Transportation Service Planning System with Mode-Specific KPI Simulation
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Solution Overview
Problem
Existing transportation service planning techniques fail to effectively balance key performance indicators (KPIs) across multiple transportation modes, leading to suboptimal service plans that do not adequately reflect user preferences or travel demand.
Innovation Solution
A transportation service planning system that includes an operation unit and a storage unit, where the storage unit holds evaluation indices, service plan creation conditions, and simulation conditions specific to each transportation mode. The operation unit creates service plans, simulates their effects, calculates evaluation indices, and revises plans to meet prescribed standards, while also generating recommendation plans based on user attributes and past behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a service plan is formulated by evaluating common KPIs such as congestion, convenience, and profitability across multiple transportation modes, then a comprehensive service plan can be created, but the plan cannot necessarily achieve desirable outcomes for each specific transportation mode or operator because KPIs differ by mode
Solution Approach 1:
The patent applies local quality by designing the evaluation system to use mode-specific KPIs tailored to each transportation mode's characteristics. Instead of applying a uniform evaluation framework, the system selects and weights KPIs locally according to the specific needs and properties of each transportation mode (e.g., rail, bus, taxi, bicycle), thereby achieving both comprehensive coverage and mode-appropriate precision
Solution Approach 2:
The patent implements dynamics by making the evaluation framework adaptable and configurable. The system allows dynamic selection and weighting of KPIs based on the specific transportation mode being evaluated, enabling the evaluation criteria to change flexibly according to the mode rather than remaining static and uniform across all modes
2Ease of operation
If route search systems recommend routes with empty seats or matching user preferences, then user convenience is improved, but travel demand itself does not increase because destinations and stopping points cannot be discovered
Solution Approach 1:
The patent applies preliminary action by proactively recommending destinations and routes to users before they have a specific travel need. The system analyzes user attributes and past behavior to suggest destinations users might not have considered, thereby creating travel demand in advance rather than merely responding to existing demand
Solution Approach 2:
The patent uses an intermediary mechanism by introducing a recommendation engine that acts as a mediator between the transportation system and the user. This intermediary analyzes user characteristics and transportation data to bridge the gap between available capacity and user needs, suggesting both routes and destinations that match user preferences while utilizing empty seats
3Device complexity
If service plans are created without considering user attributes and past behavior, then planning complexity is reduced, but the ability to provide tailored recommendations that reflect individual preferences is lost
Solution Approach 1:
The patent applies segmentation by dividing the user population into segments based on attributes and behavior patterns. Rather than treating all users uniformly or requiring complex individualized planning for each user, the system segments users into groups with similar characteristics and applies tailored recommendation strategies to each segment, reducing overall complexity while maintaining personalization
Solution Approach 2:
The patent implements parameter changes by using user attributes and behavior data as input parameters that dynamically adjust the recommendation parameters. The system changes recommendation parameters based on user segmentation, allowing the same planning framework to adapt to different user groups without requiring completely separate planning processes for each individual
Data Source
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AI summary
Provided is a transportation service planning system including an operation unit (300, 400, 500) and a storage unit (310, 410, 510). The storage unit (310, 410, 510) stores an evaluation index designated for each of transportation systems, a creation condition of a service plan for each of the transportation systems, and a service simulation condition for each of the transportation systems. The operation unit (300, 400, 500) creates a service plan for each of the transportation systems on the basis of the creation condition of the service plan, simulates a service of each of the transportation systems on the basis of the service plan and the simulation condition, calculates the evaluation index designated for each of the transportation systems on the basis of the simulation results, outputs the service plan if all of the evaluation indices satisfy a prescribed standard, and revises the service plan if at least one of the evaluation indices does not satisfy the prescribed standard.