LAX Project

• Zenaida A. Barredo• Alley Cheung• Arsen Der-

Aphrahamian• Lucy Harutyunyan• Lernik Rostami• Gevik Shahverdi

Why Tom Bradley ?• It's an international terminal. Therefore, it is very busy most of

the time, and there are enough passengers to sample for our project.

What was measured …..• Loading/Unloading time• Number of cars passing by vs. stopping at departure• Means of transportation (taxi, bus, shuttle, private car)• Reason of trip (vacation vs. business)• Local vs. visiting passengers

What we found out…• Taxis do not create traffic. In fact, private cars create the traffic

because:• They are lost• Loading/unloading takes longer

• Saying good bye to their relatives (hugging, emotions, etc.) which is time consuming

• Also, taxis have specific spots to load/unload passengers and luggages

Video

• Video

Layout of LAX

Methodology• Surveys with taxi drivers & traffic enforcement officers.• Compared cars passing by and cars stopping.• Measured loading and unloading time.• Survey with passengers to establish what determines decision

in their choice of transportation.• Quantitative Measures- Anova, Binomial, F-test, Inference

about Pairs of treatment Means.

Probabilities of Vehicles to take <1minute to load/unload

Probabilities of Vehicles to take 1.1-2 minutes to Load/Unload

1 2 3 4 5 6 7 8 9 10 110.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

TAXI CABS Departure TAXI CABS Arrival PRIVATE CARS Departure PRIVATE CARS Arrival SHUTTLES Departure

Probabilities of Vehicles to take >2 minutes to load/unload

1 2 3 4 5 6 7 8 9 10 110.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

TAXI CABS Departure TAXI CABS Arrival PRIVATE CARS Departure PRIVATE CARS Arrival SHUTTLES Departure

Probabilities of Vehicles Stopping By

1 2 3 4 5 6 7 8 9 10 110.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

Taxi cabsShuttlesPrivate cars

Probabilities of Vehicles Passing By

1 2 3 4 5 6 7 8 9 10 110.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Taxi cabsShuttlesPrivate cars

ANOVA Departure

SUMMARY

Groups Count Sum Average Variance

Taxi 44 3865 87.84091 3429.579

Shuttles 33 1577 47.78788 1243.047

Private 38 5587 147.0263 24262.51

ANOVA

Source of Variation SS df MS F P-value F crit

Between Groups 178573.6 2 89286.79 9.21702 0.000197 3.077309

Within Groups 1084962 112 9687.164

Total 1263536 114

ANOVA Arrival

SUMMARY

Groups Count Sum Average Variance

Taxi 60 2666 44.43333 737.3345

Private 76 8653 113.8553 10045.41

ANOVA

Source of Variation SS df MS F P-value F crit

Between Groups 161591.8 1 161591.8 27.17164 6.88E-07 3.911795

Within Groups 796908.1 134 5947.076

Total 958499.9 135

Taxi

Private

0 100 200 300 400 500 600 700

ZeroMin - Q1Q 1 - MedianMedian - Q2

Box plot comparison of 115 observations loading and unloading times for Taxis, shuttles and POVsDeparture area

Box plot comparison of 137 observationsloading and unloading times for Taxis and POVs Arrival area

Taxi

Shuttle

Private

0 100 200 300 400 500 600 700 800

ZeroMin - Q1Q 1 - MedianMedian - Q2

Anova- Taxi vs Non-Taxi

SUMMARY

Groups Count Sum Average Variance

count of ppl took taxi 21 59 2.8095238 1.261905

count of ppl did not take taxi 29 74 2.5517241 1.970443

ANOVA

Source of Variation SS df MS F P-value F crit

Between Groups 0.809491 1 0.809491 0.483215 0.490321 4.042652

Within Groups 80.41051 48 1.6752189

Total 81.22 49

Anova- Local vs. Visitors

SUMMARY

Groups Count Sum Average Variance

count of ppl local 34 84 2.470588235 0.923351159

count of ppl visitors 33 81 2.454545455 0.943181818

ANOVA

Source of Variation SS df MS F P-value F crit

Between Groups 0.00431 1 0.004310001 0.004618944 0.946024 3.98856

Within Groups 60.65241 65 0.933113945

Total 60.65672 66

Anova- Business vs. Vacation

SUMMARY

Groups Count Sum Average Variance

count of ppl on business 19 42 2.210526 0.508772

count of ppl on vaca 31 91 2.935484 2.195699

ANOVA

Source of Variation SS df MS F P-value F crit

Between Groups 6.191138 1 6.191138 3.960804 0.052283 4.042652

Within Groups 75.02886 48 1.563101

Total 81.22 49

ANOVA- Taxi vs. Private Car

Anova: Single Factor

SUMMARY

Groups Count Sum Average Variance

Taxi 60 2666 44.43333 737.3345

Private 76 8653 113.8553 10045.41

ANOVA

Source of Variation SS df MS F P-value F crit

Between Groups 161591.8 1 161591.8 27.17164 6.88E-07 3.911795

Within Groups 796908.1 134 5947.076

Total 958499.9 135

Taxi other Locals Visitors Business Vacation 0

5

10

15

20

25

30

35

Series1

Comparison of 50 observations based on three different categories•Passengers (groups) who took a taxi vs. passengers who chose other vehicles•Local passenger (groups) vs. visitors•Business travelers vs. leisure travelers (count of parties)

Box plot comparison of 50 observations based on three different categories•Passengers (groups) who took a taxi vs. passengers who other vehicles•Local passenger (groups) vs. visitors•Business travelers vs. leisure travelers (count of parties)

taxi

other

locals

visitors

business trip

vacation

0 1 2 3 4 5 6 7

ZeroMin - Q1Q1 - MedianMedian - Q2

Conclusion• No conclusion on why travelers chose to take taxi• Failed to find a relationship between • Locals vs. Visitors• Business vs. Leisure• Taxi Cab vs. Other Transportations

• Thus, these factors do not matter• Private cars are the most counted to load/unload passengers• Private vehicles take a significantly longer time to load and

unload• Traffic congestion in LAX is mainly caused by private cars not

taxi cabs

Recommendations• Increase uniformed personnel/traffic coordinators• Limit the loading and unloading time at curbside to 2 minutes• Strictly enforce traffic regulations• Set up electronic signs• Send out traffic alerts within LAX• Provide alternate location for passengers in tour groups• Provide 15 minutes free parking