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The components of induced trafficAny increase in demand which follows a reduction in price or improvement in level of service could be regarded as induced traffic but the term is usually reserved for that increase which is not explained simply by rerouting. This convention has no logical justification and is the result of the historical accident whereby analysts often had a model which was only expected to predict rerouting and so any other behavioural response was "extra". The various components of induced traffic can have very different implications for scheme appraisal. It is therefore necessary, when considering how one might go about measuring induced traffic, to consider all the dimensions of response rather than that arbitrary subset which are not reflected in conventional modelling exercises.
Major problems hindering the measurement of induced traffic
1. Noise and variability in the data
Any measure Some of this is due to measurement errors and some to the inherent variability of the phenomena.The extent of measurement error is generally fairly predictable for any particular survey methodology applied in a given context and so can easily be allowed for. If appropriate equipment is used and survey procedures are correctly adhered to, this source of error can be negligible.
Traffic flows vary from hour to hour, from day to day and from month to month. Some of this variation is associated with predictable cyclical patterns and may apparently be encapsulated in typical daily flow profiles and seasonal adjustment factors (see, for example DoT 1979). In practice, however, each site will have its own cyclical patterns which will not precisely match the national average figures which are widely used in the analysis of traffic data.
Traffic flows also vary as a function of special events and weather conditions affecting the site. These special factors, if recorded, can help to remove "noise" from the data but there will always remain an unexplained residual variation. The extent of this residual will vary from site to site.
Best practice will, of course, be to remove all the explainable variation and, by examining time series data at the site, to quantify the unexplained residual (e.g., as a coefficient of variation) and to use this to determine confidence limits for estimates of flow. Where this is not practical, coefficients of variation from comparable sites should be used.
2.Attribution of cause
Even if it is possible to deduce the amount of extra traffic associated with a policy intervention, it may not be possible to conclude whether it is caused by the intervention. We may be able, on statistical grounds to rule out the possibility of pure coincidence (or more accurately we will be able to show that the possibility of it having happened by chance is very small) but it is still possible that the increase may be associated with the specific policy intervention without being caused by it. The real "cause" may be a wider programme of improvements which the specific policy intervention is only one element. Thus, for example, the opening of a new stretch road may be part of a wider programme of n广告ork improvements (e.g., a strategic route) or may be part of a programme of measures designed to boost the local economy -other elements of which might be the provision of development incentives, a relaxation of planning controls or a major publicity campaign. In any such case it would be extremely difficult, unless a suitable control site can be identified and monitored, to establish how much of any extra traffic is attributable to the new link.
The role of models in the measurement of induced traffic
Mathematical models can assist our estimation of induced traffic in various ways; a previous section has outlined the use of matrix estimation software to deduce O-D matrices from traffic counts while Coombe (1995) will review the use of travel demand models to make direct estimates of induced traffic.The current section is concerned with the use of travel demand models to assist in the targeting of survey effort.
A fairly conventional travel demand model (e.g., a four stage modestudy area and, by allowing the trip matrix to respond to changes in line with plausible elasticity values, changes in link flows could be predicted . Roads showing the greatest net change in flow would be the ideal locations for traffic counts while those showing the greatest change in flow composition (e.g., as revealed by a "select link" analysis of O-Ds contributing to a given flow) would be the ideal locations for roadside interviews. The zones with the greatest change in total origins, or in distribution to different destinations, would be the best locations for household interviews.
Provided that the models' elasticities were at least as high as they "should"be, their actual value would not be crucial because our interest here is not in the magnitude of the changes predicted by the model, but in the sites where these changes are most likely to be apparent. Provided that the model has a good representation of the n广告ork and adequate elasticity values it should be able to focus our attention on the most significant survey sites. If effects cannot be found at those sites they are unlikely to be found anywhere.
Current practice
Case studies have indicated that a programme of surveys designed to identify all the components of induced traffic might easily cost in excess of 1/4 million pounds (Bonsall 199 I) and even then would probably not succeed in producing incontravertable evidence. It is therefore quite understandable that transport planning agencies have not been keen to undertake such studies. The more common approach has been simply to arrange for counts to be taken on the scheme link and, perhaps one or two parallel links before and after opening.This can normally be achieved for under twenty thousand pounds, but is often insufficient to distinguish b广告een rerouting, rescheduling and other responses and so is of very limited value in quantifying induced traffic. Typical features in such monitoring programmes are the absence of adequate control sites and the use of insufficiently long screenlines. This makes it difficult or impossible to identify rerouting, let alone the other components of induced traffic, with any confidence.
The main concern of current monitoring activity seems to be to compare forecast demand with outturn demand on the scheme. In this respect it reflects official guidance (DoT 1979 et seq) and an underlying concern to ensure that public money is being wisely spent (NAO 1988), rather than an interest in the extent and nature of any generated traffic.
Recent analysis of the results of such surveys (e.g. Harris 1993) have shown that forecasts which ignored any possible generation of new traffic have, in practice, overpredicted flows at the scheme as often as they had underpredicted them. It is tempting, but misguided, to interpret this as evidence that generated traffic is unimportant. Nor would it be correct to label as "induced" any traffic observed in excess of that predicted by an assignment-only model; discrepancies b广告een the model prediction and outturn flows often have more to do with failures to anticipate the economic cycle than with the adequacy of the models used.
If the extent of induced traffic is to be quantified then more effort and resources will need to be devoted to the necessary surveys than is currently the case.
评论
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