Vehicle Path Planning Using Time-Slot Passenger Flow Vectors
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Solution Overview
Problem
Existing transportation systems struggle to efficiently determine vehicle movement paths considering varying passenger flows at different time slots, leading to inefficiencies and reduced passenger capacity.
Innovation Solution
A method and apparatus that determine a vehicle's movement path by obtaining boarding/alighting information for each time slot, calculating passenger movement flow vectors, and optimizing vehicle routes based on these vectors to maximize passenger capacity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If vehicle movement paths are determined without considering time slot-specific passenger flows, then the system is simpler to operate, but passenger carrying capacity and productivity are reduced
Solution Approach 1:
The system segments the transportation network into multiple time slots (e.g., morning commute, afternoon commute, evening) and determines vehicle movement paths separately for each time slot based on time-specific passenger flow patterns. This segmentation allows the system to optimize for each period without overwhelming complexity, improving overall productivity while maintaining manageable system structure.
Solution Approach 2:
The system dynamically adjusts vehicle movement paths based on real-time or historical passenger flow data specific to each time slot. Instead of using fixed routes, the system adapts vehicle trajectories to match actual demand patterns, such as increasing frequency during peak hours and reducing it during off-peak periods, thereby maximizing passenger carrying capacity.
2Productivity
If vehicle routes are optimized for peak passenger flow periods, then productivity increases, but the system becomes more complex to manage
Solution Approach 1:
The system performs preliminary analysis of passenger flow patterns using historical data to predict future demand at different time slots. Vehicle movement paths are pre-planned based on these predictions, allowing operators to prepare optimized routes in advance without needing complex real-time decision-making systems, thus maintaining ease of operation while improving productivity.
Solution Approach 2:
The system incorporates feedback mechanisms that continuously monitor actual passenger flow and compare it with predicted patterns. This feedback is used to refine and adjust vehicle movement paths for future time slots, allowing the system to learn from past performance and improve optimization automatically, reducing the need for manual intervention and maintaining operational simplicity.
Data Source
AI summary
The present disclosure relates to a method and apparatus for determining a movement path of a vehicle considering a movement flow of passengers.In the method according to an embodiment of the present disclosure, boarding/alighting information for each time slot for each of a plurality of boarding/alighting points may be obtained, and departure/arrival information for each passenger may be obtained based on the boarding/alighting information for each time slot. In addition, in the method according to an embodiment of the present disclosure, at least one passenger movement flow vector for each time slot may be determined based on the departure/arrival information for each passenger, and a movement path of a vehicle may be determined based on the passenger movement flow vector for each time slot.