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Thursday , 20 June 2024

Better Origin Destination Surveys

Good Origin Destination Surveys are key to planning better and more effective transport infrastructureGood Origin Destination Surveys are key to planning better and more effective transport infrastructure

Quite often governments plan transport infrastructure, based on prospects suggested by construction companies, product integrator or simply ?obvious need?. As the country progresses, it is necessary to make these decisions based on more accurate appraisal of potential demand; this is essential for publicly funded projects as well as for those implemented by the private sector, for example toll roads. Basic data like traffic counts and Origin Destination surveys are the foundation of improved decision making in this field.

Take, for example, the simple section of a road network in Figure 1 where the blue lines represent existing roads connecting settlements, the letters U to Y junctions and the numbers are hourly traffic counts. If the project involves paving and widening road section U-Y, then the counts may be enough to justify the reduced delays and operating costs. However, this improvement may also attract trips from A to D that beforehand use a route via V and X. In this case traffic counts will not be enough to estimate future conditions on the improved link. This is particularly important if the project is a completely new link, for example, the dotted red line. Were it to be tolled, what would be the new traffic on link U-X and how much revenue would the toll generate? A problem like this requires a comprehensive data collection effort including an Origin Destination Survey, OD survey for short.

OD Survey

The objective of an OD survey is to identify and quantify all possible trips that may be attracted to a new (or improved) transport link. In the case of our hypothetical toll road, the most important of these trips are those from A and B to D and E, as illustrated.

One needs to ascertain how many trips are undertaken by vehicles between these locations and also on some of the characteristics of those trips, for example the willingness to pay tolls to save travel time. In this article we will only focus on the methods to estimate the number of trips.

As shown, it is possible to intercept all (reasonable) trips between A and H and D and E at the locations [1] and [2]. In order to find out details of the journeys, one can use active or passive methods. An active method usually involves intercepting a trip, often at the roadside, and asking travellers at least about their Origin, Destination and Trip Purpose. Sometimes it is possible and desirable to also find out about the income level (as it will be related to the willingness to pay tolls) and the party who is paying for any tolls (it could be the company the traveller works for and this will increase the willingness to pay). One must be very careful not to add questions that will not be used later in the analysis: each additional question over origin-destination-purpose has an effect on the result ? it is likely to deteriorate the quality and reliability of the responses.

In order to undertake roadside interviews, it is necessary to inform the traffic police (and sometimes other authorities) and get their permission to stop traffic; this usually requires their assistance too. On busy roads it will not be possible to stop all vehicles. So a sample will be taken to reduce delays and complaints. In some urban locations, it is often possible to take advantage of natural stops at traffic lights and undertake a quick interview whilst drivers wait for the green signal; the police and authorities must be informed about the survey in advance.

There are also a number of passive methods that rely on simple observation. For example, one can locate observers at the junctions U and X and get them to record the number plates and times of vehicles crossing the junctions (you will need more than one observer per site). This task has to be undertaken simultaneously at all relevant junctions and may be supported by video recordings to enable the annotation of number plates at an office. Once the timed number plates (in five or ten-minute time slots) are recorded the analyst will match observed vehicles building up one or more Origin Destination matrices; this task is usually undertaken by a computer programme that may allow for minor errors in recording numbers and times.

Today, it is also possible to undertake this vehicle-matching task using radio-detectors, for example Bluetooth. There are problems with this type of technology though: the sample depends on the number of active devices, at any one time, on the vehicle or person. For Bluetooth devices, sample rates are generally low, between 5% and 20% and they lead to additional problems when they are switched on or off during the journey. Of course, in the case of passive methods, one must infer the journey purpose and it is not possible to ask about the willingness to pay.

The objective of an Origin Destination survey is to identify and quantify all possible trips that may be attracted to a new (or improved) transport link.

Another method adopted in large cities is to undertake a Household Travel Survey, similar to a Census but asking questions about travel to a sample of the population – usually between 1% and 3% of the households are interviewed. This is an expensive and complex undertaking that requires extensive planning and pilot testing. Questions are asked about household composition, vehicle ownership and license holding as well as all trips undertaken a previous day by each member. This provides a very rich data source necessary to plan urban transport schemes. Despite its advantages, a 3% sample of trips is a poor basis to generate trip matrices and therefore Household Travel Surveys are usually complemented with intercept surveys as those mentioned above.

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