Taxi Driver Online

That's an interesting question.

Basically 80 is the end calculation that Halcrow deem to be the number that indicates SUD or not.

Now I haven't a clue why that number shouldn't be 50 or 150, but the likes of Halcrow need a base, and if anyone asks them they will say through experience.

And it will cost someone £20-50,000 to prove them wrong.

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IDFIMH

But what does the number 80 equate to? Is it 80 passengers that can't get a taxi? Or 80 chickens crossing the road? Or could it be egg fried rice on the chinese takeaway menu?

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Grandad,
To support my charity text MAYORWALK to 70085 to donate £5

Extract from Brum's Taxi Demand Survey 2010;

Latent demand

According to DfT guidelines, latent demand should be considered in the calculation of taxi demand. However, on the basis of the findings of the 2008 survey, which showed that there is oversupply of HCV’s, it is difficult to justify the cost of undertaking another public attitude survey for this purpose so soon after the previous one. Furthermore, case law (Brighton 15) indicates that latent demand need not be considered when measuring unmet demand. Hence this proposal focuses on patent demand.

(Brighton 15) The 1989 case R v Brighton Borough Council ex p. Bunch (C.O.D. 558) found that the authority need only look at patent demand, and need not consider latent demand in the market place. Also, the authority should limit its consideration to demand for licensed taxis. It is not obliged to consider the presence or absence of PHVs in the market.

_________________
Kind regards,

Brummie Cabbie.

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You asked the question Mr Grandad & here's the answer!!

See if you can understand it; it's just a long calculation that ends in an index number & if that number is greater than 80 there is a SUD.

EXTRACT FROM BRUM'S TAXI DEMAND STUDY 2010;

Appendix 1: Index of Significant Unmet Demand (ISUD)

The Index of Significant Unmet Demand (ISUD) is generally regarded as the standard measure for unmet demand. The ISUD is a formula comprising of the product of six measures which are shown and explained below.

ISUD = APD x PF x GID x SSP x SF x LDF

The ISUD was first developed in the 1990s, modified in 2003 when a seasonality factor was added to the algorithm, and again in 2006 when the latent demand element was added to reflect DfT’s guidance on its inclusion in studies.

The index has two principle components:

• Patent demand, which is measured using rank observation data; and
• Latent demand, which is established through the assessment of rank observation data and a public attitude survey

The first five of the following six measures quantify patent demand and the sixth establishes latent demand. When the index value is greater than 80, significant unmet demand is present.

APD: Average Passenger Delay = 0.2
Calculated across the entire week, this is the average of all the observations. This has been entered into the equation as a unit in minutes.

PF: Peaking Factor = 1
This is a weighting element used to provide dispensation for the effects of peaked demand on the ability of the trade to meet that demand. High peaking is generally identified by night time demand (at weekends), this being substantially higher than demand at other times. Where passenger demand is significantly higher at night then PF=0.5, otherwise PF=1.

GID: General Incidence of Delay = 10.25
The proportion of passengers who travel when the delay (or queuing time) is greater than one minute (calculated to be 10.25%).

SSP: Steady State Performance = 1.05
A measure of performance during “normal” hours; quantified by the proportion of hours during weekday daytimes (10:00 – 16:00) when passengers queue at ranks (calculated to be 1.05%).

SF: Seasonality Factor = 1
This is a factor that takes account of the effect of seasonality. A value of 1 is attributed to the months of September through to November, and for March to June (considered “typical” months); 1.2 for January and February and the longer school holidays (where demand tends to drop); and 0.8 for December (taking account of the pre-Christmas rush of activity).


LDF: Latent Demand Factor = not measured within this study
This is a measure of the proportion of the public who have given up trying to obtain a HCV during the previous three months, derived from a public attitude survey.

Research by Design’s observations have determined that only a very small minority of passenger delays are due to there being no taxis available. However, the data inputted into the formula below is based on all waiting / passenger delay data, including those due to passenger surge and not insufficient taxis.

ISUD = 0.2 x 1 x 10.25 x 1.05 x 1
ISUD = 2.15

The cut off level for significant unmet demand is 80. It is clear that Birmingham is far below this cut of point and thus there is no significant unmet demand.

The table below details the ISUD across time of day. In none of the day parts does the ISUF reach the 80 cut off level. Morning sees the highest ISUD, driven by a higher General Incidence of Delay (GID).

Total 2.15
Morning 6.56
Day 0.83
Evening 1.35
Night 1.18

If based on only the delays due to no taxis available:

APD: Average Passenger Delay = 0.01
Calculated across the entire week, this is the average of all the observations (including those where there were no passenger delays). The average delay is based only on those delay caused by no taxis being available at the rank. As the incidence of this across all observations is so low, the APD is a particularly small number. This has been entered into the equation as a unit in minutes.

PF: Peaking Factor = 1
This is a weighting element used to provide dispensation for the effects of peaked demand on the ability of the trade to meet that demand. High peaking is generally identified by night time demand (at weekends), this being substantially higher than demand at other times. Where passenger demand is significantly higher at night then PF=0.5, otherwise PF=1.

GID: General Incidence of Delay = 1.3
The proportion of passengers who travel when the delay (or queuing time) is greater than one minute due to there being no taxis available (calculated to be 1.3%).

SSP: Steady State Performance = 0
A measure of performance during “normal” hours; quantified by the proportion of hours during weekday daytimes (10:00 – 16:00) when passengers queue at ranks (there are no incidences of this in weekday daytimes).

SF: Seasonality Factor = 1
This is a factor that takes account of the effect of seasonality. A value of 1 is attributed to the months of September through to November, and for March to June (considered “typical” months); 1.2 for January and February and the longer school holidays (where demand tends to drop); and 0.8 for December (taking account of the pre-Christmas rush of activity).

LDF: Latent Demand Factor = not measured within this study
This is a measure of the proportion of the public who have given up trying to obtain a HCV during the previous three months, derived from a public attitude survey.

Research by Design’s observations have determined that only a very small minority of passenger delays are due to there being no taxis available. However, the data inputted into the formula below is based on all waiting / passenger delay data, including those due to passenger surge and not insufficient taxis. If passenger surge delays were omitted from the formula, the output would be reduced.

ISUD = 0.01 x 1 x 1.3 x 0 x 1
ISUD = 0

The cut off level for significant unmet demand is 80. It is clear that Birmingham is far below this cut off point and thus there is no significant unmet demand.

_________________
Kind regards,

Brummie Cabbie.

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