Too often we are bombarded with statistics, numbers that are supposed to describe the state of things. This is especially true in transportation and traffic where there seems to be a lot of information or data circulating about all kinds of stuff usually including numbers of vehicles, speeds, quantities of people and goods transported, and so on.
There is a tremendous amount of data collected by many government agencies. These include traffic counts by the DPWH, port and airport statistics by the PPA and CAAP, and socio-economic data from all over the country by the NSO. There is also wealth of information that can be derived from various project reports whether these be infrastructure master plans or evaluations of policies and programs related to transport and traffic. Local governments that require transport impact studies for developments within their jurisdictions are supposed to compile the data contained in these reports, which include traffic counts and projections at roads and intersections, transport facilities inventories, and travel time and delay data among others essential for impact analysis.
Origin-Destination (OD) data are important for planning transport from the national to local levels. Inter-regional, inter-provincial or inter-city OD data for people and freight are essential for planning infrastructure that would be able to adequately and efficiently handle the traffic between regions, provinces and cities/municipalities. As it is impractical (i.e., costly) to determine the exact numbers of traffic for all modes on a very frequent basis, sampling is very important and the determination of sample size as well as the sectors and areas to be sampled are essential aspects of any study. The current MMUTIS Update and Capacity Enhancement Project (MUCEP) that is the long-delayed follow-up to the Metro Manila Urban Transportation Integration Study (MMUTIS), for example, required household information surveys (HIS) for an area that is now referred to as Mega Manila, which is basically comprised of Metro Manila, Region 3 and Region 4A. Such a large study area necessitates careful sampling in order for assumptions regarding the data aggregation and disaggregation to hold.
Often, for many studies concerning cities and regions, person trip and freight volume data are more valuable than vehicle trip data. Though vehicle volumes are important, the number of people traveling or the amount of goods being transported are a better basis for planning transport. This is especially true for passengers as it is desirable to have the numbers as the basis for determining the frequencies (how often and with what schedule) and capacities (vehicle size/passenger capacity), which need to be balanced or optimized according to the demand. This demand is variable throughout the year and the day and will definitely have implications on revenues. There are desirable schedules for passengers as well as for goods. Moreover, it is important to determine also the trip distances that would allow for the estimation of the number of trips in terms of passenger-km and ton-km units. Such information are useful for travel demand modeling and forecasting including the evaluation of suitable transport modes and service characteristics for passengers and freight.
[to be continued]