Multi-Objective Path Planning for Intelligent Public Transport
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Solution Overview
Problem
Traditional route planning methods for intelligent public transport systems are inefficient in minimizing passenger waiting periods and optimizing bus operations, leading to suboptimal passenger experience and increased costs.
Innovation Solution
A multi-objective path planning method that generates a shortest path network topology, dynamically allocates bus routes based on passenger waiting periods, road lengths, and travel distances, and determines an optimal bus route configuration to minimize waiting times and maximize passenger capacity, thereby improving overall efficiency and experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional route planning methods based on historical experience and greedy rules are used, then the planning process is simple, but the passenger waiting period is long and the load factor is low
Solution Approach 1:
The patent implements dynamic route planning that adapts to real-time passenger demand and traffic conditions. The system continuously updates route configurations based on current state information, transforming static historical experience-based planning into dynamic optimization that responds to changing conditions, thereby reducing passenger waiting periods while maintaining manageable complexity through algorithmic automation
Solution Approach 2:
The system incorporates feedback mechanisms that use real-time passenger flow data, traffic conditions, and route performance metrics to continuously improve route planning. This feedback loop enables the system to learn from historical data and adjust routes dynamically, achieving better load factors and reduced waiting times without proportionally increasing planning complexity
2Productivity
If traditional route planning methods are used, then the operational complexity is low, but the bus operating cost is high and passenger experience is poor
Solution Approach 1:
The system performs preliminary route planning and optimization before the actual transportation service begins. By pre-calculating optimal routes based on historical data and predicted demand, the system prepares route configurations in advance, enabling efficient real-time execution without requiring complex dynamic adjustments during operation, thus improving productivity while controlling system complexity
Solution Approach 2:
The patent utilizes parameter changes in passenger demand, traffic conditions, and route characteristics to optimize route planning. By monitoring and responding to changes in these parameters, the system dynamically adjusts route configurations to improve productivity and reduce operating costs, achieving better efficiency without proportionally increasing system complexity through automated parameter-based decision making
3Reliability
If multi-objective optimization is implemented to minimize waiting period and maximize load factor, then passenger experience improves, but the computational complexity increases
Solution Approach 1:
The patent segments the route planning problem into multiple independent or loosely coupled sub-problems, such as route selection, timing optimization, and resource allocation. This segmentation allows each sub-problem to be solved separately with simpler algorithms, reducing overall computational complexity while maintaining high optimization quality through coordinated solutions to the segmented components
Data Source
AI summary
Provided is a multi-objective path planning method for an intelligent public transport system, includes: generating a shortest path network topology for connecting bus stops by analyzing a traffic network topology and bus drivable paths; dynamically and evenly allocate bus routes according to passenger waiting periods, road lengths, and the shortest path network topology, to thereby allocate different routes for different buses; and determining an optimal bus route configuration according to average passenger travel distances, passenger experience, and the bus routes. The method can minimize a passenger waiting period while ensuring a high passenger load rate, thereby improving the overall efficiency of the public transport system and the travel experience of passengers.