Transport Disruption Management System for Passenger Priority Allocation
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Solution Overview
Problem
Conventional disruption management systems for public transportation struggle to detect traffic disruptions promptly and efficiently allocate limited transport resources, leading to unnecessary passenger delays and sub-optimal travel arrangements.
Innovation Solution
A transport disruption management system comprising an analytics module that detects or predicts travel disruptions using data from sensors and video feeds, a priority determination module that assesses passenger priorities based on individual circumstances, and a resource allocation module that allocates mitigation resources effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional disruption management systems rely on human input to detect disruptions, then the system is easier to operate, but the detection time becomes unpredictable and delays increase
Solution Approach 1:
The system enables self-service disruption detection by automatically monitoring transport routes using sensors, video feeds, and data from other transport systems. The analytics module processes this data to detect disruptions without human intervention, eliminating the unpredictable delays associated with manual reporting while maintaining operational simplicity.
Solution Approach 2:
The patent replaces the mechanical system of human reporting with an automated electronic detection system. Sensors, video cameras, and data communication networks substitute for human observers, providing continuous automated monitoring that eliminates the variability in detection time inherent in human-operated systems.
2Device complexity
If conventional systems allocate transport resources without passenger data, then the system complexity is reduced, but the resource allocation efficiency deteriorates
Solution Approach 1:
The system performs preliminary actions by collecting and storing passenger data before disruptions occur. This advance preparation includes gathering information about passenger destinations, accessibility requirements, and journey priorities, enabling rapid and efficient resource allocation when disruptions happen without adding significant complexity during the disruption response.
3Reliability
If automated detection systems use multiple data sources, then detection reliability is improved, but the device complexity increases
Solution Approach 1:
The analytics module serves multiple functions by processing data from diverse sources including sensors, video feeds, and external transport systems. This multi-functional approach consolidates what would otherwise require separate detection systems into a single unified module, improving reliability through data triangulation while minimizing the increase in overall system complexity.
Data Source
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AI summary
A transport disruption management system 100 for managing travel disruption of passengers. The transport disruption management system comprises: an analytics module 106, configured to: receive data from one or more sensors located along one or more transport routes of vehicles carrying passengers; and detect or predict a travel disruption event from the received data, a priority determination module 108 configured to: receive, from the analytics module, information indicating that a travel disruption event has been detected or predicted, and determine a travel priority of one or more passengers of a transport vehicle affected by the travel disruption event based on priority determination data; and a resource allocation module 110 configured to allocate mitigation resources to the passengers affected by the travel disruption event, based on the priority determined by the priority determination module and the nature of the detected or predicted travel disruption event.