Variable Transit Point Routing for Multi-Modal Transport
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Solution Overview
Problem
Transportation systems face challenges in addressing the first/last-mile problem, where users struggle to connect to and from fixed transportation networks, and existing solutions often rely on rigid, schedule-based services that do not adapt to dynamic conditions.
Innovation Solution
A communications server apparatus and method that generate and optimize multi-modal journey options by introducing variable transit points based on transportation network parameters, such as driver supply, accessibility, and fare surging risks, allowing for on-demand and ride-hailing services to optimize routes dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fixed or schedule-based transportation services are used, then service reliability is improved, but adaptability to dynamic conditions deteriorates
Solution Approach 1:
The patent applies dynamics by transforming fixed transit points into variable transit points that can change location based on real-time transportation network conditions. The system dynamically adjusts transit point locations considering parameters such as driver supply, accessibility, fare surging risks, and detour minimization, allowing the transportation system to adapt to changing conditions while maintaining service reliability through structured optimization.
2Adaptability or versatility
If variable transit points are introduced, then adaptability is improved, but device complexity increases
Solution Approach 1:
The patent applies parameter changes by determining variable transit points based on multiple transportation network parameters including driver supply levels, accessibility metrics, fare surging risk assessments, and detour distance calculations. The system changes the location parameter of transit points dynamically based on these parameters, achieving adaptability through parameter-driven decision making rather than structural complexity.
Solution Approach 2:
The patent replaces mechanical/physical fixed infrastructure with a computational system that uses algorithms and data processing to determine optimal transit points. Instead of physically reconfiguring transportation infrastructure, the system substitutes computational optimization to achieve variable transit point locations, reducing physical device complexity while maintaining adaptability.
3Adaptability or versatility
If multiple transportation modes are integrated, then versatility is improved, but system complexity increases
Solution Approach 1:
The patent applies universality by creating a multi-modal transportation system where a single integrated platform handles multiple transportation modes (ride-hailing, public transit, walking). The system provides universal journey planning capabilities that work across different modes, allowing users to access versatile transportation options through a unified interface rather than separate systems for each mode.
Solution Approach 2:
The patent merges multiple transportation networks (road network for ride-hailing, public transport network, walking paths) into a single integrated multi-modal network. By combining these separate networks into one unified system with shared transit points and coordinated routing, the patent achieves versatility while managing complexity through integration rather than multiplication of separate systems.
Data Source
AI summary
A communications server apparatus for managing a request for transport-related services, which is configured to, in response to receiving user request data, generate a data record having a plurality of transit point data fields having data for a corresponding plurality of transit points from an origin to a destination, including a variable transit point data field having data that is determined based on data associated with at least one transportation network-related parameter, and having a plurality of trip section data fields for a corresponding plurality of trip sections defining navigation directions from the origin to the destination, and, for each trip section data field, to associate the trip section data field with a respective transit point data field, and, based on the data of the associated transit point data field, to determine a respective transportation mode and to generate transit data in respect of the respective transportation mode.