Elevator Car Assignment via Passenger Proximity Detection
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Solution Overview
Problem
Elevator systems face challenges in determining the number of passengers intending to board a car when not all individuals have indicated their destination, leading to inadequate space allocation during peak times, as the dispatch controller cannot account for additional passengers traveling with those who have placed requests.
Innovation Solution
The system uses proximity detectors, such as cameras, depth sensors, and turnstile data to determine if individuals are likely associated with a passenger who has entered a service request, allowing the controller to assign the elevator car and reserve space for those not initially indicating a destination, based on distance, movement, and past travel behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the dispatch controller assigns elevator cars based only on explicit passenger requests, then the assignment process is simple and fast, but inadequate space is allocated when additional passengers are not accounted for
Solution Approach 1:
The system performs preliminary detection of passenger proximity and association before the elevator car assignment is finalized. By detecting groups of passengers approaching together and predicting they will travel together, the system reserves space in advance for unannounced passengers, ensuring adequate capacity while maintaining efficient dispatch decisions
Solution Approach 2:
The system continuously monitors passenger movement and proximity data, using this feedback to dynamically adjust car assignments. By detecting that additional passengers are approaching the elevator landing with the original requester, the controller can modify the assignment to accommodate them, improving space allocation accuracy without sacrificing overall system efficiency
2Measurement precision
If the system monitors and analyzes passenger proximity and movement patterns, then accurate prediction of group travel is achieved, but the system complexity and computational requirements increase
Solution Approach 1:
The detector is designed as a multi-functional device that simultaneously performs multiple tasks: detecting passenger presence, measuring proximity distances, tracking movement patterns, and identifying group associations. This universal detector reduces overall system complexity by consolidating what would otherwise require separate specialized sensors and processing systems
Solution Approach 2:
The system uses the existing infrastructure of the building (turnstiles, destination entry devices, lighting systems) to gather passenger data and provide association detection. By leveraging already-present components for multiple purposes, the system achieves accurate passenger grouping without adding significant external complexity
Data Source
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AI summary
An illustrative example embodiment of an elevator system (20) includes a destination entry device (22) configured to allow a passenger to indicate an intended destination prior to entering an elevator car (24, 26, 28) and at least one detector (32, 36, 38) configured to detect a proximity between the passenger and at least one other individual that has not indicated an intended destination. A controller (30) is configured to determine whether the detected proximity between the passenger and the at least one other individual satisfies at least one criterion indicating that the at least one other individual likely is associated with the passenger, will board an elevator car (24, 26, 28) with the passenger, and will travel to the intended destination with the passenger. The controller (30) is configured to assign an elevator car (24, 26, 28) to carry the passenger and the at least one other individual to the intended destination when the detected proximity satisfies the at least one criterion.