Elevator Allocation Using Predicted Passenger Traffic
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Solution Overview
Problem
Elevator systems using immediate call allocation face challenges in reassigning calls and managing elevator load, leading to reduced passenger service levels, especially in destination control systems where calls cannot be reassigned once allocated.
Innovation Solution
A method and apparatus for computing allocation decisions in elevator systems that utilize historical passenger batch journey data to construct traffic statistics, model expected calls, and estimate elevator load, allowing for optimized allocation decisions, including the use of 'dummy' calls to simulate and optimize the allocation of elevators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If immediate call allocation is used in destination control systems, then call allocation speed is improved, but the ability to reassign calls optimally deteriorates
Solution Approach 1:
The system performs preliminary modeling of expected calls and elevator loads before actual call allocation occurs. By using historical passenger batch journey data to construct traffic statistics and model future calls, the system prepares optimal allocation decisions in advance, allowing immediate allocation to be both fast and optimizable.
2Device complexity
If calls are not reassigned in destination control systems, then system simplicity is improved, but passenger service level deteriorates
Solution Approach 1:
The system uses self-service through automated modeling and prediction algorithms that analyze historical data and automatically determine optimal call allocations. The elevator control apparatus independently computes allocation decisions based on modeled expected calls and estimated elevator loads, improving service levels without requiring complex manual intervention or reassignment protocols.
3Device complexity
If elevator load is not monitored and managed, then system simplicity is improved, but system performance deteriorates
Solution Approach 1:
The system implements feedback through continuous monitoring of actual passenger batch journeys and comparison with modeled expected calls. Historical passenger traffic statistics are constructed from actual data and fed back into the modeling process, allowing the system to learn from past performance and continuously optimize elevator load management and allocation decisions.
Data Source
AI summary
A method and an apparatus for computing allocation decisions in an elevator system is provided. Historical passenger batch journey data relating to the elevator system is obtained, wherein each passenger batch journey includes an origin and a destination floor of the journey, the number of passengers of the journey and the time of the journey. Historical passenger traffic statistics are constructed based on the passenger batch journey data, and expected calls are modelled based on the passenger traffic statistics. The modelled expected call is taken into account in computing subsequent allocation decisions in the elevator system.