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TIME AND TRAFFIC SURVEY REPORT –
NIMULE-ELEGU BORDER
(SOUTH SUDAN/UGANDA)
Rock city parking yard
Consultant: Lillian Muhebwa
Client: Trade Mark East Africa (TMEA)
June 2013
FINAL REPORT
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EXECUTIVE SUMMARY
This is a report on the time and traffic survey undertaken at Nimule-Elegu, on the South Sudan/Uganda
border in April, 2013. The assignment was aimed at obtaining baseline statistics at this border including
Truck queue time, Total customs processing time through country customs areas, Origin and destination
of Commercial Trucks and Buses, as well as total and daily traffic volumes.
Results of the survey undertaken for a duration of seven (7) consecutive days indicate that traffic at this
border is majorly commercial traffic – including buses and trucks. This traffic component accounts for
81% and 68% of the total through traffic recorded of 2159 and 2668 vehicles respectively at Elegu and
Nimule respectively. Commercial traffic majorly services the towns of Kampala, Nairobi, Mombasa,
Eldoret, Nakuru and Juba. A summary of the baseline statistics required as part of the terms of reference
is as presented below
Key traffic Parameter Elegu Outbound traffic Nimule Outbound traffic
Total day time traffic: 1557 Vehicles 2391 Vehicles
Ave daily Day time traffic 222 Vehicles 342 Vehicles
Ave daily Night time traffic 86 Vehicles 40 Vehicles
Estimated Night traffic 602 Vehicles 277 Vehicles
Estimated Total traffic 2159 Vehicles 2668 Vehicles
Average daily traffic 308 Vehicles 381
Average Daily Queue time 13 hours 38 Minutes 48 Minutes
Average Daily Customs processing time 22 hours 12 Minutes 3 hours 28 Minutes
Total waiting time 59 hours 50 Minutes 4 hours 16 Minutes
The estimated night time traffic at Nimule is significantly lower because night counts were stopped by
RSS security personnel after only three hours of the planned 12 hours for the two night surveys. Traffic
Outbound at Elegu has a higher dwell time at the border because trucks are laden and as compared to
outbound traffic at Nimule that is mainly empty trucks and thus with less procedural requirements.
Overall, trailer trucks at Elegu have the highest dwell time of 88 hours and 21 minutes with Light trucks
having the least. This dwell time is also relatively high because of the manual system used for document
processing and registry. At Nimule, trucks queue for a maximum of 5 hours 22 minutes with
corresponding maximum dwell time within the customs clearing zone of 13 hours 38 minutes. The latter
can mainly be explained by night time arrivals after closing time of about 19:00 EAST and have to wait
until the traffic is allowed through the next morning.
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Table of Contents
EXECUTIVE SUMMARY ................................................................................................................................ 1
ACRONYMS AND KEY DEFINITIONS ............................................................................................................. 3
1 INTRODUCTION ....................................................................................................................................... 4
1.1 ASSIGNMENT SCOPE .................................................................................................................... 4
1.2 METHODOLOGY ........................................................................................................................... 5
1.2.1 Time survey .......................................................................................................................... 5
1.2.2 Traffic survey ....................................................................................................................... 5
1.2.3 Data collection and preparation for survey ........................................................................... 7
1.2.4 Vehicle Categorisation .......................................................................................................... 8
1.2.5 Overview of truck movement procedures............................................................................. 8
2 SURVEY RESULTS ..................................................................................................................................... 9
2.1 Traffic Volume component .......................................................................................................... 9
2.1.1 Elegu - Outbound traffic Uganda .......................................................................................... 9
2.1.2 Nimule - Outbound traffic South Sudan .............................................................................. 12
2.2 Origin destination survey ........................................................................................................... 16
2.2.1 Traffic originating from Uganda .......................................................................................... 16
2.2.2 Traffic originating from South Sudan .................................................................................. 16
2.3 Queue time ................................................................................................................................ 18
2.3.1 Elegu-Uganda ..................................................................................................................... 18
2.3.2 Nimule ............................................................................................................................... 19
2.4 Processing Time ......................................................................................................................... 20
2.4.1 Elegu - Uganda ................................................................................................................... 20
2.4.2 Nimule – South Sudan ........................................................................................................ 21
3 CONCLUSION ......................................................................................................................................... 23
ANNEX I – DATA COLLECTION FORMS ....................................................................................................... 24
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ACRONYMS AND KEY DEFINITIONS
CCZ Customs Clearing Zone
CPT Customs Processing Time
DRC Democratic Republic of Congo
EAST East Africa Standard Time
OSBP One Stop Border Post
TMEA TradeMark East Africa
TOR Terms of Reference
URA Uganda Revenue Authority
RSS Republic of South Sudan
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1 INTRODUCTION
This report presents the results of the Time and Traffic survey conducted at the Nimule-Elegu border
crossing between South Sudan and Uganda. Nimule-Elegu is the main border of South Sudan to Uganda
and services Juba, the capital city of the Republic of South Sudan.
The survey was commissioned by TradeMark East Africa (TMEA) as part of collecting baseline data to be
used in the planning, and monitoring and evaluation of its projects in particular the One-Stop Border
Post (OSBP) project aimed at reducing transport and related costs along the key transport corridors in
East Africa.
1.1 ASSIGNMENT SCOPE
This survey involved three main components viz obtaining statistics on through traffic at the
border, waiting/dwell time for commercial trucks at the border and origin/destination survey for
commercial vehicles. The study objectives were to:
i) Obtain queue waiting time and customs processing time for trucks transporting commercial
cargo (both containerised and non-containerised cargo) at the Nimule-Elegu border and
thus determine total waiting time at the above mentioned borders.
ii) Determine baseline border crossing times against which future changes will be measured.
iii) Determine baseline border traffic volumes by vehicle category and composition by types of
goods (containers, petroleum products) and categories.
iv) Obtain information on origin/destination of selected commercial traffic (Coaches, Coasters
and all truck categories).
Specifically, the survey sought to obtain statistics on:
i) The average number of trucks queuing.
ii) The estimated average queue time for commercial trucks disaggregated by category
iii) The estimated average customs processing time
iv) Day time traffic by category of vehicles;
v) Average day time traffic by category of vehicles;
vi) Estimated Night traffic by category of vehicles;
vii) Average night time traffic by category of vehicles
viii) Average Daily Traffic (by category)
ix) Total Volume of traffic for the survey week
x) Origin/Destinations for the selected commercial traffic (Coaches, Coasters and all truck
categories).
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1.2 METHODOLOGY
The methodology adopted for obtaining data for the different survey components is detailed
below:
1.2.1 Time survey
A manual queue time survey was undertaken over a period of 7 days, for 12 hours daily starting
at 0600 hours East African Standard Time (EAST) and ending at 1800 hours EAST. Data collection
was also undertaken for 24 hours on two days (one week day and one weekend day) to obtain
representative data/information for night traffic.
Eight data collection stations were commissioned as detailed below and as illustrated in the
schematic in figure 1-1 below.
i) Station A1 at end of the queue for trucks arriving at the border from Uganda to obtain arrival
times for traffic originating from Uganda (T1)
ii) Station A2 at the front exit gate on from the parking yard on the Uganda side of the border to
obtain exit times for traffic originating from South Sudan(T2)
iii) Station A3 at the back exit gate on from the parking yard on the Uganda side of the border to
obtain exit times for traffic originating from South Sudan(T3)
iv) Station B at the entry gate into the CCZ in front of Uganda Revenue Authority offices to obtain
time of entry into the Customs area for traffic originating from the Uganda(T4)
v) Station C at the security stop/check point for traffic exiting South Sudan to obtain time of
entry into the CCZ for traffic originating from South Sudan (T5)
vi) Station D1 at the T-junction before the entrance to the main vehicle parking yard at RSS
customs office Nimule to obtain arrival times for traffic originating from South Sudan (T6)
vii) Station D2 at the junction after the “rock city” vehicle parking yard in Nimule long the nimule-
Juba highway to obtain exit times for traffic originating from Uganda (T7)
Time data was also collected from the Jebel Parking yard for truck exits.
Queue times are calculated as the difference between entry times at stations A and D and
entry times into the CCZ at stations B and C respectively; that is [T4 - T1] and [T6 -T5] .
Customs processing times are calculated as the difference between entry times into the CCZ
at stations B and C and Exit times out of the CCZ in the next country at stations A and D
respectively; that is [T7 - T4] and [T6 -T3] or [T6 –T2] for traffic originating from Uganda and
South Sudan, respectively.
1.2.2 Traffic survey
This component involved traffic volume, and origin and destination survey. Manual classified traffic
counts were conducted at each border crossing over a period of 7 days, for 12 hours on each day. In
addition, 24 hour counts were performed for one week night and one-weekend night during the
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survey week to obtain indicative night traffic. Road side interviews with truck drivers were also
conducted to obtain Origin/Destination information. As with the time survey component, data was
collected at four stations as below:
i) Stations A1 and D1 – data on all vehicular traffic originating from Uganda and Rwanda
respectively
ii) Stations B and C - data on origin and destination for commercial traffic originating
from Uganda and South Sudan respectively
Figure 1-1: Schematic Layout of Survey stations
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1.2.3 Data collection and preparation for survey
i) Data was collected by enumerators recruited from the local community as specified in the
TOR. The enumerators were prepared for the survey and trained on the use of the data
collection instruments. Training took place two days prior to the start of the actual data
collection exercise as detailed hereafter.
ii) Training details
The training took a two pronged approach involving both theoretical and practical sessions.
The theoretical session adopted a Class room style arrangement using simple language and
participatory tools. Participants were taken through the study scope, data collection forms
and key elements of the survey like Vehicle categories, survey duration and protocols as
well as data quality.
The practical session was done on two days and involved atransect to familiarize
enumerators with proposed data collection stations, and vehicle categories. Thereafter,
data collection by enumerators using the survey forms for a period of two hours each on
both days of the training with each enumerator collecting data at each of the two main
station categories. A debrief was held to discuss results of the exercise, clarify on any
outstanding issues and agree the final team of enumerators. The second practical session
was to clarify any outstanding issues and for enumerators to get more practice with the
data collection forms
Figure1-2 record of training session
iii) Three categories of data collection forms as detailed in Annex I were used. Form category 1 to
capture data on traffic volumes as well as truck arrival, Form category 2 to capture origin and
destination data on buses and time (entry into CCZ) data for commercial trucks, Form category
3 for time (exit from CCZ) data for commercial trucks. Category 1 Forms were used at stations
A1 and D1, category 2 forms at stations B and C while category 3 forms were used at stations
A2, A3 and D2.
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1.2.4 Vehicle Categorisation
For purposes of this survey, vehicles were categorized into four major categories with key sub-
categories as detailed in the table below:
Vehicle Category Description
1.Container Trucks:
Header Trailers All trucks transporting removable containers (20ft and 40ft).
Fuel Tankers All commercial fuel transporting vehicles
2.Non-containerised trucks:
Light truck Pickups, lorries and small trucks carrying capacity up to 8T
Medium truck Trucks with equivalent carrying capacity from 8T up to 15T
Other All other non-containerised trucks larger than medium trucks
3.Buses:
Coach All commercial buses transporting 45 or more passengers
Coaster All commercial buses transporting max 30 passengers
Minibus All commercial buses transporting max 14 passengers
3.Passenger vehicles:
Saloon/Sedan/Mini-van Small passenger vehicles of capacity up to 7 passengers
4WD’s Large passenger vehicles
Pick-ups Passenger pickups – Not carrying goods
1.2.5 Overview of truck movement procedures
Elegu Outbound traffic: On arrival, trucks queue by the roadside along the Gulu-Nimule Road, the
queue regularly stretching to over a kilometer. Documents are submitted to the URA official at the
entry/exit gate. Trucks are let through depending on the traffic between the exit barrier and before the
bridge. Consignment details are then recorded in a manual register by URA then passed on to RSS
customs officials operating in the URA office. The latter also make records in a manual register then
documents are sent to Nimule for the rest of the customs process. On entry, the truck driver formalizes
with Uganda immigration procedures and waits for exit advice from the customs agent before finalizing
RSS immigration procedures. After crossing into the CCZ on the Nimule side of the border, Trucks are
then parked in one of the three parking yards, after registering their records in the exit register; waiting
to be exited. Priority parking is in the main customs yard Fuel tankers and trucks with relief items use
the rock city parking yard and the third parking at Nimule national park entry is mainly used when the
other two are full. Trucks are exited once the customs process is complete
Nimule Outbound traffic: on arrival, trucks proceed to the security check point, the Turnman/Co-driver
proceeds to clear with immigration and register truck details in the exit register. Trucks then proceed to
the Elegu side and park in the customs yard. Truck details are recorded by URA in a manual register after
completion of relevant documentation (empty manifest) and transit traffic pays the necessary road user
fees at URA. Trucks are released thereafter and exit to Uganda.
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2 SURVEY RESULTS
2.1 Traffic Volume component
Day time traffic volumes for vehicular traffic crossing the Nimule-Elegu border were recorded
daily on each of the survey days from 6:00 to 18:00 EAST. In addition, night traffic volumes were
also recorded on one weekday and one weekend day at Elegu1. Data collection on the Nimule
side was only undertaken up 22:00 due to security concerns with the enumerators not being
allowed at their stations by security personnel. Results of this survey component are presented
in the sections that follow.
2.1.1 Elegu - Outbound traffic Uganda
Results of the traffic counts are presented in table 2-1 below and also graphically illustrated in
figure 2-1.
Table 2-1: Through traffic statistics –Day time Traffic originating from Uganda
Survey Day
Passenger vehicles
Buses Non-containerised
trucks Trailer trucks
Fuel tankers
Total
Day 1 48 20 92 52 15 227
Day 2 21 10 95 52 19 197
Day 3 52 19 95 43 26 235
Day 4 50 19 90 52 47 258
Day 5 41 22 91 46 27 227
Day 6 85 12 69 44 19 229
Day 7 40 21 78 36 9 184
Category Total
337 123 610 325 162 1557
Average daily
48 18 87 46 23 222
% 22% 8% 39% 21% 10% 100%
Average daily vehicular day time traffic for traffic originating from the Elegu side of the border
was obtained as 222 vehicles. The total day-time through traffic for the survey week was 1557
vehicles. An analysis of the traffic composition summarized in figure 2-1indicates that
commercial trucks as defined by this survey contribute the largest proportion of through traffic
at the Nimule-Elegu border, contributing 70% of the total traffic. Further analysis of this traffic
category indicates that non containerized trucks account for the largest proportion of
commercial trucks - 39% of total traffic, with the containerized trucks (Fuel tankers and Trailer
trucks) contributing 31% of total traffic.
1 Night time data collection was disrupted on both days planned for 24 hour data collection
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Figure 2-1: Vehicle Traffic Composition - Elegu
The daily traffic variation presented in figure 2-2 below shows that the daily traffic volumes
across the different survey days are within the same range, with a standard deviation of 25. The
highest daily traffic volume obtained was on day 4 (258 vehicles) and the lowest on day 7 (184
vehicles), both of which are weekdays.
Figure 2-2: Daily Traffic Variation
Passenger vehicles
22%
Buses 8%
Non-contanerised
trucks 39%
Containerised Trucks
31%
Commercial Trucks
70%
Vehicle Traffic composition - Elegu
0
50
100
150
200
250
300
Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7
Fuel tankers 15 19 26 47 27 19 9
Trailer trucks 52 52 43 52 46 44 36
Non-contanerised trucks 92 95 95 90 91 69 78
Buses 20 10 19 19 22 12 21
Passenger vehicles 48 21 52 50 41 85 40
Traf
fic
volu
me
Daily traffic volume variation - Elegu
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Overall there are significant traffic volumes obtained across the different vehicle categories.
Commercial traffic in particular is high at this border. The average daily truck volumes are
disaggregated as 87 non-containerized trucks, 23 Fuel tankers and 46 trailer trucks.
Night time traffic volumes are also significant and the results are presented in table 2-2:
Table 2-2: Through traffic statistics –Night Traffic originating from Uganda
Survey Day Passenger vehicles
Buses Non-
contanerised trucks
Trailer trucks
Fuel tankers
Total
Weekend day
10 8 32 14 12 76
Week day 12 7 38 18 21 96
Average daily Night
traffic 11 8 35 16 17 86
Night time traffic is quite high at the Nimule-Elegu border. The average daily night traffic on the
Elegu side for the two survey days was obtained as 86 vehicles. Most of the night time traffic is
commercial traffic comprising mainly the non-containerized trucks. Traffic on weekend days of
the survey is lower, about 79% of that recorded on the week days.
Comparison of day time and night
time traffic volumes indicates that
traffic is largely day time traffic,
this comprising an estimated 72%
of the total traffic. Vehicle arrival
trends across the survey week as
summarized in figure 2-4 aside,
further reinforce the traffic flow
trend. It is noted that most of the
traffic is day time traffic with
several peaks. The highest hourly
traffic volumes were recorded in the morning from 6:00am to 10:00am, at 13:00 hours and
16:00hours. From the figure, the most notable hourly traffic volume peaks are early morning
between 7:00 and 9:00 EAST and afternoon at 13:00 and 16:00 EAT. This indicates that traffic
builds up creating long queues as shown in the frame in figure 2-5 below. Night time traffic
recorded was on average less than 20 vehicles per hour, Night traffic tails off about 23:00 hours
and starts to pick up at 04:00hours.
0
20
40
60
80
100
120
140
160
6:00
7:00
8:00
9:00
10:0
011
:00
12:0
013
:00
14:0
015
:00
16:0
017
:00
18:0
019
:00
20:0
021
:00
22:0
023
:00
0:00
1:00
2:00
3:00
4:00
5:00
Traf
fic
Vo
lum
e
Hour
Total Vehicular Traffic hourly variation
Figure 2-4: Hourly traffic flow variation
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The estimate of the total through traffic at Elegu is presented in Table 2-3 below:
Table 2-3: Estimated Through traffic statistics – From Uganda
Parameter Passenger vehicles
Buses Non-contanerised
trucks Trailer trucks
Fuel tankers
Total
Total day traffic 337 123 610 325 162 1557
Ave Night traffic 11 8 35 16 17 86
Estimated Night traffic
77 53 245 112 116 602
Estimated Total traffic
414 176 855 437 278 2159
*- Estimated night traffic is obtained using statistical average not the rounded average figure
The estimated total through traffic was obtained as 2159 vehicles translating to an estimated daily
average of 308 Vehicles. The corresponding volumes for the different vehicle categories are shown in
table 2-3. As with both Night and Day time traffic statistics, the total traffic is largely commercial vehicles
i.e. Trucks and Buses, contributing 68% of the total traffic.
2.1.2 Nimule - Outbound traffic South Sudan
Results of the traffic counts are presented in table 2-4 below and also graphically illustrated in figure 2-
5.
Figure 2-5: Illustration of queuing trucks at Elegu
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Table 2-4: Through traffic statistics –Day time Traffic originating from South Sudan
Survey Day Passenger vehicles
Buses Non-containerised
trucks Trailer trucks
Fuel tankers
Total
Day 1 78 16 137 37 35 303
Day 2 137 22 142 38 43 382
Day 3 141 20 130 41 39 371
Day 4 147 44 131 52 31 405
Day 5 74 33 145 60 22 334
Day 6 112 21 112 14 11 270
Day 7 126 16 132 34 18 326
Category Total
815 172 929 276 199 2391
Average Daily
116 25 133 39 28 342
% 34% 7% 39% 12% 8% 100%
Average daily vehicular day time traffic for traffic originating from the Nimule side of the border was
obtained as 342 vehicles. The total day-time through traffic for the survey week was 2391 vehicles. An
analysis of the traffic composition summarized in figure 2-6 indicates that commercial trucks as defined
by this survey contribute the largest proportion of through traffic from Nimule, contributing 59% of the
total traffic. Further analysis of this traffic category indicates that non containerized trucks account for
the largest proportion of commercial trucks - 39% of total traffic, with the containerized trucks (Fuel
tankers and Trailer trucks) contributing 20% of total traffic.
Figure 2-6: Vehicle Traffic Composition - Nimule
Passenger vehicles
34%
Buses 7%
Non-contanerised
trucks 39%
Containerised Trucks
20%
Commercial Trucks 59%
Vehicle Traffic composition - Nimule
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The daily traffic variation presented in figure 2-7 below shows that the daily traffic volumes
across the different survey days are within the same range, with a standard deviation of 47. The
highest daily traffic volume obtained was on day 4 (405 vehicles) and the lowest on day 6 (270
vehicles), both of which are weekdays.
Figure 2-7: Daily Traffic Variation
As with Outbound traffic at Elegu, significant traffic volumes across all the different vehicle
categories were recorded at the Nimule side of the border. The average daily traffic volumes
obtained are 116 passenger vehicles, 25 Buses, 133 non-containerized trucks, 28 Fuel tankers
and 39 trailer trucks.
The night time traffic component could not be accurately estimated since data collection at
night was not possible as a result of stoppages by RSS security personnel. Counts were recorded
for an average of 3 hours; up to 22:00 on the week day and up to 21:00 on the weekend day and
results obtained for records up to 21:00 are presented in table 2-6:
Table 2-6: Through traffic statistics –Night Traffic originating from South Sudan
Survey Day Passenger vehicles
Buses Non-contanerised
trucks Trailer trucks
Fuel tankers
Total
Weekend day 0 0 9 3 1 13
Week day 10 1 39 11 5 66
Average Night traffic
5 1 24 7 3 40
0
50
100
150
200
250
300
350
400
450
Day 1
Day 2
Day 3
Day 4
Day 5
Day 6
Day 7
Fuel tankers 35 43 39 31 22 11 18
Trailer trucks 37 38 41 52 60 14 34
Non-contanerised trucks 137 142 130 131 145 112 132
Buses 16 22 20 44 33 21 16
Passenger vehicles 78 137 141 147 74 112 126
Traf
fic
volu
me
Daily traffic volume variation - Nimule
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The average daily night time traffic for the two survey days was obtained as 40 vehicles. 61% of
the night time traffic recorded is of non-containerized truck category. Night time traffic on the
weekend day of the survey is about 19% of that recorded on the week day.
Comparison of day time and night time volumes shows that traffic from South Sudan is also
largely day time traffic, this comprising an estimated 88% of the total traffic. Hourly traffic
volume trends across the survey week as summarized in figure 2-8 below also present a similar
scenario. The figure further reiterates traffic flow behavior; almost all the traffic flows before
18:00 (day time close) with hardly any traffic recorded between the hours of 18:00 and 22:00.
Figure 2-8: Hourly Traffic Variation
There are several notable traffic peaks within the day in the hours of 6:00, 7:00, 9:00, 13:00,
15:00 and 16:00. The hourly total day-time volumes are at least 150 vehicles.
Estimated total through traffic was obtained as 2668 vehicles translating to an estimated daily
average of 382 Vehicles. The corresponding volumes for the different vehicle categories are
shown in table 2-7 below. More than 1000 non-containerised trucks were recorded during the
survey week and a total of 1642 commercial trucks were recorded
Table 2-7: Through traffic statistics –Night Traffic originating from South Sudan
Parameter Passenger vehicles
Buses Non-
containerised trucks
Trailer trucks
Fuel tankers
Total
Total day traffic 815 172 929 276 199 2391
Ave Estimated Night traffic
5 1 24 7 3 40
Estimated Night traffic 35 4 168 49 21 277
Estimated Total traffic 850 176 1097 325 220 2668
0
50
100
150
200
250
300
6:00
7:00
8:00
9:00
10:0
011
:00
12:0
013
:00
14:0
015
:00
16:0
017
:00
18:0
019
:00
20:0
021
:00
22:0
023
:00
0:00
1:00
2:00
3:00
4:00
5:00
Traf
fic
Vo
lum
e
Hour
Total Vehicular Traffic hourly variation
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2.2 Origin-Destination survey
The second component of this survey involved an origin and destination analysis for selected
commercial traffic that included all trucks, coasters and coaches. Results of the analysis for this
component are presented hereafter.
2.2.1 Traffic originating from Uganda
The majority of commercial traffic into the Nimule-
Elegu border originates from six principal towns –
Kampala, Mombasa, Nairobi, Eldoret, Tororo and
Nakuru comprising both transits and local exports.
Figure 2-9 aside illustrates this and it shows that
almost all the commercial traffic at this border
originates from Uganda and Kenya. Less than 2% of
the total commercial traffic was recorded to originate
from Rwanda (Kigali) and Tanzania (Isaka and Dar).
The presentation of origin in table 2-8 below provides
a further analysis of origin by vehicle category. This
informs the nature of traffic and therefore the
business from those origins. Kampala with the highest
percentage (37%) is mainly trade in general merchandise as noted from the high composition of
non-containerised trucks, Mombasa (22%) – Foreign imports, Nairobi (15%) – industrial goods,
Eldoret (8%), Nakuru (3%) and Kisumu (2%) – Fuels, and Tororo (7%) – Cement. 99% of the traffic
is destined to Juba. Clearly the Elegu-Nimule border is a key transit route for commercial traffic to
Juba the capital of South Sudan and hence commercial hub for the country.
2.2.2 Traffic originating from South Sudan
For traffic originating from South Sudan, the
scenario is the reverse of traffic into South Sudan.
As depicted in figure 2-10 aside and table 2.9 below
most of the commercial traffic is trucks returning
empty, mainly from Juba (82%), after delivery of
goods. The other significant portion of traffic
originates from Nimule (15%) and comprises
commuter taxis and local delivery trucks.
As with the principal origins for outbound traffic at
Elegu, this traffic is destined to Kampala (36%),
Nairobi(19%), Mombasa(13%) and Eldoret(5%). A
significant portion (15%) of the traffic from Nimule
TZ1%Kigali
0%Eldoret
8% Kisumu2%
Mombasa22%
Nairobi15%
Nakuru3%
Kampala37%
Northern Ug.1%
Eastern Ug.7%
Other4%
Principle Origins - Elegu
Figure 2-9: Commercial Traffic composition -principal origins
Juba 82%
Nimule 15%
Wau 1%
Other 2%
Principle Vehicle Origins - Nimule
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terminated in Elegu. This comprised of commuter taxis and trucks delivering construction
materials within Elegu.
Table 2-8: Origin & Destination summary – Elegu outbound traffic
Origin Destination Coach CoasterLight
Truck
Medium
Truck
Other
Truck
Trailer
Truck
Fuel
TankerTotal
Adjumani Juba 3 3
Juba 2 2 4
Nimule 1 1
Atiak Magwi 1 1
Busia Juba 1 1
Dar Juba 6 6
Eldoret Juba 2 3 104 109
Juba 1 1
Nimule 2 2
Entebe Juba 1 1
Goli Juba 1 1
Gulu Juba 5 2 7
Hoima Juba 1 4 5
Iganga Juba 1 1
Isaka Juba 11 1 12
Isingiro Juba 7 7
Jinja Juba 1 1 2
KabaramaidoJuba 2 2
Kahama Juba 1 1
Bor 2 2
Elegu 1 1
Juba 59 3 159 133 76 90 6 526
Nimule 1 1
Wau 1 1
Panyang 1 1
Rumbek 1 1
Kayunga Juba 1 1
Kiboga Juba 2 2
Kigali Juba 2 2
Kigumba Juba 1 1 2
Kiguru Juba 1 1
KiryadongoJuba 1 1
Kisumu Juba 1 23 24
Lira Juba 1 14 2 17
Lusaka Juba 1 1
Luwero Juba 1 1
Malaba Juba 1 3 4
Masaka Juba 2 2
Masindi Juba 1 1
Mbale Juba 9 9
Mbarara Juba 8 1 9
Aweil 1 1
Juba 9 6 47 242 16 320
Juba 4 17 15 80 75 20 211
Panyang 1 1
Nakuru Juba 1 38 39
Paidha Juba 1 3 4
soroti Juba 22 22
Tororo Juba 1 3 49 5 58
Arua
Elegu
Kampala
Mombasa
Nairobi
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Table 2.9: Origin & Destination summary – Nimule outbound traffic
2.3 Queue time
As noted in section 1.2, queue time was taken as the difference between the time a truck arrives
at the border and the time it enters the customs clearing area.
2.3.1 Elegu-Uganda
For traffic originating from the Uganda side of Nimule-Elegu border, queue time was computed
as [T3 - T1] with parameters defined as in section 1.2.1 above.
Table 2-10 below shows the average queue times obtained for traffic recorded during the survey
week.
Table 2-10: Average Queue Times for Traffic originating from Uganda
Origin Coach coasterFuel
Tanker
Light
Truck
Medium
Truck
Other
Truck
Trailer
Truck
Grand
Total
Aweil 1 1
Bentiu 1 1
Bor 1 5 1 7
Juba 83 1 176 269 128 241 278 1176
KAPOETA 1 1
Malakia 1 1
MELEWA 1 1
Nimule 2 1 210 5 2 1 221
Panyang 1 1
Pibor 1 1
Rumbek 1 1
Torit 2 2 1 5
Wau 1 5 4 4 1 5 20
YAMBIO 1 1
YEI 1 1 2 1 5
Category Total 86 1 185 486 150 247 288 1443
Survey DayLight
Truck
Medium
Truck
Other
Truck
Trailer
Truck
Fuel
Tanker
Ave.
Daily
Light
Truck
Medium
Truck
Other
Truck
Trailer
Truck
Fuel
Tanker
Grand
Total
Day 1 7:32 13:18 16:57 13:48 10:23 12:54 29 14 34 48 12 137
Day 2 8:18 15:55 17:45 17:08 10:46 14:23 39 18 38 55 19 169
Day 3 8:09 14:40 16:18 17:03 13:46 13:57 30 18 15 42 24 129
Day 4 7:16 12:22 19:11 21:36 14:30 15:57 29 25 32 55 50 191
Day 5 6:09 4:07 11:43 10:29 6:10 8:26 31 15 33 47 30 156
Day 6 8:59 21:52 20:40 23:06 16:52 18:31 24 10 20 38 13 105
Day 7 2:03 10:59 4:58 3:36 16 3 2 21
Daily Average 7:15 13:12 16:55 17:02 12:05 13:38 198 103 172 287 148 908
Average Queue time by truck category - Elegu Truck frequency distribution by category
19 | P a g e
The average daily queue time for commercial truck traffic was obtained as 13 hours 38 minutes.
The queues are contributed by the high traffic obtained at this border as indicated in section
1.2.1. The average hourly commercial traffic is about 16 vehicles with peaks at particular hours
like early morning and early evening, which contributes to the high queue times. The limited
manoeuver space on the road (particularly that leading to the CCZ and to the bridge), limited
parking space in the RSS customs yard, and early arrivals before border operations commence
also contribute to the high queue times.
Queue time variation across the different truck categories is quite significant with the heavier
goods vehicles queuing longer. It is noted that light trucks have the shortest queue time of 7
hours 15 minutes as compared to the other categories. This may be because of the ability to
easily maneuver on the narrow road.
Figure 2-11 below shows that the earlier a truck arrives the shorter its queue time. Trucks that
arrive in the early morning hours have the shortest queue times. The queue times increase as
operational hours progress peaking at 18:00 hours. Generally, lower queue times were noted for
traffic arriving outside of the border operational hours.
Figure 2-11: Variation of Queue Time by Arrival Hour
2.3.2 Nimule
For traffic originating from Nimule, queue time was computed as and [T4 -T5], all parameters as
previously defined. Table 2-11 below shows the queue average times obtained for traffic recorded
during the survey week.
0:00
2:24
4:48
7:12
9:36
12:00
14:24
16:48
19:12
6:0
0
7:0
0
8:0
0
9:0
0
10
:00
11
:00
12
:00
13
:00
14
:00
15
:00
16
:00
17
:00
18
:00
19
:00
20
:00
21
:00
22
:00
23
:00
0:0
0
1:0
0
2:0
0
4:0
0
5:0
0
Qu
eu
e ti
me
(Hr:
Min
)
Truck Arrival hour
Average Hourly Queue Time variation
20 | P a g e
Table 2-11: Average Queue Times for Traffic originating from Nimule
Results from the survey indicate an average daily queue time of forty eight minutes. Trucks from
Nimule queue have a much shorter time, because most of them are returning empty so do not
require elaborate procedures to scrutinize the documentation and/or a lot of time consuming
preparation to clear with border agencies.
Queue times could be shorter if
the border operated 24 hours
and therefore trucks that arrive
in the late evening did not have
to queue while waiting for the
border to open in the morning.
This is illustrated in figure 2-12
aside that shows the queue time
variation with truck arrival hour.
A steep rise in queue time is
noted from 19:00 hours when
the border
2.4 Processing Time
Customs processing time was obtained as the dwell time for trucks within the customs clearing area;
this was taken as the difference in time from when a truck enters the customs clearing area in one
country to the time it exits in the next country after clearing with all border formalities.
2.4.1 Elegu - Uganda
For traffic originating from Uganda, was calculated as [T2 - T4] all parameters as previously defined.
Results of data analysis are summarized in table 2-12 below:
Survey
Day
Light
Truck
Medium
Truck
Other
Truck
Trailer
Truck
Fuel
Tanker
Ave.
Daily
Light
Truck
Medium
Truck
Other
Truck
Trailer
Truck
Fuel
Tanker
Grand
Total
Day 1 5:46 0:15 0:12 0:28 0:16 1:39 39 20 33 39 27 158
Day 2 3:30 0:28 0:25 0:18 0:27 1:11 31 19 20 22 32 124
Day 3 0:14 0:08 0:05 0:11 0:08 0:10 47 21 25 39 35 168
Day 4 0:56 2:07 2:00 2:21 1:48 1:45 68 17 52 55 31 223
Day 5 0:05 0:03 0:07 0:08 0:05 0:06 59 18 24 43 18 162
Day 6 0:05 0:04 0:05 0:41 0:01 0:07 71 5 13 8 7 104
Day 7 0:14 0:09 0:13 0:07 0:18 0:12 73 15 29 43 17 177
Daily
Ave. 1:07 0:29 0:40 0:43 0:32 0:48 388 115 196 249 167 1116
Average Queue time by truck category - Nimule Truck frequency distribution by category
0:00
2:24
4:48
7:12
9:36
12:00
14:24
16:48
Qu
eu
e T
ime
[H
r:M
in]
Truck Arrival hour
Average Hourly Queue time variation - Nimule
Figure 2-11: Hourly Queue time variation - Nimule
21 | P a g e
Table 2-12: Average Customs processing Times for Traffic originating from Uganda
Average customs processing time for the survey week was obtained as 46 hours 12 minutes. The highest
daily average processing time of 61 hours 37 minutes was obtained on day one and the lowest of 5
hours on day seven customs processing times gradually dropping as the survey week progressed. The
higher processing times at the beginning of the survey week can be attributed to the backlog that had
been created by truck drivers’ strike on the two days prior to the start of the survey when trucks were
not crossing from Uganda into South Sudan. The times dropped as the situation progressively
normalized.
Within truck categories, light trucks generally have the lowest processing times and trailer trucks the
highest. There is no obvious trend in the customs processing times obtained pointing to the possibility
that several different factors influence the clearing process.
2.4.2 Nimule – South Sudan
Results of the analysis for trucks from South Sudan are summarized in table 2-13 below.
Table 2-13: Average Customs processing Times for Traffic originating from South Sudan
Survey DayLight
Truck
Mediu
m Truck
Other
Truck
Trailer
Truck
Fuel
Tanker
Ave.
Daily
Light
Truck
Medium
Truck
Other
Truck
Trailer
Truck
Fuel
Tanker
Grand
Total
Day 1 26:10 52:45 50:14 81:05 71:43 61:37 14 24 26 49 5 118
Day 2 37:08 29:33 53:52 73:54 52:24 53:27 27 6 26 29 19 107
Day 3 19:56 38:28 62:46 68:16 49:38 51:47 22 22 31 41 11 127
Day 4 20:38 49:04 34:43 62:54 48:16 41:27 24 17 18 15 25 99
Day 5 18:19 26:53 45:41 38:01 45:30 32:00 20 21 9 7 16 73
Day 6 16:22 24:18 4:47 17:03 15:46 16 5 5 2 28
Day 7 6:46 7:34 2:08 1:10 3:02 5:00 9 4 5 1 4 23
Daily Average 22:40 38:47 47:42 71:19 47:20 46:12 132 99 120 142 82 575
Average CP time by truck category - Elegu Truck frequency distribution by category
Survey
Day
Light
Truck
Medium
Truck
Other
Truck
Trailer
Truck
Fuel
Tanker
Ave.
Daily
Light
Truck
Medium
Truck
Other
Truck
Trailer
Truck
Fuel
Tanker
Grand
Total
Day 1 1:26 1:26 4:32 6:05 1:37 3:12 29 20 24 34 27 134
Day 2 1:54 1:18 8:16 2:32 5:35 3:54 23 14 17 28 27 109
Day 3 0:34 2:05 3:00 5:52 1:10 2:46 29 20 29 41 36 155
Day 4 0:39 2:06 5:08 2:13 1:07 2:18 38 17 36 50 27 168
Day 5 1:00 1:11 5:50 3:06 1:44 2:47 40 22 38 43 23 166
Day 6 13:44 1:36 2:11 1:45 1:33 15:23 23 6 14 11 7 61
Day 7 0:34 1:17 1:50 1:53 1:00 1:18 41 19 33 33 20 146
Daily
Ave. 4:45 1:34 4:22 3:31 2:01 3:28 223 118 191 240 167 939
StdDev 9:07 2:36 9:51 6:24 7:09 4:31
Average Customs processing time by truck category - Nimule Truck frequency distribution by category
22 | P a g e
The average customs processing time obtained across the survey week was three hours twenty
eight minutes. The dwell time within the CCZ is shorter for Traffic outbound on the Nimule side
because most of the commercial traffic is empty trucks returning after delivery of goods. Average
processing times across the different truck categories are within the same range with a standard
deviation of four hours thirty one minutes [04:31min] on the average daily customs processing
time. There is a wide variation particularly for the light trucks category and trucks in the “other”
category. This is particularly noted on day 6 under the light trucks category with an average CPT of
13 hours 44 Minutes.
Data in the sections above indicates that traffic from the Uganda side of the border outbound to
South Sudan, has a higher processing time and thus spends longer in the customs clearing zone.
This is because traffic outbound from this side of the border is laden with goods, which implies
customs clearing and verification processes to ensure the requisite taxes and procedures are
adhered to. In addition, these processes are manual with very limited / almost no data sharing
between the customs of both countries, making the process even longer. In comparison, traffic
outbound on the Nimule side is mainly empty trucks returning from delivering goods and is subject
to fewer procedures mainly recording of truck details (like registrations and origin/destination) and
payment of road user levies.
23 | P a g e
3 CONCLUSION
This survey sought to obtain baseline traffic and time statistics for the Nimule-Elegu border to
South Sudan and Uganda.
A summary of the key baseline statistics required as defined in the TOR is presented in table 3-1
below. Traffic on both sides of the border is largely day time traffic with similar figures obtained for
traffic volumes. The total estimated weekly through traffic is 2159 for outbound traffic at Elegu and
2668 for outbound traffic at Nimule. This corresponds to an average daily traffic of over 300
vehicles on either side. The higher traffic from Nimule is attributable to traffic that terminates in
Elegu. Statistics indicate a very high percentage of non-containerised traffic on either side of the
border, however with a significant proportion of Containerised trucks.
Table 3-1: summary baseline statistics
The time statistics obtained indicate that trucks queue longer at Elegu and customs processing time
for outbound traffic is also higher. The average total dwell time for outbound traffic was obtained
as 59 hours 50 minutes; this is a total waiting time of over four days as compared to Nimule
outbound commercial traffic that on average spends 4 hours in at the border. This can be
attributed to several factors related to customs clearance since truck traffic from Uganda is mainly
laden as compared to truck traffic from the South Sudan side that is mainly empty trucks requiring
less procedures and checks. In addition, there was a strike for two days prior to the start of the
survey which may have contributed to the high CPT particularly on days 1 and 2 due to traffic
buildup.
The principal origin and destination towns for commercial traffic are key commercial towns in
Uganda, Kenya and South Sudan. Some traffic was also recorded as originating from Dar, Isaka and
Kigali. This indicates that Nimule-Elegu border is an important transit route on the Northern and
Central corridor routes for commercial vehicle traffic to Juba.
Traffic volume ParameterPassenger
vehiclesBuses
Non-
contanerised
trucks
Trailer
trucks
Fuel
tankersTotal
Passenger
vehiclesBuses
Non-
contanerised
trucks
Trailer
trucks
Fuel
tankersTotal
Total day time traffic 337 123 610 325 162 1557 815 172 929 276 199 2391
Ave daily Day time traffic 48 18 87 46 23 222 116 25 133 39 28 342
Ave daily Night time traffic 11 8 35 16 17 86 5 1 24 7 3 40
Estimated Night traffic 77 53 245 112 116 602 35 4 168 49 21 277
Estimated Total week traffic 414 176 855 437 278 2159 850 176 1097 325 220 2668
Ave. daily traffic 59 25 122 62 40 308 121 25 157 46 31 381
Dwell time ParameterLight
Truck
Medium
TruckOther Truck
Trailer
Truck
Fuel
TankerAve. Daily
Light
Truck
Medium
TruckOther Truck
Trailer
Truck
Fuel
Tanker
Ave.
Daily
Ave Daily Queue time 7:15 13:12 16:55 17:02 12:05 13:38 1:07 0:29 0:40 0:43 0:32 0:48
Ave Daily CPT 22:40 14:47 23:42 23:19 23:20 22:12 4:45 1:34 4:22 3:31 2:01 3:28
Total waiting time 29:56 52:00 64:37 88:21 59:25 59:50 5:52 2:04 5:02 4:14 2:34 4:16
Principal commercial vehicle
origin
Principal commercial vehicle
Destination
Elegu Outbound traffic Nimule Outbound traffic
Kampala, Nairobi, Eldoret, Mombasa, Nakuru Juba, Nimule
Juba Kampala, Nairobi, Eldoret, Mombasa
24 | P a g e
ANNEX I – DATA COLLECTION FORMS
FORM CATEGORY 1
FORM CATEGORY 2
Border station: NIMULE/ELEGU Date:
Shift: (Day, Evening, Night) Weather ( Rainy/ sunny/Clear):
Trailer truck
(1x40, 2x20,
or 1x20)
Fuel
tanker
(tick)
Light truck
(tick)
Medium
truck (tick)
TRUCKS FROM UGANDA
Hour
startingArrival time Number plate (Reg #)
Other -
heavy goods
trucks (tick)
Date:
Shift (Day, Eve, Night)
Trailer truck
(1x40, 2x20,
or 1x20)
Fuel
tanker
Light
truck
Medium
truck
coach -
60 pax
Coaster-
30 pax
Border station: NIMULE/ELEGU
Weather ( Rainy/ sunny/Clear):
VEHICLES FROM UGANDA
Hour
starting
Entry time
to Customs
clearing
area
Number plate (Reg #) Other -
heavy
goods
trucks
Origin Destination
25 | P a g e
FORM CATEGORY 3
Border station: NIMULE/ELEGU Date:
Shift: (Day, Evening, Night) Weather ( Rainy/ sunny/Clear):
Trailer truck
(1x40, 2x20,
or 1x20)
Fuel tanker
(tick)
Light truck
(tick)
Medium
truck (tick)
Number plate (Reg #)
Other -
heavy goods
trucks (tick)
TRUCKS FROM NIMULE
Hour
starting
Exit time from
Customs
clearing area