System Capacity and Performance
The capacity of capacity of 2getthere’s CyberCab PRT system depends on the configuration of the system, the vehicle capacity and average occupancy, average cycle time (driving + dwell time), minimum required headway and empty vehicle movement. In true-PRT configuration the capacity will range between 2,500 and 3,000 pphpd, while higher capacities can be achieved by implementing a smart infrastructure configuration, intelligent scheduling and introduction of a ride-sharing concept.
The CyberCab PRT vehicle accommodates a 6-person family (4 adults, 2 children). In a true-PRT configuration, the average occupancy of a PRT vehicle is likely to be similar to regular traffic (±1.5 passengers per vehicle). However, the average occupancy and thus the hourly capacity could be increased by introducing (Single Origin, Multiple Destinations) ride-sharing. Note: this is especially valid for peak hours, when the higher average occupancy is not off-set by a longer dwell-time of the vehicles in the stations to allow additional passenger to arrive (and board).
The station dwell-time and the trip time are minimized to optimize the system capacity and fleet-size. To minimize dwell time, a fast (safe and reliable) door-mechanism is required as well as a station configuration allowing multiple, independent berths (as designed by 2getthere). A high average speed, to minimize trip time, is achieved through rapid acceleration (within the limits of passenger comfort and the restrictions of the infrastructure) and a considerable maximum speed (40km/ph).
The minimum required headway (distance between two vehicles) determines the possible throughput of vehicles per hour. To allow for a complete standstill of a trailing vehicle for an instantaneously stopped vehicle (brick-wall stop) a 4 second headway is required (at 40km/ph). However, as an instantaneous stop is not possible, the PRT system can operate at a shorter headway – comparable to the 2 second headways used by cars.
A smart infrastructure configuration is required to ensure minimum driving times between the main locations within the network. Strategic buffer locations and possible short-cuts need to be identified and set-up. The smart configuration also concerns stations and especially (the length of) their ramps. These can influence the merging speed and the operations – and thus system capacity – considerably.
Intelligent scheduling based on known transportation patterns can be used to optimize empty vehicle movement – ensuring vehicles are there where transportation is requested. By minimizing the empty vehicle movement, the system capacity is optimized.