4. I. INTRODUCTION
This report provides a Supply-Demand analysis, capacity analysis hereafter, for all Regional Transit System (RTS) bus routes (Campus Routes and
Later Gator Routes are presented in Appendix A and B respectively). Currently, the analysis only focuses on weekday services. The purpose of this
analysis is to help determine which routes would benefit from the addition or reduction of buses.
II. METHODOLOGY
The data used in this analysis comes from RTS’s Spring 2013 Automatic Passenger Counter (APC) data. First, the raw data is summarized by Route,
Block and Trip. Then, the records of weekday trips were selected out.
5. 1
Figure 1: APC file used in this analysis
The field “Max” represents the maximum load of passengers on individual trips, which is used as the main variable in the analysis. The value of
“Max” indicates the used capacity of each bus each trip. For instance, if the maximum load of one trip is 20 passengers, then the capacity used was
20. As the data is summarized by route and trip, the mean value of the “Max,” which represents the served demand or used capacity, for that
particular trip are calculated. It is important to note that the mean estimates the central tendency of a dataset so making bus adjustments to match the
mean will result in passengers being left behind. This is particularly relevant for the travel patterns observed with University of Florida and Santa Fe
College Students. Buses towards campus in the morning have little to no capacity while buses away from campus have most if not all capacity.
Taking these together shows that only 50% of capacity is being consumed and adjusting to these levels would be problematic. While the
methodology is being addressed to capture this, the results here should be considered for extreme cases of under (>80%) or over capacity (<20%).
6. 2
Figure 2: The scripts used in this analysis
The majority of work then moves to Python coding. We choose to write python scripts to perform the analysis quickly, accurately and automatically.
The scripts run with ArcPy under the environment of ArcGIS. The field “Trip” indicates the actual start time of an individual trip. Plus, the “Time”
represents the duration of the same trip. Therefore, the start time and end time can be both obtained. Based on this information, through running the
scripts, a table that contains the information of the status of bus service in a ten-minute interval is realized.
7. 3
The results of the scripts also tell us how many buses are actually on the road during any particular ten-minute interval, which is necessary for
calculating the supply of service or, capacity; this only considers seating capacity – the addition of standing capacity would add another 20-30
persons per bus.
Figure 3: The table created by running the scripts (partly)
8. 4
III. RESULTS
1. Route 1
Chart 1: Route 1 Weekday Capacity Analysis
Inferences:
For route one, the busiest time of a day is from 17:00 to 17:50. The other peak hours appear at 8:15, 9:15, and 10:15. Beginning from 16:00,
the service remains in a high-demand status until 18:00.
Recommended Suggestion:
Adjustments should be made to satisfy the huge demand from 17:00 to 17:50. Actually, from 17:00 to 17:20, route one runs out of seated
capacity. Potentially reduce service from 13:00 to 16:00, in order to increase coverage between 17:00 to 17:50.
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5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 1 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
9. 5
2. Route 2
Chart 2: Route 2 Weekday Capacity Analysis
Inferences:
Based on the analysis, the demand of Route 2 is being met. It is not necessary to make any adjustments to this route; note at the request of the
City Commission a second bus was added to this route in Spring 2014 to achieve 30 minutes headways.
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10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 2 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
10. 6
3. Route 5
Chart 3: Route 5 Weekday Capacity Analysis
Inferences:
Based on the analysis, the peak hour appears at 17:00 to 17:40. Any other period of time, the used capacity rarely goes above 60%. The
demand of the service has a steep decrease after 19:30.
Recommended Suggestion:
The consideration of reducing some services should be given. After 19:30, the number of serving buses could be reduced from two to one.
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5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 5 Weekday Capacity Analysis Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
11. 7
4. Route 6
Chart 4: Route 6 Weekday Capacity Analysis
Inferences:
The peak hour appears at 12:00 to 12:30. However, based on the analysis, the demand of the service of Route 6 is sufficiently satisfied.
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10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 6 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
12. 8
5. Route 7
Chart 5: Route 7 Weekday Capacity Analysis
Inferences:
Based on the analysis, the demand of the service of Route 7 is sufficiently satisfied.
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10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 7 Weekday Capacity Analysis Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
13. 9
6. Route 8
Chart 6: Route 8 Weekday Capacity Analysis
Inferences:
The strongest demand on Route 8 appears between 7:30 to 9:00 and 15:00 to 17:50. During the late morning, noon, and early afternoon, the
demand is relatively small. The busiest time appears at 17:00 to 17:20, the only time that the percentage of usage hit over 80%.
Recommended Suggestion:
From 21:00 to 23:00, consider reducing the number of buses serving the route from two to one.
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10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 8 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
14. 10
7. Route 9
Chart 7: Route 9 Weekday Capacity Analysis
Inferences:
The peak hour of Route 9 appears at 9:00. After 9:00, the demand for service is almost evenly distributed..
Recommended Suggestion:
Reducing some service from 12:00 to 16:00 should be considered. Also, after 23:00two serving buses seems unnecessary; in spring 2014 the
number of evening bus was reduced.
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10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 9 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
15. 11
8. Route 10
Chart 8: Route 10 Weekday Capacity Analysis
Inferences:
The busiest hour appears at the beginning of the service, which may indicate a need for earlier service.
Recommended Suggestion:
1. Start service earlier.
2. The increase in the number of buses to three seems to be unnecessary.
3. Consider reducing the number of buses after 18:00 to 20:00.
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6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 10 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
16. 12
9. Route 11
Chart 9: Route 11 Weekday Capacity Analysis
Inferences:
The peak hour appears at 17:00 to 17:30.
Recommended Suggestion:
The demand on Route 11 is sufficiently satisfied. Based on demand consider implementing a split with second bus.
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10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 11 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
17. 13
10.Route 12
Chart 10: Route 12 Weekday Capacity Analysis
Inferences:
The two peak hours appear at 9:10 and 17:10.
Recommended Suggestion:
Route 12 highlights the limitation of averaging, especially for campus routes. According to the graphs, there are no times when capacity is
lacking. However, looking at individual trips between 8:00 and 10:40 and 17:00 to 17:30, some buses run out of capacity, meaning the
distribution of passengers are greatly different even during the same time.
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10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 12 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
18. 14
11.Route 13
Chart 11: Route 13 Weekday Capacity Analysis
Inferences:
The most capacity is consumed at 18:20. From 11:00 to 17:00, the demand of Route 13 maintains at a relatively low level.
Recommended Suggestion:
Reduce between 11:00 to 16:00. From 17:40 to 19:00, add one more bus.
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5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 13 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
19. 15
12.Route 15
Chart 12: Route 15 Weekday Capacity Analysis
Inferences:
Based on the analysis, the demand on the Route 15 is met.
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5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 15 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
20. 16
13.Route 16
Chart 13: Route 16 Weekday Capacity Analysis
Inferences:
The busiest time occurs at the beginning of the service. Demand drops off great after 7:00PM.
Recommended Suggestion:
Consider reducing evening services; note that evening service was reduced in spring 2014.
Due to the highest demand appearing during the first trip, it may suggest adding an additional trip
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10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 16 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
21. 17
14.Route 17
Chart 14: Route 17 Weekday Capacity Analysis
Inferences:
Based on the analysis, the demand of the service of Route 17 is sufficiently satisfied; similar to route 16 reduce evening service
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10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 17 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
22. 18
15.Route 20
Chart 15: Route 20 Weekday Capacity Analysis
Inferences:
The demand of Route 20 consistently consumes most capacity. . The peak hour appears at 16:20.
Recommended Suggestion:
Similar to Route 12 there are a number of trips that run out of capacity, which is not directly reflected in the graph.
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5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 20 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
23. 19
16.Route 21
Chart 16: Route 21 Weekday Capacity Analysis
Inferences:
Based on the analysis, there are no adjustments needed on Route 21.
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6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 21 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
24. 20
17.Route 23
Chart 17: Route 23 Weekday Capacity Analysis
Inferences:
The second busiest situation occurs at the beginning of the service, which may indicate demand for earlier service.
Recommended Suggestion:
Start and end service earlier.
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6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 23 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
25. 21
18.Route 24
Chart 18: Route 24 Weekday Capacity Analysis
Inferences:
There is necessity to make any adjustments to this route; per City Commission request an additional bus was added to this route to achieve
30-minute headways.
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100.00%
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5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 24 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
26. 22
19.Route 25
Chart 19: Route 25 Weekday Capacity Analysis
Inferences:
Most capacity remains on this route.
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5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 25 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
27. 23
20.Route 27
Chart 20: Route 27 Weekday Capacity Analysis
Inferences:
Most capacity remains unconsumed on this route.
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8 1/2 9 1/2 10 1/2 11 1/2 12 1/2 13 1/2 14 1/2 15 1/2 16 1/2 17 1/2
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 27 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
28. 24
21.Route 28
Chart 21: Route 28 Weekday Capacity Analysis
Inferences:
Based on the analysis, demand is sufficiently satisfied.
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100.00%
0
40
80
6 7 8 9 10 11 12 13 14 15 16 17 18
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 28 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
29. 25
22.Route 34
Chart 22: Route 34 Weekday Capacity Analysis
Inferences:
The busiest hour occurs at 18:30. Demand on Route 34 remains relatively constant between 11:00am and 5:00pm.
Recommended Suggestion:
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6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 34 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
30. 26
23.Route 35
Chart 23: Route 35 Weekday Capacity Analysis
Inferences:
Demand has a steep decrease after 17:20.
Recommended Suggestion:
An earlier trip may be beneficial. Evening service was reduced in Spring 2014 consistent with trend present in graph..
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10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 35 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
31. 27
24.Route 36
Chart 24: Route 36 Weekday Capacity Analysis
Inferences:
Peak hour occurs at 8, 9, 10, 15, 16, and 17.
Recommended Suggestion:
Consider reducing some service between 10:20 and 14:50.
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6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 36 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
32. 28
25.Route 38
Chart 25: Route 38 Weekday Capacity Analysis
Inferences:
The demand on Route 38 keeps at a high level even towards the end of its service.
Recommended Suggestion:
Consider expanding service span and adding another bus.
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6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 38 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
33. 29
26.Route 39
Chart 26: Route 39 Weekday Capacity Analysis
Inferences:
The busiest time occurs at the beginning of the service.
Recommended Suggestion:
Consider adding an earlier trip.
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10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 39 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
34. 30
27.Route 43
Chart 27: Route 43 Weekday Capacity Analysis
Inferences:
The peak hour occurs at 8:00 and the second busiest hour appears at 17:00.
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5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 43 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
35. 31
28.Route 46
Chart 28: Route 46 Weekday Capacity Analysis
Inferences:
Route 46 highlights another limitation of methodology in that it does not accurately display passengers per hour and therefore provide a
complete picture of productivity. Consider two routes which both have 15 passengers per trip but one operates every 60 minutes and the other
every 15 minutes. While over the same period they both may consume the same capacity the route with the 15-minute frequency moves 4
times as many people. Route 46 does not consume a great deal of capacity over any single hour but has upwards of 50 or more people per
hour.
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6 7 8 9 10 11 12 13 14 15 16 17 18
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 46 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
36. 32
29.Route 62
Chart 29: Route 62 Weekday Capacity Analysis
Inferences:
Based on the analysis, the demand of the service of Route 62 is sufficiently satisfied.
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10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 62 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
37. 33
30.Route 75
Chart 30: Route 75 Weekday Capacity Analysis
Inferences:
From 12:00 to 17:40, the demand of Route 75 stays at a high level
Recommended Suggestion:
Consider adding another trip after 20:20. In addition, consider adding a third bus all day long.
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10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 75 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
38. 34
31.Route 76
Chart 31: Route 76 Weekday Capacity Analysis
Inferences:
Based on the analysis, the demand of the service of Route 76 is sufficiently satisfied.
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0
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6 7 8 9 10 11 12 13 14 15 16 17 18 19
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 76 Weekday Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
39. 35
IV. CONCLUSION
The following chart is the general capacity analysis for all routes running on weekdays.
Chart 32: All Routes Weekday Capacity Analysis
Generally speaking, as we can conclude by observing the chart, the aggregate demand is sufficiently served. The trend of the demand and the trend of
supply (capacity) are almost paralleled with each other, which can be a significant proof to justify the current scheme and the schedule arrangement
of the transit system. However, the recommendations by each individual route that suggested in the last section of this report should be given serious
considerations.
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5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Capacity Analysis -- All Rutes on Weekday
Capacity-unused
Capacity-used = Demand Served
Percentage of Capacity-used
40. 36
APPENDIX A. CAMPUS ROUTES ANALYSIS
1. Route 117
Chart 33: Route 117 Capacity Analysis
Inferences:
Most capacity remains unconsumed on this route.
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80.00%
100.00%
0
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80
6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 117 Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
41. 37
2. Route 118
Chart 34: Route 118 Capacity Analysis
Inferences:
The two peak hour appears at 11:40 and 18:30. However, only one bus is on service at the second busiest time of a day.
Recommended Suggestion:
After 18:00, remain at least two buses serving until 19:00 to cover the peak hour.
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100.00%
0
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160
6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 118 Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
42. 38
3. Route 119
Chart 35: Route 35 Capacity Analysis
Inferences:
The chart above shows a period pattern of the demand on Route 119. The peak hours appear at 12:30 and 13:30, at which the percentage of
capacity-used reaches 80%. After 17:30, this period pattern does not show any signal of decline.
Recommended Suggestion:
Consider add one more bus during the busiest hours and extent the service till 18:30.
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10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 119 Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
43. 39
4. Route 120
Chart 36: Route 120 Capacity Analysis
Inferences:
Based on the analysis, the demand on Route 120 is sufficiently satisfied.
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
0
40
80
6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 120 Capacity Analysis Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
44. 40
5. Route 121
Chart 37: Route 121 Capacity Analysis
Inferences:
Most capacity remains unconsumed on this route.
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
0
40
80
6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 121 Capacity Analysis Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
45. 41
6. Route 122
Chart 38: Route 122 Capacity Analysis
Inferences:
Most capacity remains unconsumed on this route.
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
0
10
20
30
40
50
6 7 8 9 10 11 12 13 14 15 16 17 18
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 122 Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
46. 42
7. Route 125
Chart 39: Route 125 Capacity Analysis
Inferences:
The peak hour occurs at 11:30. Based on the analysis, the demand on Route 120 is sufficiently satisfied.
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
0
40
80
120
6 7 8 9 10 11 12 13 14 15 16 17 18
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 125 Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
47. 43
8. Route 126
Chart 40: Route 126 Capacity Analysis
Inferences:
Most capacity remains unconsumed on this route.
Recommended Suggestion:
Consider reducing some of the service.
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
0
40
80
17 18 19 20 21 22 23 24 25 26 27
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 126 Capacity Analysis Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
48. 44
9. Route 127
Chart 41: Route 127 Capacity Analysis
Inferences:
Most capacity remains unconsumed on this route.
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
0
40
80
6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 127 Capacity Analysis Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
49. 45
APPENDIX B. LATER GATOR ROUTES ANALYSIS
1. Route 300
Chart 42: Route 300 Capacity Analysis
Inferences:
The peak hour appears at 26:00 which refers to 2:00 am in the morning.
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
0
40
80
120
20 21 22 23 24 25 26 27
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 300 Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
50. 46
2. Route 301
Chart 43: Route 301 Capacity Analysis
Inferences:
Peak hour occurs at 26:20. Most capacity remains unconsumed on this route.
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
0
40
80
120
20 21 22 23 24 25 26 27 28
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 301 Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
51. 47
3. Route 302
Chart 44: Route 302 Capacity Analysis
Inferences:
The two peak hours appear at 25:50 and 26: 40 which refer to 1:50 AM. and 2:40 AM. However, the current schedule does not provide the
full-service at the second peak hour.
Recommended Suggestion:
Adjustment of schedule should be made between 26:00 and 26:50.
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
0
40
80
120
20 21 22 23 24 25 26 27 28
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 302 Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
52. 48
4. Route 303
Chart 45: Route 303 Capacity Analysis
Inferences:
The percentage of capacity-used never goes above 20%. No significant indications justify the necessity of a second bus.
Recommended Suggestion:
Consider reducing some of the service.
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
0
40
80
20 21 22 23 24 25 26 27 28
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 303 Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
53. 49
5. Route 305
Chart 46: Route 305 Capacity Analysis
Inferences:
Based on the analysis, the demand on Route 305 is sufficiently satisfied.
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
0
40
80
20 21 22 23 24 25 26 27 28
10MINUTELOAD/CAPACITY
TIME OF DAY (10 - MINUTE INTERVALS)
Route 305 Capacity Analysis
Capacity-unused
Capacity-used = Demand Served
Passengers / Bus
Percentage of Capacity-used
