1. A Workshop on Driver Training & Vehicle
Maintenance
Performance Monitoring of Star Bus
Visakhapatnam
August 31, 2012
Umang Jain
Associate-Urban Transport

2. Background
• Government of National Capital Territory of Delhi (GNCTD) initiated
a new scheme for Operation of Private Stage Carriage Services to
replace the existing private stage carriage service scheme.
• Existing Routes (650Nos) have been classified into Clusters(17 Nos.)
• The Scheme envisages concurrent operation of Delhi Transport
Corporation (DTC) and private operator in each Cluster (in the ratio
of 40:60) under a Unified Time Table
• Star Bus was awarded the first cluster which at present operates
100 buses(Non AC) on 5 routes which eventually is planned to
expand to 32 routes and 231 buses
• The operator has been allocated space at Millennium Depot and is
paid on a gross cost basis.
• Star Bus has procured the fleet and is responsible for operating and
maintaining the system, the fare collection rests with Delhi
Integrated Multimodal Transit System Limited(DIMTS)

3. Introduction
• The area of the site is approximately 5 hectares
3

4. Introduction
• There are 250 drivers and 60 staff members
4

5. Existing Operations-Star Bus
Route From To Route Scheduled Scheduled No. of Kms/bus Schedule
No length (km) frequency buses /day 1 way trip
• Star Bus currently operates on 5 routes with 100 buses
(min)
• Fleet Utilization is 95% WEEKDAY WEEKEND
411 Mori gate Ambedkar 25.4 20 9 10 203.2 72
Nagar
419 Old Delhi Ambedkar 17.8 8 22 17 213.6 264
Nagar
469 Anand Ambedkar 29.4 10 25 24 235.6 200
Vihar Nagar
522 Ambedkar Krishi Kunj 27.05 7 15 12 216.4 120
Nagar
534 Anand Mehrauli 30.25 10 24 23 242 192
Vihar
Total 129.9 95 86 1110 848
• The average route length is 26 km
•The average vehicle utilization is 222km/bus/day
•The spare buses are 5%
5

6. Existing Operations

7. Overview of Activities at the Bus Depot
• Time mapping of activities taking place from the time of in shedding of
the buses to out shedding was performed to appreciate the system
• The major activities are:
 In shedding of buses
 Parking of buses
 Washing
 Maintenance
 Fuelling
 Out shedding of buses
• The peak hours of each category of operations were deduced which
provide valuable input in the actual bus operations planning
7

8. TIME MAPPING OF ACTIVITES AT DEPOT
IN SHEDDING(1-2min/bus(21:30-00:30))
Peak Hour 23:00-00:00
PARKING
WASHING(23:00-04:00) SWEEPING(10 MIN)
SHUTTING WINDOWS(3 MIN)
Buses washed/day-50
Peak Hour 23:00-00:00 AUTOMATIC WASHING(4 MIN)
Break 01:00-02:00
MAINTENANCE(23:00-04:00) MINOR(Periodical Checking-10
buses/day)
FUELLING(23:00-02:00)
CONDUCTOR DUTY ALLLOCATION
(5-7 MIN)
OUTSHEDDING(04:00-08:30)
GPS CHECK&TIMELY OUTSHEDDING
CHECK BY DIMTS
Peak Hour 05:30- 8
CLEANING(2-3 MIN)
06:30

9. Data Analysis
• EMBARQ India collected and analyzed the following:
 GPS Data pertaining to Bus Route 419(2days)
 Electronic Ticketing Machine(ETM) Data pertaining to Bus
Route 419 (1 day)
 Fuel Consumption Data for the entire system(Month of
May’12)
9

10. GPS Data Analysis
10

11. GPS Data Analysis
• GPS Data for two days in the month of June,2012 pertaining
to Bus route 419, was analyzed based on the following
criteria:
 Missed stops
 Curtailed trips
 Travel time at different times of the day
11

12. GPS Data Analysis
• The average travel time to traverse the entire route is 57 minutes
• Standard deviation of travel times which is calculated to determine the
layover time is 9 minutes, while scheduled layover time is 4 minutes
Date Direction Parameter 08:00- 05:00- 11:00- 16:30- 20:00- Overall
11:00 08:00 16:30 20:00 23:00
4 June Down* Avg (min) 57 43 63 63 51 57
Std dev(min) 7 4 7 6 7 9
4 June Up** Avg (min) 54 41 61 61 47 55
Std dev(min) 14 11 12 13 11 10
12 June Down* Avg (min) 58 44 59 70 56 57
Std dev(min) 5 3 5 8 9 8
12 June Up** Avg (min) 64 59 62 69 55 62
Std dev(min) 5 7 4 7 6 7
*Down-Ambedkar Nagar-Old Delhi Railway Station
12
** Up- Old Delhi Railway Station-Ambedkar Nagar

13. GPS Data Analysis
• Morning peak hour travel time is about 10% less than
the evening peak travel time
• The travel time in the early morning period (5AM-8AM) is
less than the late evening period (8PM-11PM) travel time
• The standard deviation in both directions is almost the
same
• Early morning trips take the least time due to less traffic
on the road
13

14. GPS Data Analysis
• The results obtained from GPS data were startling
• The data revealed that almost all stops including stops
witnessing heavy passenger demand were being missed very
regularly
• On taking up the matter with Star Bus and further enquiries
the results can be explained based on the following facts:
 The geo fencing extends upto 25 m from the bus stops
 The machine does not recognize dwell time less than 10
seconds
 The machine considers the stop to be missed if the speed of
the bus at the stop is more than 10kmph*
*Speed taken as 10kmph rather than 0 kmph due to system’s shortcoming
14

15. GPS Data Analysis
04-Jun 12-Jun
DOWN UP DOWN UP
TIME %of %of %of %of
Missed Missed Missed Missed
MissedTrip trips MissedTrip trips MissedTrip trips MissedTrip trips
05:00 08:00 206 16 44 5 205 14 74 7
08:00 11:00 177 14 138 16 254 17 180 17
11:00 14:00 225 17 138 16 244 16 186 18
14:00 17:00 204 16 126 14 273 18 152 14
17:00 20:00 195 15 147 17 235 16 185 18
20:00 23:00 270 21 259 29 292 19 260 25
23:00 02:00 21 2 32 4 0 0 17 2
1298 884 1503 1054
•On any given day, the number of stops missed in the down
direction is more than the up direction(1.5 times)
•There is a wide variation in the number of missed stops in both
directions when compared across days(20% increase)
15

16. GPS Data Analysis
• 30-35% of the total stops missed in the day(daily) on
bus route 419 are missed in the peak hours
• The percentage of missed stops are highest in the
time period 8PM-11PM
• During early morning (5AM-8AM) the percentage of
stops missed in downward direction is more than the
up direction(200%)
16

17. No of Schedules
100
120
140
0
20
40
80
60
ambedkar nagar
pushpa vihar
pushpa bhawan
sheikh sarai
chirag delhi
panchasheel
siri fort
central school
MCKR
defence colony
panth nagar
Average Missed Schedules In a day
CGO complex
oberoi hotel
delhi public school
sunder nagar
zoo
national stadium
ITPO
pragati maidan
supreme court
GPS Data Analysis(2 Days)
ITO
expresso building
The Misses Schedules in the Down Direction are presented below
delhi gate
dariya ganj
subhash park
Total Schedules in a day
jama masjid
red fort
17
old delhi

18. No Of Schedules
100
120
140
20
40
60
80
0
old delhi
red fort
in a day
jama masjid
darya ganj
delhi gate
saheed park
ITO
pragati maidan metro
pragati maidan
ITPO Average No of Missed Schedules
National stadium
zoo
sunder nagar
oberoi hotel
CGO
panth nagar
defence colony
MCKR
GPS Data Analysis(2 Days)
central school
The Misses Schedules in the Up Direction are presented below
siri fort
krishi vihar
chirag delhi
sheikh sarai
pushpa bhawan
Total Schedules in a day
18
pushpa vihar
ambedkar nagar

19. GPS Data Analysis-June 04, 2012-Up Direction
30 5:00 8:00
8:00 11:00
11:00 14:00
25
14:00 17:00
17:00 20:00
No of Missed Schedules
20:00 23:00
20
23:00 2:00
15
10
5
0
old delhi red fort jama darya delhi gate saheed ITO pragati pragati ITPO National zoo sunder oberoi CGO
masjid ganj park maidan maidan stadium nagar hotel
metro
19

20. GPS Data Analysis-June 04, 2012-Up Direction
30 5:00 8:00
8:00 11:00
25 11:00 14:00
14:00 17:00
No of Missed Schedules
17:00 20:00
20
20:00 23:00
23:00 2:00
15
10
5
0
panth defence MCKR central siri fort krishi vihar chirag sheikh pushpa pushpa ambedkar
nagar colony school delhi sarai bhawan vihar nagar
20

21. No of Missed Schedules
10
12
14
16
18
20
0
2
4
6
8
ambedkar
nagar
pushpa
vihar
pushpa
bhawan
sheikh
sarai
chirag
delhi
panchash
eel
siri fort
central
school
MCKR
defence
colony
panth
nagar
CGO
5:00 8:00
complex
23:00 2:00
8:00 11:00
20:00 23:00
17:00 20:00
14:00 17:00
11:00 14:00
oberoi
hotel
delhi
21
public
school
GPS Data Analysis-June 04, 2012-Down Direction

22. No of Missed Schedules
10
15
20
25
0
5
sunder nagar
zoo
national stadium
ITPO
pragati maidan
supreme court
ITO
expresso building
delhi gate
dariya ganj
subhash park
5:00 8:00
23:00 2:00
17:00 20:00
11:00 14:00
jama masjid
red fort
8:00 11:00
20:00 23:00
14:00 17:00
22
old delhi
GPS Data Analysis-June 04, 2012-Down Direction

23. Issues
• The scheduled layover is 4 minutes which needs to
be relooked
• The GPS data needs to be monitored closely and
necessary action in the form of penalties and
incentives needs to be undertaken

24. Fuel Consumption Analysis
24

25. Fuel Consumption-Analysis
• Fuel consumption data for the month of May 2012
for the entire system i.e., 5 routes was analyzed
Bus Route Avg Fuel Standard deviation
Consumption(km/kg)
534 2.66 0.10
469 2.58 0.10
419 2.52 0.09
522 2.49 0.10
411 2.43 0.08
Average 2.53
• Bus Route534 performs the best while route 411 is the worst
•The variation in all routes is almost the same
25

26. Fuel Consumption-Analysis
Route Mileage(km/kg)
• Km/kg
2.2- 2.3- 2.4- 2.5- 2.6- 2.7- 2.8- 2.9- Total
2.3 2.4 2.5 2.6 2.7 2.8 2.9 3.0 Buses
411 1 3 3 3 10
419 3 7 8 2 2 22
469 1 1 14 5 3 1 25
522 1 1 5 6 2 3 1 17
534 1 3 13 2 1 1 21
•On route 411, 40% of the buses have mileage less than 2.5km/kg
•On route 419, more than 50% of the buses have mileage more than 2.5km/kg
•On route 469, more than 90% of the buses have mileage more than 2.5km/kg
26

27. Fuel Consumption-Analysis
•On route 522, 50% of the buses have mileage less
than 2.5
•On route 534, almost all buses have mileage
greater than 2.5
•534 is the best performing route while routes 411
and 522 need to be studied in depth to find out
reasons for poor performance
27

28. Fuel Consumption-Analysis
Mileage Range(2.3-2.4km/kg)
Fuel
BUS ID Consumption(km/kg) ROUTE ID DRIVER ID NAME
3562 2.39 419/31 4028 Charan Singh
3567 2.39 419/2 2039 Naresh
3570 2.39 419/30 2068 Badri Prasad
3579 2.37 522/10 2016 Darmveer Singh
3580 2.26 522/26 2051 Sanjay Sapra
3621 2.33 411/10 2060 Anand Singh
3622 2.27 411/12 4075 Rohtash Singh
3625 2.38 411/16 2047 Sandeep
3646 2.39 411/2 4038 Mewa Singh
3871 2.37 469/14 2076 Sunil Basista
It has been observed that some of the buses and drivers’(32%)
performance is a cause of concern
28

29. Fuel Consumption-Analysis
Mileage Range(2.4-2.5km/kg) Fuel
Consumption
Fuel (km/kg)
Consumption BUS ID ROUTE ID DRIVER ID NAME
BUS ID (km/kg) ROUTE ID DRIVER ID NAME
3588 2.43 522/27 3030 Vinod Shrivastwa
3535 2.50 419/29 2075 Rajesh Kumar
3589 2.45 419/32 3092 Shamshad Ali
3556 2.44 419/22 3038 Pappu
3590 2.50 411/4 3031 Bijendar Sngh
3559 2.46 411/8 3139 Amit Kumar
3618 2.43 411/14 4064 Deshraj
3563 2.45 522/8 4013 Mahak Singh
3619 2.47 419/36 3083 Vikas
3566 2.45 419/28 3088 Karambir Singh
Gyan Singh/vimal 3643 2.43 411/17 3126 Tilak Singh
3569 2.49 419/12 2082, 2084 Chopra
3644 2.45 419/35 3138 Tej Pal
3581 2.50 522/14 4116 Ashok Kumar
3647 2.49 522/12 2046 Papu
3583 2.47 522/22 2017 Suresh Kumar
3873 2.47 469/20 4123 Hari Singh
3584 2.44 522/20 4039 Jai Singh
3881 2.50 469/37 4083 Sunil Kumar
3587 2.44 419/33 4096 Bhagat ram
3907 2.46 534/37 3128 Saleem Khan
29

30. Fuel Consumption-Analysis
Mileage Range(>2.7km/kg)
Fuel
BUS ID Consumption(km/kg) ROUTE ID DRIVER ID NAME
3550 2.72 419/10 4110 Ajay Kumar
3868 2.82 469/8 2067 Vikram Sharma
3880 2.75 469/34 4095 Suresh Kumar
3885 2.75 469/41 3100 Jai Pal
3887 2.76 469/43 3073 Mohammad Yunus
3951 2.86 534/6 3097 Karan Singh
3967 2.81 534/40 4018 Suresh Chand
3970 2.93 534/36 4056 Ramesh Singh
It has been observed that some of the buses and drivers’ performance(8%) is
very encouraging
The rest of the drivers and buses(60%) are performing satisfactorily
30

31. Issues
• An experiment in the form of assigning drivers to specific
bus(registration number) needs to happen for some length of
time(preferably 1 month) to determine if fuel consumption
can be attributed to drivers and driving habit
• Assigning drivers to specific bus may result in improved fuel
consumption due to familiarity with vehicle and route
• Driver Training can play a very significant role in improving
fuel efficiency

32. ETM Data Analysis
32

33. ETM Data Analysis
• ETM Data was analyzed for route 419 for a particular day
•The Peak hour occurs from 9-10 AM
1200
Occupancy of Bus
Up
1000
800
600
400
200
0
5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Time of Day
1200
Down
Occupancy of Bus
1000
800
600
400
200
0
5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Time of Day
33

34. ETM Data Analysis
• 28% of the users have a trip length upto 4 km, while 60% of
the users have a trip length upto 8 km
•Average trip length is 8.07 km
% trips
0%
3% 14% upto 4km
28% 4- 8km
8 -12km
23% 12 - 16km
16 - 20km
>20km
32%
34

35. ETM Data Analysis
• The average fare / passenger is Rs 8.13
•Fare/km works out to be Rs 1.01
Fare (Rs) % of passengers
5 55
10 28
15 18
35

36. ETM Data Analysis
• ETM Data for a particular day pertaining to route 419 was
analyzed
900
800
Occupancy Of Buses
700
600
500
400
300
200
100
0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
Bus Stops
The peak hour occupancy of the bus is shown in the graph above
36

37. ETM Data Analysis
• Based on the analysis, it is recommended to implement
short loops to run the operations in an optimal manner
Route From To Length Frequency No of % of OD
(km) (min) Buses captured
419 Ambedkar Old delhi 18 5 12 100
Nagar Railway
Station
419A Old Delhi Pant 10 15 4 33
Railway nagar
Station
419 B Pant Ambedkar 8 15 4 29
nagar nagar
37

38. Issues
• Permission needs to be sought from DIMTS for suggesting the
recommended short loop
• The PIS as well as display boards on the bus need to reflect
the new loops
• Scheduling needs to be changed
• The passengers need to be made aware of the changes in the
route by advertising in both electronic and print media

39. Conclusion
• Achievement: Based on Fuel Consumption analysis, Star Bus
redesigned its incentive scheme for the drivers by including fuel
efficiency as a criterion for performance.
• By employing scientific methods of bus performance monitoring,
improvements in the performance can be accomplished
• Scheduling should be flexible and should be different at different
times of the day based on travel times in the peak and off peak
hours
• Driver training can go a long way in improving fuel efficiency which
shall lead to saving of costs
• Innovative methods like using short loops optimizes bus operations

40. Thank You