9.2.2.9 Reliability Benefits

Research and modelling of reliability benefits for transport appraisal has progressed significantly in the last few years. Evidence suggests that travellers value changes in excess travel time (i.e. late running) higher than changes in scheduled travel time.

The preferred measure of reliability is the standard deviation in travel time. The change in the standard deviation of travel time is then valued using the value of reliability, which is obtained by multiplying the value of time by the reliability ratio.

Due to the relatively immature nature of research on the valuation of reliability, these benefits should be identified separately from the standard TEE benefits, and not included as part of the core NPV or BCR.

Transport Scotland recognize that the calculation of reliability benefits can be resource intensive, depending on the modelling tools which practitioners have available. As such, it is important that the need to undertake an assessment of reliability benefits is properly scoped at Part One Appraisal, to ensure that the resource dedicated to the analysis is proportionate to the requirements of the study.

General Principles

Travel time variability (TTV) or Journey time variability (JTV) is defined as variation in journey times that travellers are unable to predict. These terms are used interchangeably.

Travel time variability is an increasingly important issue. Evidence suggests that travellers value changes in excess travel time (i.e. late running) higher than changes in scheduled travel time, thus journey time variability can influence modal and route choice. Travellers are sensitive to the consequences, such as prolonged waiting times, missed connections and arrival at the destination either before or after the desired or expected arrival time. This leads to an analysis in which the traveller is conceived of as choosing between travel alternatives each of which is characterised by a distribution of consequences, defined in terms of conventional generalized cost components (cost, travel time, etc.), together with the impact on timing constraints. The decision rule used to resolve choice in this situation has generally been some version of "maximum expected utility" (MEU) theory, in which travellers are assumed to choose the travel alternative that maximises the expected value of an appropriate defined utility function.

Measures of Reliability

Reliability is defined as variation in journey times that drivers are unable to predict. Hence reliability is confined to random effects. It arises from either variability in recurrent congestion at the same period each day - Day to Day Variability (DTDV) or variability in non-recurrent congestion such as incidents. It excludes predictable variation relating to varying levels of demand by time of day, day of week, and seasonal effects which travellers are assumed to be aware of.

Hence any calculations of changes in reliability must first remove the effects that are attributable to predictable variation. Once we are left with only unpredictable variation, the appraisal of transport schemes or policies should aim to place a value on any changes to this journey time variability because of the extra costs it incurs on drivers and passengers.

For most public transport journeys, the existence of timetabled arrival times means that it is usual to consider reliability in terms of lateness, defined as the difference between travellers' actual and timetabled arrival times. Adopting this definition means that arrival before the timetabled arrival time is usually ignored. This is based on the assumption that the operation of public transport generally acts to avoid early arrival. Two measures of lateness must be considered: average lateness; and the variability of lateness, measured by the standard deviation of lateness.

For journeys by private road vehicles (including road goods vehicles), it is reasonable to expect travellers to be aware of the average journey time, including variations caused by factors such as different traffic conditions at different times of the day. Thus reliability should be measured in terms of the unpredictable variability in travel times about these averages, measured by the standard deviation of travel time.

To estimate the monetised benefit of changes in the variability of lateness (for public transport) or of journey time (for private road vehicles), money values are needed. The concept of the reliability ratio enables changes in variability of lateness or of journey time to be expressed in monetary terms. The reliability ratio is defined as:

Reliability Ratio = Value of SD of travel time / Value of travel time
or
Reliability Ratio = Value of SD of lateness / Value of lateness

In addition, for public transport, the calculation of the monetised benefit of changes in average lateness also requires suitable money values. The value of average lateness may also be expressed in relation to the value of travel time:

Value of lateness = factor * value of travel time

Note that it is possible to estimate the benefits of changes in average lateness without also estimating the benefits of changes in the variability of lateness.

Evidence on values for these measures is of variable quality. However, some broad conclusions presented in the PDFH can be drawn, as follows: the value of average lateness for public transport is broadly the same as the value of time spent waiting for public transport, that is, 2.5 the value of in-vehicle time; the value of the reliability ratio ranges from 0.6 to 1.5 for public and about 0.8 for private passenger travel.

In order to use these results it is necessary to be able to specify how a transport intervention will affect public transport lateness and/or private vehicle reliability.

For multi modal studies, highway and public transport reliability should be appraised separately, employing the methods currently available for each mode.

Private Vehicle Travel

A key element used in a highway scheme appraisal is the expected average journey time on the day of the week and at the time of day in question. This can be complemented by an assessment of reliability, which may reflect:

• the consequences for subsequent activities should unexpected variability arise;
• the likelihood of encountering an incident which reduces capacity and
• other implicit effects which cause unreliability and variability in the average journey times.

Reliability can be measured by the standard deviation of journey time at a given time of day, or by the coefficient of variation (CV) which is defined as the ratio of the standard deviation of journey time to the average journey time. Either measure can be used when appraising proposals to improve the reliability of private vehicle travel.

Typically, road journeys that are repeated on a number of occasions are likely to take slightly less time than the average with a small number of trips encountering significant delays. The latter have a disproportionate impact on the standard deviation.

The Reliability Ratio expresses the value of variability of journey times, measured using the SD of journey time at a particular time of day, in comparison to the value of journey time. There is a limited amount of evidence on the values to be applied to the standard deviation of travel time - the 'value of reliability'. This comes from a variety of sources, but has usefully been pulled together through a workshop arranged by the Netherlands Ministry of Transport (The Value of Reliability in Transport, 2005). Using a standard value of time, the value of the standard deviation of journey times can be calculated using the recommend reliability ratio values below.

The way in which the change in the level of JTV is forecast will, in the light of current knowledge, vary according to the context. Different methodologies have been developed for inter urban motorway and dual carriageway roads, urban roads, and other roads, as discussed below. In appraising travel time reliability on highway schemes, it is important to distinguish whether the scheme being appraised is an Urban Road (defined usually as having a speed limit of 30 or 40 miles per hour) or Inter Urban Road (which usually have a speed limit of 50 plus miles per hour). On Inter Urban Roads it is also important to further distinguish between Motorway roads; Dual carriageway roads and single carriageway roads.

Inter Urban Motorway and Dual Carriageway Variability

Research (Arup, 2004) has shown that as long as demand is below capacity, incidents will be the main source of JTV, and DTDV is much less important except in urban areas where the two effects cannot be readily separated. The additional delays caused by congestion unrelated to incidents and any associated variability can be assumed to be allowed for in the journey time forecasts. However, in the case of delays due to incidents a separate element for average delays will usually need to be added to the variability element.

The research led to the development of a computer program INCA and associated advice note, which provides details of how to estimate the monetised benefits of measures affecting journey time variability covering incidents on motorways and dual carriageways. The model derivation assumes a dual carriageway layout and the parameters are based on data for motorways only. It is therefore not suitable for single carriageways, though the model may be used for dual carriageways as well as motorways. The resulting estimates of benefits cannot be taken to be as robust as those for time savings or accident reductions, for example. However, it is thought that a monetary benefit estimate will be of more value to decision makers than the qualitative score that can be presented in the Appraisal Summary Table. INCA reflects how delays caused by incidents vary according to the severity and length of the incident, the number of lanes blocked and the volume of traffic at the time. Changing the number of lanes available to traffic changes both the probability of encountering an incident (or its aftermath) and the delays caused by incidents

For motorways and dual carriageways, alternative routes avoiding particular sections usually have limited capacity making it difficult for large numbers of drivers to divert if they encounter delays due to an incident. In the absence of significant "transient excess demand" (temporary periods of demand exceeding capacity), incidents are the main source of unpredictable variability and the methods set out in the INCA advice should be used. However, it is important to note that the research underlying this advice currently incorporate what are intended to be conservative assumptions, which will be refined in due course.

Urban Road Variability

Models predicting journey time variability from all sources have been developed for urban areas. In such areas alternative routes are more readily available than on motorways and there are many ways for drivers to divert away from incidents which reduce capacity on a particular route. This affects the relative importance of incident and day to day variability (DTDV) effects.

Initially models were developed for the London Congestion Charging study in 1993. These were modified using additional data collected in Leeds (2003) with these improvements reported in Arup (2004). In 2007, Hyder Consulting in collaboration with Ian Black and John Fearon were commissioned by the DfT to further develop the travel time variability relationships for a wider sample of urban routes. Theses routes are spread over the 10 largest urban areas in England as identified in DfT's Public Service Agreement (PSA). The analysis in the research was based on ITIS/CJAM (Congestion and Journey-time Acquisition and Monitoring System). The form of model developed forecasts the Standard Deviation of Journey Time from Journey Time (t) and Distance (d) for each origin to destination flow. Under the further assumptions that distances and free-flow speeds do not change as a result of the scheme, the change in journey time variability (represented by Δσij) is given by:

The reliability benefit applying the rule of a half is therefore calculated using:

 
Note that the value of reliability (VOR) is obtained by multiplying the value of time by the reliability ratio and Tij1 and Tij2 are number of trips before and after the change
Although the model above can be used to estimate the effect of schemes and their reliability benefits in urban areas, a locally calibrated model or at least a local validation is preferable.

Other Road Types

For journeys predominantly on single carriageways outside urban areas, it is not currently possible to estimate monetised reliability benefits. Instead, the assessment of changes in reliability should be based on changes in 'stress', the ratio of the annual average daily traffic (AADT) flow to the Congestion Reference Flow (a definition of capacity). Reliability of road journey times is believed (on the basis of work carried out for DfT's ITEA Division) to decline as flows approach capacity. Thus, 'stress', is, with some limitations, considered to be a reasonable proxy for reliability. Detailed advice on stress, including the definition of Congestion Reference Flow, is provided in DMRB Vol 5.1.3.

A worksheet is provided so that values for improved reliability can now be calculated and results presented in a consistent manner.

Experience to date has shown that schemes which reduce congestion, by reducing the journey time spent queuing, also reduce the variability of journey times. The effect is largest on motorways operating nearest capacity. The effect is less in urban areas, because more alternative routes are available in urban areas.

Public Transport

Valuation

It is likely that some passengers, particularly infrequent travellers, will be unaware of predictable variation. Indeed evidence from the Passenger Demand Forecasting Handbook (PDFH) for rail suggests that only 25% of passengers are aware of advertised delay. For those passengers unaware of this predictable delay the increase in journey time can be treated as unpredictable variation.

This is equivalent to a lateness factor of 2.5 for all advertised delay. This is because the predictable and unpredictable lateness factors (1 and 3 respectively), when weighted according to the 25/75 split, produce an average lateness factor of 2.5. In the absence of similar evidence for private travel the following recommendation applies only to rail travel.

Theory and practical constraints

For projects where passenger performance improvements are to be fully assessed, a detailed reliability assessment should provide evidence on how improvements in reliability are to be achieved and the expected consequential effects within the principles set out below.

Due to the existence of timetables for public transport the analyst should focus on delay, rather than journey time in appraising reliability. This practical constraint comes from the rail industry performance data and not from something inherent in all public transport. For rail we use the term performance to capture the impact of both punctuality and reliability. Punctuality concerns whether trains arrive at their scheduled time. When a train fails to run, or does not stop at all its scheduled destinations, it is said to contribute to unreliability (the rate of cancelled trains).

In contrast to the private road transport, where the traveller has the possibility of continuous adjustment of his departure time, most public transport is characterised by the existence of a timetable, with only discrete possibilities for departure. As can be expected, this leads to further disutility associated with the service interval. The disutility resulting from discrepancies between Preferred Arrival Time (PAT) and scheduled arrival time would exist even with 100% reliability, therefore the costs associated with discrete departure times can effectively be ignored when valuing the effects of a change in reliability. When public transport timetables do not correspond well to the timing of an individual user's activities (i.e. their PAT), some travellers may actually find the variation beneficial.

Ideally valuation of reliability would be based on the difference between the passenger's PAT and their actual arrival time. However we have very little knowledge about passengers' PATs. For this reason we adopt the scheduled arrival time of a service as a proxy for the passenger's PAT. It is the difference between scheduled arrival time and actual arrival time which is used to measure a passenger's delay.

Consequences of delay from a rail perspective

Disutility from unpredictable variation has two elements. The first and most significant element is the consequences of arriving late (missing meetings, unproductive use of time, etc). This is measured using mean delay and valued by applying the appropriate lateness factor. Mean delay cannot be interpreted as a component of journey time because of its uncertain nature. Mean delay should contain only unpredictable delay. Any predictable delay should be removed from the calculation and treated as additional journey time.

Research has assessed the perceived weighting of lateness relative to in-vehicle time in order to place a value on the consequences of arriving late. Estimates of the value of this lateness factor vary between 1 and 5, according to a number of variables such as the type of service and the journey purpose.

Variation in delay

The second element of disutility arises from the additional cognitive burden of unpredictable variation and can be described as the intrinsic irritation factor arising from variation in arrival times. This is most accurately measured using the standard deviation of journey time and valued according to the appropriate reliability ratio.

The reliability ratio allows us to represent the variability of delay, measured by the standard deviation of delay, in terms of an equivalent change in mean delay. The recommended reliability ratio values are shown below:

If the reliability ratio has a value of, for example 0.5, then a 1 minute reduction in the standard deviation of delay is equivalent to a 0.5 minute reduction in mean delay.

Given that it is rare that we ever have a complete knowledge of the delay distribution with which to calculate the standard deviation of journey time an alternative method can be used. Research by Bates et al has suggested that it is the "pure" lateness effect which tends to dominate the calculations, because the effect of variability is less important given that rail passengers have already made some "compromises" in selecting arrival or departure time of their preferred scheduled train. Indeed, as noted earlier, some travellers may find that variability brings them closer to their preferred arrival time than an "on-time" arrival would. Consequently a 20% uplift of the lateness factor is an acceptable proxy for the additional disutility incurred as a result of variability in delay.

Lateness Factor

Therefore a central lateness factor of three, which includes the uplift of 20% for a change in variability, should be used in the general case. Where sufficient evidence can be provided to justify the application of a different lateness factor a value higher or lower than 3 should be adopted. In the general case one minute of average lateness is valued by passengers as being equivalent to three minutes of scheduled journey time. This conversion to scheduled journey time allows us to place a monetary value on reliability using the appropriate value of time.

Where no delay data is available for an intermediate station the analyst should use delay data from the final destination. In this case it may be appropriate to use a different lateness factor. But a robust rationale should be provided for any departure from the recommended central factor of 3.

Early Arrivals

The theory of Bates et al states that early arrival contributes to variability. They recommend that early arrival is given the same weight as late arrival but the opposite sign. Early arrivals are recorded but not included in the Public Performance Measure (PPM). It is therefore recommended that early arrivals are treated as on time and, as a result, excluded from calculations of mean delay and variance of delay. It is recognised that this is not the ideal theoretical approach, or the method outlined by Bates et al, but that it represents a pragmatic approach.

Reliability

A measure of rail performance must also examine the rate of cancelled services or reliability. To make allowance for the total lateness caused by cancelled trains we usually multiply the service interval by 1.5. This cancellation factor is in line with the notion that in this case the delay impacts on waiting rather than in-vehicle time. Waiting time incurs higher disutility than in-vehicle time because of the additional discomfort involved. The resulting lateness should then be multiplied by the lateness factor of 3 to capture the full costs of poor performance.