Abstract:
The present invention is directed to the grouping of contiguous floors in a building into sectors. According to the present invention, historical information regarding the number of passengers arriving at each floor is obtained and used to predict the number of passengers to be arriving at each of the floors. By summing the predicted traffic per floor and dividing by the number of sectors to be formed, average traffic per sector can be determined. In the preferred embodiment, sectors are formed, starting from the first floor above the lobby and continuing through to the top floor in the building, by selecting a set of contiguous floors for each sector such that the predicted traffic for each sector is less than a predetermined threshold. Specifically, if the predicted traffic for a selectable next contiguous floor, added to the predicted traffic for all contiguous floors already selected for the sector, is less than the predetermined threshold, the selectable floor is included in the sector. Otherwise, another sector is begun with the selectable floor as the bottom floor in the other sector. In the preferred embodiment, the predetermined threshold is based on the determined average traffic per sector. In another aspect of the present invention, the frequency of service elevator cars to each sector is variable. The traffic volume for each formed sector is determined and compared with the determined average traffic per sector. The frequency of service of elevator cars to each sector is variable, based on this comparison. Thus, sectors having a larger traffic volume are serviced more often, relative to sectors having a smaller traffic volume.
Abstract:
The present invention is directed to the grouping of contiguous floors in a building into sectors. According to the present invention, historical information regarding the number of passengers arriving at each floor is obtained and used to predict the number of passengers to be arriving at each of the floors. By summing the predicted traffic per floor and dividing by the number of sectors to be formed, average traffic per sector can be determined. In the preferred embodiment, sectors are formed, starting from the first floor above the lobby and continuing through to the top floor in the building, by selecting a set of contiguous floors for each sector such that the predicted traffic for each sector is less than a predetermined threshold. Specifically, if the predicted traffic for a selectable next contiguous floor, added to the predicted traffic for all contiguous floors already selected for the sector, is less than the predetermined threshold, the selectable floor is included in the sector. Otherwise, another sector is begun with the selectable floor as the bottom floor in the other sector. In the preferred embodiment, the predetermined threshold is based on the determined average traffic per sector. In another aspect of the present invention, the frequency of service elevator cars to each sector is variable. The traffic volume for each formed sector is determined and compared with the determined average traffic per sector. The frequency of service of elevator cars to each sector is variable, based on this comparison. Thus, sectors having a larger traffic volume are serviced more often, relative to sectors having a smaller traffic volume.
Abstract:
The present invention is directed to determining the frequency of elevator cars to each sector in a building divided into sectors. According to the invention, historical information regarding the number of passengers arriving at each floor is obtained and used to predict the number of passengers to be arriving at each of the floors. By summing the predicted traffic per floor and dividing by the number of sectors to be formed, average traffic per sector can be determined. Traffic volume for each formed sector is compared with the determined average traffic per sector. The frequency of service of elevator cars to each sector is variable, based on this comparison. Thus, sectors having a larger traffic volume are serviced more often, relative to sectors having a smaller traffic volume.
Abstract:
The present invention is directed to an elevator dispatching system for controlling the assignment of elevator cars. More particularly, the present invention is directed to a method of determining the commencement and/or conclusion of UP-PEAK and DOWN-PEAK periods of operation. For example, for commencing UP-PEAK operation, a lobby boarding count is predicted, based on historical information of the number of passengers boarding the elevators at the lobby. The predicted lobby boarding count is compared with a predetermined threshold value. If the predicted lobby boarding count is greater than the predetermined threshold value, UP-PEAK is commenced. In the preferred embodiment, the predetermined threshold value is a predetermined percentage of the building's population. Additionally, the present invention is directed to a method of adjusting the threshold value based on actual passenger traffic. For example, once UP-PEAK is commenced, the load of the first few elevators leaving the lobby within a predetermined time interval is determined, and the threshold value is adjusted based on their predetermined load. If the determined load is greater than a certain percentage of the elevator car's capacity, indicative of starting UP-PEAK too late, the threshold value is decreased. Similarly, if the determined load is less than a certain percentage of the elevator car's capacity, indicatve of starting UP-PEAK too soon, the threshold value is increased.
Abstract:
An elevator system employing a micro-processor-based group controller communicating with the cars to assign cars to hall calls based on a Relative System Response (RSR) approach. However, rather than using unvarying bonuses and penalties, the assigned bonuses and penalties are varied using "artificial intelligence" techniques based on combined historic and real time traffic predictions to predict the number of people behind the hall call, and calculating and using the average boarding and de-boarding rates at "en route" stops and the expected car load at the hall call floor. Prediction of the number of people waiting behind hall calls for a few minute intervals are made using traffic levels measured during the past few time intervals on that day as real time predictors, using a linear exponential smoothing model, and traffic levels measured during similar time intervals on previous similar days as historic traffic predictors, using a single exponential smoothing model. The remaining capacity in the car at the hall call floor is matched to the waiting queue using a hall call mismatch penalty. The car stop and hall stop penalties are varied based on the number of people behind the hall call and the variable dwell times at "en route" stops. The stopping of a heavily loaded car to pick up a few people is penalized using a car load penalty. These enhancements to RSR result in equitable distribution of car stops and car loads, thus improving handling capacity and reducing waiting and service times.
Abstract:
Elevator system with multiple cars ( 1-4 ) and a group controller ( 32 ) having signal processing means ( CPU ) controlling car dispatching from the lobby ( L ). During peak conditions (up-peak, down-peak and noontime), each car is dispatched and assigned to hall call floors having a large predicted number of passengers waiting on priority basis, resulting in queue length and waiting time at the lobby and upper floors being decreased, and system handling capacity increased. Estimations of future traffic flow levels for the floors for five minute intervals are made using traffic levels measured during the past few time intervals on that day as real time predictors, using a linear exponential smoothing model, and traffic levels measured during similar time intervals on previous similar days as historic traffic predictors, using a single exponential smoothing model. Combined prediction is used to assign hall calls to cars on priority basis for those floors having predicted high level of passenger traffic to limit maximum waiting time and car load. Noontime priority scheme is based on multiple queue sizes and percentages of maximum waiting time limits. Different waiting time limits can be used for lobby and above lobby up and down hall calls with automatic adjustment. During up-peak the lobby is given high priority. The lobby queue is predicted using passenger arrival rates and expected car arrival times. Down-peak operation uses multiple queue levels and percentages of waiting time limits, with estimated queues based on passenger arrival using car-to-hall-call travel time.
Abstract:
Elevator system with multiple cars ( 1-4 ) and a group controller ( 32 ) having signal processing means ( CPU ) controlling car dispatching from the lobby ( L ). During peak conditions (up-peak, down-peak and noontime), each car is dispatched and assigned to hall call floors having a large predicted number of passengers waiting on priority basis, resulting in queue length and waiting time at the lobby and upper floors being decreased, and system handling capacity increased. Estimations of future traffic flow levels for the floors for five minute intervals are made using traffic levels measured during the past few time intervals on that day as real time predictors, using a linear exponential smoothing model, and traffic levels measured during similar time intervals on previous similar days as historic traffic predictors, using a single exponential smoothing model. Combined prediction is used to assign hall calls to cars on priority basis for those floors having predicted high level of passenger traffic to limit maximum waiting time and car load. Noontime priority scheme is based on multiple queue sizes and percentages of maximum waiting time limits. Different waiting time limits can be used for lobby and above lobby up and down hall calls with automatic adjustment. During up-peak the lobby is given high priority. The lobby queue is predicted using passenger arrival rates and expected car arrival times. Down-peak operation uses multiple queue levels and percentages of waiting time limits, with estimated queues based on passenger arrival using car-to-hall-call travel time.