignment, then service quality is improved, but system complexity is worsened
Solution Approach 1:
The system employs a multi-functional assignment mechanism that handles proximity calculation, skill matching, preference analysis, and insurance verification through a unified platform. This universal approach improves service quality through comprehensive factor consideration while managing system complexity by consolidating multiple functions into a single integrated system.
Solution Approach 2:
The system enables automatic evaluation and weighting of multiple factors including proximity, skills, preferences, and insurance information without requiring manual intervention. This self-service capability improves service quality through comprehensive analysis while reducing the perceived complexity for users by automating the evaluation process.
3Reliability
If traditional professional service providers are used, then service reliability is improved, but cost and scheduling difficulty are worsened
Solution Approach 1:
The system enables service providers to autonomously manage their availability, skills, and service offerings through the platform. This self-service approach maintains service reliability by allowing experienced providers to participate while dramatically improving scheduling ease through automated matching and real-time availability updates, eliminating the need for manual scheduling coordination.
Data Source
AI summary
Aspects of the disclosure provide a computer-implemented method and system for the assignment of crowdsourced roadside assistance service providers to distressed vehicles/drivers requiring roadside assistance. The methods and systems may include a roadside assistance service provider system with a collection module, an assignment module, and a feedback module. The collection module collects roadside assistance service provider information and historical statistics from real-world information and stores the information in a database that may then be analyzed using particular rules and formulas. The assignment module assigns particular roadside assistance service providers to particular distressed vehicles/drivers based on one or more characteristics. The feedback module may provide near real-time cues to the roadside assistance service provider's mobile device, such as alerting when the amount of time spent on a task exceeds a predefined threshold, flagging high priority tasks/assignments, providing a technical reference for the repair.