What is CUBE Analyst?
CUBE Analyst is a program which estimates an origin-destination (O-D) trip matrix. It is an optional, standalone and separately licensed module in the CUBE suite.
CUBE Analyst estimates one matrix at a time, and the data should form a set related to this particular matrix; that is, the data should correspond to the same time period (hour(s) of day, day of week, time of year) as the matrix. It should also correspond to the same units of flow as the matrix (vehicles, pcu’s, passengers, etc.).
The characteristic common to all estimation options offered by CUBE Analyst is that they make the best use, in a flexible way, of commonly available data sources to contribute to the estimation process.
Data is given levels of confidence or reliability by the user which conditions the influence of varying sources of data in the estimation. The estimation process is based on the maximum likelihood technique, coupled with an optimization procedure.
Common elements and variations
Conventions used in this document
This document applies to all levels of functionality offered and modes of operation of CUBE Analyst. Features specific to a variant are noted.
This document concentrates on CUBE Analyst; wider matters on matrix estimation, and the context within which CUBE Analyst may be used, are described in the Introduction to the Matrix Estimation Programs. This also explains the terms which have a specific meaning for CUBE Analyst which are also used in this document.
CUBE Analyst can now estimate CUBE Voyager Public Transport matrices by using an intercept file output by the CUBE Voyager PT program.
CUBE Analyst enables transport planners to estimate origin-destination (O-D) trip matrices and to maintain the currency of existing O-D matrices, while minimizing survey costs.
As is described in Introduction to the mathematics in CUBE Analyst, CUBE Analyst is suitable for estimating present day matrices, but not for forecasting future year trip matrices.
The software contains a number of novel and distinctive features. It was first developed as a collaborative venture with the Dutch Ministry of Transport, the Rijkswaterstaat. Subsequently, studies and developments undertaken for Centro (the Passenger Transport Executive for the West Midlands area of England) led to a broadening of the software’s capabilities to consider public transport passenger matrices, as well as highway (vehicle) matrices, and to estimate detailed matrices for very large study areas.
Common elements and variations
The characteristic common to all variants of CUBE Analyst is that they make the best use, in a flexible way, of most available data sources in the estimation process. This includes not only vehicle traffic or passenger flow counts and prior (old) matrices, but also partially observed matrices, zonal trip end (generation and attraction) data, vehicle routing, travel cost matrices, and even previously calibrated trip cost distribution functions. An extension is the use of a further form of data called part trip data, described in Part-trip data .
Data is ascribed confidence, or reliability levels by the user. This conditions the influence of data when different data items (inevitably) imply different trip matrix cell values. The estimation process is based on a statistically rigorous procedure which takes direct account of inherent traffic data variability. It uses the maximum likelihood technique, coupled with a powerful optimization procedure, to derive simultaneously an unusually large set of model parameters. These then determine the estimated trip cell values with correspondingly enhanced precision.
Nevertheless, the estimation process remains mathematically underspecified and a feature of CUBE Analyst is the information available to assess the quality of the estimated matrix. This includes comparative and sensitivity analyses, and reports which draw on a range of graphical and tabular presentations. Statistical reports are available which provide information on the standard errors of model parameter values, and indicators of the stability of estimated trip matrix cells (via a sensitivity matrix).
CUBE Analyst provides a hierarchic approach to estimation, suited for use with very large matrices, typically, between 2,500 and 5,000 zones in size. Its basic approach is to estimate a general matrix, in which zones are automatically grouped into districts. This area-wide estimation is then used to control a set of detailed estimations, which build up to provide a fully detailed estimate for the entire study area.
The introductory chapters provide:
•An overview of CUBE Analyst
•A set of Standardized Procedures, suitable for different types of estimations
The document considers estimation of highway and public transport matrices and all of the CUBE Analyst features.
Highway and public transport estimation are very similar, apart from obvious differences such as the use of line (service) data for public transport. There are also differences in emphasis, for example, count data is often more plentiful and reliable for highways than for public transport. Where such differences arise, they are noted.
When reading this document note that:
The next four chapters provide an essential overview of CUBE Analyst
•Chapter 6, Estimation Process documents an example of applying CUBE Analyst
•Chapter 7, Hierarchic Estimation is concerned with the specialist topic of hierarchic estimation
Conventions used in this document
The following conventions are used in this document:
•Parameters, options, and selections appear in upper case.
For example: COSTM
•Technical term introduced for the first time, in upper and lower case italics.
For example: Hessian
•Terms and phrases with particular meaning in the context of CUBE Analyst in quotes. These phrases may also appear in italics.
For example: Sensitivity Matrix
CUBE Analyst is a major system. The programs ensure that the mechanics of operation for the user are straightforward, but it requires familiarity with a number of programs, especially for data preparation and analysis of results, and this should be taken into account when planning to use it for the first time.
CUBE Analyst is designed about a number of rigorous principles, including the calibration of the mathematical estimation model which the program undertakes. One consequence is that it is computationally intensive; the differing sets of data are considered simultaneously and this requires the availability of relatively large amounts of random access memory (RAM), memory, and of disk space.
For highways, cost data is produced by Bentley products.
For public transport in TRIPS, cost data is produced by MVPUBM