Dynamic Mass Transit Routing via Hub Stop Thresholds
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Solution Overview
Problem
Scaling on-demand transportation services for mass transit vehicles to serve tens or hundreds of passengers within a short timeframe is complex and cannot be reasonably accomplished by manual planning techniques, and existing systems lack efficient dynamic routing solutions that account for changing demand and safety constraints.
Innovation Solution
A computer-implemented method for routing mass transit vehicles that dynamically selects hub stops as waypoints based on threshold times, minimum allowed waytime, and minimum progress, allowing vehicles to adjust routes in real-time to optimize service requests without manual driver intervention, using a central dispatch system and telemetric data for route optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual planning techniques are used for routing mass transit vehicles, then the system is simple to operate, but it cannot efficiently serve tens or hundreds of passengers within a short timeframe
Solution Approach 1:
The routing system performs self-service through automated algorithms that dynamically determine optimal routes and stops based on real-time passenger requests and vehicle locations, eliminating the need for manual driver intervention while handling large volumes of passengers efficiently
Solution Approach 2:
The patent replaces manual mechanical routing decisions with automated computer-based algorithms that process passenger requests, calculate travel times, and determine optimal stops without human intervention, thereby increasing service capacity while managing system complexity through software
2Adaptability or versatility
If driver interaction is required to accept passenger requests during trips, then the system can handle on-demand requests, but it creates unsafe driving practices
Solution Approach 1:
The vehicle routing system serves itself by automatically accepting and processing passenger requests without driver interaction. The automated system evaluates requests, determines routing decisions, and manages trip modifications independently, maintaining safety while preserving on-demand adaptability
Solution Approach 2:
The patent introduces an automated routing system as an intermediary between passengers and vehicles. This intermediary processes all request-related operations, eliminating the need for drivers to interact with passenger requests while maintaining the system's ability to handle on-demand service
3Adaptability or versatility
If fixed vehicle routes are used, then the transportation service is predictable and easy to schedule, but it cannot adapt to changing passenger demand patterns
Solution Approach 1:
The routing system transitions from static fixed routes to dynamic adaptive routing. The system continuously adjusts vehicle routes and stops based on real-time passenger requests and conditions, enabling demand responsiveness while automated processing maintains rapid decision-making without significant time loss
Data Source
AI summary
A computer implemented system and method for routing a vehicle. The method includes establishing, in a computer memory, a set of parameters comprising a plurality of hub stops and a threshold time, receiving a service request comprising a service location, determining a current location of the vehicle, determining an upcoming travel time for the vehicle to travel from the current location to the service location, and determining, via a processor, a next stop for the vehicle selected from: if the upcoming travel time does not exceed the threshold time, the service location; and if the upcoming travel time exceeds the threshold time, one of the plurality of hub stops.