REGLAS FUNDAMENTALES DE SEGURIDAD
DIAGNÓSTICO SOFTWARE
The user-cost factors are the constant values, independent on traffic flows and network performance, that are used in the benefits analysis for all project alternatives and all scenarios. For this research project the factors are: value of time (VOT), vehicle occupancy and the costs of accidents.
4.5.2.4.1 VALUE OF TIME
“The value that [road] users assign to their travel time will depend upon the opportunity cost of that time, and the consumption opportunities that the users associate with travelling.” (AASHTO, 2010) This opportunity value is attributed to one hour of a road user’s time, and is expressed in ZAR/h. Since work is an alternative use of time, especially in the commute travel context, the opportunity value is normally linked to an hourly, after-tax wage rate. Other determinants, such as mode and distance as well as distance, have also been used. In this case study, however, no differentiation between the VOT for motorists and cyclists was made.
The User and Non-User Benefit Analysis for Highways manual (AASHTO, 2010) recommends the following VOTs:
- Driver alone commute → 50% of wage rate - Carpool driver commute → 60% of wage rate - Carpool passenger commute → 40% of wage rate
In the Netherlands, an hour lost by an employee in traffic is also calculated as half of the average hourly salary (Buis et al, 2000). In South Africa, on the other hand, a proportion of 0.25 for the wage rate is often used. As a result of these differences, the sensitivity analysis was performed. A proportion of 0.5 was assumed for the start.
Page | 102 As the statement above suggests, VOT varies for different road user types and / or trip purposes. School learners have a VOT that differs to that of their parents (with differences also between parents), and SU students again have a different VOT to SU staff.
The average VOT of the school learners was taken as zero. In the surveys distributed to the school parents, the parents were asked to give their household’s annual income. These specified incomes were used to first compute the average income of all the households, and then determine the VOT of the school parents (see Table 4.9). The income range relates to the income groups that the respondents could choose from and the frequency refers to the number of responses received for each of these groups. It was assumed that there are 250 working days in the year and 8 working hours in a day. The average hourly wage for the school parents (per household) is ZAR384.47. The VOT thus is ZAR190.00, with rounding. It was assumed though, that this VOT only applies to 0.25 of the drivers who drop their children at school. For the other, i.e. non-working, parents and SU students, the per capita income of South African citizens was applied. This income was calculated by adding the last four quarterly national nominal GDP estimates given in the respective quarterly GDP reports, compiled by Statistics South Africa, and then dividing the sum by the total South African population (see Table 4.10). This value was then furthermore divided by the total number of hours in a year to determine the VOT; no further proportion of 0.5 was applied. With rounding, the answer came to ZAR8.00/h. The average VOT of SU staff was calculated from the average salaries of SU employees taken from PayScale (updated 4 July 2015) and shown in Table 4.11. The average hourly wage for SU staff (assuming an equal proportion of commuters for each job) is ZAR116.27, which, with rounding, results in an average VOT of ZAR60.00/h. For the other commuters on the road network, i.e. the general commuters, this same VOT was applied, as it seemed like a fair balance between the low per capita average income and the high average income of the school parents.
Table 4.9: Average income calculation for the school parents of Bloemhof Girls' High School, Paul Roos Gymnasium and Rhenish Girls' High School.
Income range Mid-value, ui
frequency BGHS,
fBGHS
fPRG fRGHS ftotal ftotal × ui avg.
ZAR0 to ZAR100k ZAR50k 4 13 7 24 ZAR1,2 mil
ZAR768,931 (annual) ZAR384.47
(hourly) ZAR100k to ZAR350k ZAR225k 48 48 25 121 ZAR27.23 mil
ZAR350k to ZAR650k ZAR500k 55 105 35 195 ZAR97,5 mil ZAR650k to ZAR1.3 mil ZAR975k 79 147 52 278 ZAR271,05 mil
more than ZAR1.3 mil ZAR1,5 mil 34 62 11 107 ZAR160,5 mil
total 725 ZAR557,48 mil
To summarise, the following VOTs were applied in this research project to monetise travel time (with VOT = 0.5 × hourly wage):
- School learners → ZAR0.00/h
- Working school parents → ZAR190.00/h
- Non-working school parents and US students → ZAR8.00/h
Page | 103 Table 4.10: Calculation for the average VOT for all people for all hours of the day, assumed for non- working parents and SU students.
nominal GDP for third quarter of 2014
Gross domestic product, Third quarter 2015 Statistics South Africa
ZAR963 billion
nominal GDP for fourth quarter of 2014
Gross domestic product, Fourth quarter 2015 Statistics South Africa
ZAR979 billion
nominal GDP for first quarter of 2015
Gross domestic product, First quarter 2015 Statistics South Africa
ZAR975 billion
nominal GDP for second quarter of 2015
Gross domestic product, Second quarter 2015 Statistics South Africa
ZAR991 billion 2015 mid-year population estimate Statistics South Africa 54.96 million people per capita annual income of SA citizens ZAR71,106
hours in a year 365 × 24 = 8760 hours
Avg. VOT for all people for all hours of
the year ZAR8.12
Table 4.11: Average hourly wage calculation for SU staff (PayScale, 2015).
Job Salary range Mid-value salary Avg. salary
Lecturer ZAR140,688 to R476,167 308,428
ZAR232,534 (annual) ZAR116.27 (hourly) Office administrator ZAR78,105 to R313,481 195,793
Researcher ZAR114,059 to R460,879 287,469
Research Assistant ZAR62,860 to R214,031 138,445
4.5.2.4.2 VEHICLE OCCUPANCY RATE
As should be clear from the previous subsection, travel time savings are evaluated per road user and not per vehicle. An average vehicle occupancy rate was therefore required. A value of 1.46 passengers per vehicle was calculated from the responses to the lift club questions asked in the SU survey (see Table 4.12 ). This question was not directly included in the school-learner questionnaire, so the vehicle occupancy results calculated for the SU trips were also employed for the school trips. A sensitivity analysis was performed with an average vehicle occupancy of 1.2, because it is believed that many of the other, general commuters travel alone.
Table 4.12: Vehicle-occupancy-rate calculation.
Vehicle occupancy Frequency, f Vehicle occupancy × f Avg. vehicle occupancy
1 172 172 1.46 2 27 54 3 13 39 4 10 40 5 4 20 6 1 6 Total 227 331
Page | 104 4.5.2.4.3 ACCIDENT COSTS
The accident cost rates shown in Table 4.13 were applied in the accident-savings calculations. The values were originally specified by the National Institute for Transport and Road Research (1999), which is now CSIR Transportek. Prof. CJ Bester of the SU department of Transportation Engineering has updated these values every year to account for inflation of the private transport operation group.
Table 4.13: 2015 accident cost rates applied in the accident-savings calculations.
Accident type Cost (ZAR)
Fatal injuries 1,2 million
Seriously injured 275,000
Slightly injured 72,000
Damage only 47,200