Origin Destination Surveys OD调查…and Trip Generation Surveys…交通出行率调查 Sample Size (100 vehicles or more) of randomly selected vehicles that turned left to go south at Interchange/Intersection 8. In this Survey: 55% of samples went south past机场高速 45% turned right onto黄山大道 Total Left Turn Vol = 1630 vph Result: 900 vehicles (55%) go south 730 vehicles go west on黄山大道

1. Origin Destination Surveys OD调查
…and Trip Generation Surveys…
交通出行率调查

2. Project
Description 项
目概况
Project Setting
项目区域现状
Travel Demand
Analysis
交通需求分析
Transportation
Impact Analysis
交通影响分析
Transportation Mitigation Measures
交通改善措施
Appendix A, Appendix B, etc.
etc. 附录A, 附录B, 等等

3. But first…但首先，
Traffic Counts, REVISITED…
高峰时段交叉口交通流量调查,回访

4. Scoping Site in Advance for
Intersection Traffic Counts
计算前的准备工作
 Visit the project site
 take pictures of traffic controls and lanes 拍摄交通控制
和路面情况
 observe intersection conditions
 Minimize Complications in taking traffic counts
 Engineer should make determination of staff needs, in
advance.
 Timing of intervals, Recording
 Complications means LOST DATA and a bad count on the
day of survey.
 Incorrect Counts
 Missing Information.Wrong North Arrow, etc

5. Traffic Count Sheet: Hard to Interpret
交通流量调查问卷: 用中文很难解释
Problem:
Intersection mis-
labeled because road
closure was at
LongShouLu

6. Traffic Count Sheet: Incorrect Method
交通流量调查问卷: 错误的方法
Counted first...
5:30-5:45 pm
Counted second...
5:45-6:00 pm
Counted third...
6:00-6:15 pm

7. Traffic Count Sheet: Hard to Interpret
交通流量调查问卷:用中文 很难解释

8. Traffic Count Sheet: Only 15 Minute Count
交通流量调查问卷: 只有15分钟的流量调查

9. 15 Minute Count is Not Enough
15分钟流量调查不够
Left
Out
Right
Out
Left In Right In
3:30 12 8 16 12
3:45 20 16 24 28
4:00 20 4 8 24
4:15 32 28 12 24
4:30 32 8 20 48
4:45 16 16 24 52
5:00 28 12 32 64
5:15 32 20 32 88
5:30 40 24 28 92
5:45 16 12 72 104
6:00 40 12 60 116
6:15 32 8 20 60
What you get when you
multiply a 15 minute count by
4:
DIFFERENT RESULTS!
不同的结果
32 17 48 100
32 17 48 100
32 17 48 100
32 17 48 100
32 17 48 100
32 17 48 100
32 17 48 100
32 17 48 100
32 17 48 100
32 17 48 100
32 17 48 100
Actual:
Actual:
Actual:
Actual:
Actual:
Actual:
Actual:
Actual:
Actual:
Actual:
Actual:

10. 15 Minute Count is Not Enough
15分钟流量调查不够
 Long Hu Xi Juan 3 hr. Count. 龙湖西苑3小时流量调查 A real count.
 What happens when you multiply a 15 minute count
by 4 to “short-cut” the count process. 4当你计算15分
钟的流量，会发生什么？You get vastly different
hourly totals!你会得到不同的结果 Likely Incorrect.
很有可能是不正确的
0
20
40
60
80
100
120
140
3:30 3:45 4:00 4:15 4:30 4:45 5:00 5:15 5:30 5:45 6:00 6:15 Actual
Left Out
Right Out
Left In
Right In
Actual Peak HourTotal实际高峰时段总
Actual Peak HourTotal 实际高峰时段总
Actual Peak HourTotal实际高峰时段总
PeakHourVolume
左出口
右出口
左入口
右入口

11. We need to Count for:
 TWO HOURS minimum
 We find the peak HOUR from
these two hours of data.
 It cannot be guessed…
 …it is incorrect to multiply a 15
minute count by four(4) to get an
hourly total. 15min x 4 peak hour

12. 15 Minute Count is Not Enough
 This example shows that you get four very different answers
 The first 15 minutes x 4 is 15% of actual.
 The second 15 minutes x 4 is 25% of actual.
 The third 15 minutes x 4 is 50% of actual, etc. etc.
 The fourth set was close, but that was LUCKY
0
20
40
60
80
100
120
140
3:30 3:45 4:00 4:15 4:30 4:45 5:00 5:15 5:30 5:45 6:00 6:15 Actual
Left Out
Right Out
Left In
Right In
Actual Peak HourTotal
Actual Peak HourTotal
Actual Peak HourTotal
PeakHourVolume

13. Photo Documentation is very
Important and Helpful
龙寿路 /人兴路
LongShou / RenXing

14. Photo Location 1: 1
龙寿路 /人兴路
LongShou / RenXing
1

15. Photo Location 1: 2
龙寿路 /人兴路
LongShou / RenXing
1

16. Photo Location 1: 3
龙寿路 /人兴路
LongShou / RenXing
1

17. Photo Location 2: 1
龙寿路 /人兴路
LongShou / RenXing
2

18. Photo Location 2: 2
龙寿路 /人兴路
LongShou / RenXing
2

19. Photo Location 3: 1
龙寿路 /人兴路
LongShou / RenXing
3

20. Photo Location 3: 2
龙寿路 /人兴路
LongShou / RenXing
3

21. Photo Location 4: 1
龙寿路 /人兴路
LongShou / RenXing
4

22. ORIGIN DESTINATION SURVEYS
An Overview of

23. TDA: Origin Destination Surveys
 O&D and Mode Split Surveys OD&交通方式调查
 Different Methodologies.
 License Plate Study (video, audio, or handwritten)
 Check-Point / Intercept Interviews.
 Ask questions.在街上采访
 This can be at say, toll booth, or just on the street too.
 Video and Analysis. Observe. 视频和分析。守
 “Big Data” and BlueTooth “大数据”和蓝牙
 Phone Calls. Ask direct questions.拨打电话。提问
 Interpretation and Summary of Data
 Currently, Big Data has highest level of assumptions built into it,
because of:
 Limited data set comprised of cell phone users, or those that use blue tooth.
 Latency of up to a minute.

24. License Plate Survey, VIDEO
can “zoom in” later for clarity, engineer
just shoots video… easy
?
?
?
?
???
Can’t see all plates… this is a problem.

25. 20 video Cameras Survey
…filmed during PEAK HOUR. Got ALL plates.

26. License Plate Survey, AUDIO
Requires visual clarity, can be difficult
for engineer to see…
?
?
?
???
Again, Can’t see many plates… Problem.
??

27. One Solution: Expensive.
 When you want to get ALL cars, you need to put
a video camera on ALL lanes, and get EVERY car.
 You must use high speed camera shutter.
 You need an overhead bridge, or some other way
to get a clear shot
 You need a camera operator for EACH lane.
 Even with only two locations, you need 6-8
camera operators and 8 cameras total.
 One such study for one day cost $45k in USA,
and had only 6 locations (25 camera operators).

28. Another Solution: Sample.
 A sample is different than a strict license plate survey.
 A sample gives you percentages of what direction people
are going, but it is with a RANDOM selection.
 Random selection can be done with watching video in
office and choosing a car.
 Random selection can NOT be done by picking a license
plate, because it biases depending on the lane visible to the
engineer. Far lanes are difficult to see, and eliminating
those from the sample creates a bias that is unknown.
 Also, because the license plate method requires matching
of plate data at each end, if there are too many missing
plates in the sampling, this makes it less reliable. Hard to
quantify if there are many entrance and exit points being
surveyed.

29. Origin Destination
let’s watch the Green Truck

30. 人兴路 RENXING RD
VIDEO Origin & Destination SURVEY
A REALWORLD EXAMPLE:
Traffic Impact Analysis 交通影响分析

31. Project Description: Study Area
黄山大道

32. NEW ROAD? What Will Happen?

33. WB Traffic from JinKai

34. Traffic Will SHIFT with New Road

35. We had to define this
Traffic with an O&D Survey.
1. The traffic on the bridge was counted: 1630
2. Percentage of bridge to Freeway counted: 55%

36. Video Survey Corridors

37. Video Camera Tripod Locations

38. Selected Study Intersections

39. TOOK NEW TRAFFIC COUNTS
 Used iPhoneTraffic Count
Tool
 Used ManualTraffic Count
Sheet Method

40. Summary of Origin/Destination
 Traffic Count Data was used with O&D
Data
 Sample Size (100 vehicles or more) of
randomly selected vehicles that turned
left to go south at
Interchange/Intersection 8.
 In this Survey:
 55% of samples went south past机场高速
 45% turned right onto黄山大道
 Total LeftTurnVol = 1630 vph
 Result: 900 vehicles (55%) go south
 730 vehicles go west on黄山大道

41. Video Inspection Methodology
 In the video clips that follow, the
methodology used to sample traffic is set
forth.
 Video clips are “scrubbed” to watch a vehicle
very quickly, to see where it came from, and
to see where it went.

42. Origin Destination Samples
“Video Scrubbing Method”

43. Worksheet: Random Sampling of Vehicles

44. WB Traffic from JinKai
 PM Peak Hour is 2273 vehicles WB/SB on
金开大道. 1630 turns to go south on
人和大道. 643 goes west on 金开大道.
 55% of 1630 goes south on 人和大道
based on the O&DVideo Survey results.
 This is the control volume: 900
 45% of 1630 goes west on 黄山大道

45. Reassign Traffic from JinKai

46. NB RenHe to EB JinKai SHIFT?

47. Existing NB RenHe Traffic

48. Same Method Used
for NB Traffic: sampling
 Using Sampling methodology
lets the engineer multiple
percentage (%) values by the
TRAFFIC COUNT data to get
the amount of traffic that
would SHIFT.
 You need a statistically valid
sample size. At least 100
random samples.

49. Even the NB LEFT TURN traffic
is expected to SHIFT

50. Other Emerging Technologies
that can be used for O&D…
 BLUETOOTH
 How it works
 Advantages:
 It is time, date and location data, but needs interpretation
(bus passengers, bikes, peds, etc., mixed with car’s data)
 Can helps in determining paths and times
 Can be useful in timing studies, speed studies,O&D
 Disadvantages:
 It is just small sampling, not a traffic count
 Traffic counts still need to be performed.
 It is ONLY counting the cell phones that have blue tooth
turned ON
 Demographics of local Bluetooth users is not known
 Interpretation of data to determine car status, ped status,
bike, or even bus status…

51. Bluetooth Sampling Devices
can detect BTA phones, BTA computers, some cars

52. Bluetooth Sampling Technology
grabs a unique BT ID Address, and matches them

53. Bluetooth Sampling Technology
matches IDs at different measuring stations, and
computes travel times & speeds.

54. Bluetooth O&D Result Matches
Can also detect the path traveled (assumed),
depending on # of stations used. It’s still JUST
sampling… because not everyone uses bluetooth.
This kind of information is extremely helpful in setting up a travel
demand model, and calibrating it to real world conditions.
It is the trip distribution variable(s).

55. TRIP GENERATION SURVEYS
An Overview of

56. Trip Generation in USA
two thick manuals, 1500 pages,
users guidebook too.

57. Trip Generation in USA
 ITE Manual has 162 landuses
 China Manual has 36 landuses
 China manual can use more
categories and data.

58. Trip Generation Data in China is 5 times less than
what USA is using. More data is needed.
ITE Manual China Manual
162 landuses 36 landuses
ITE ITE ITE CHINA
ITE ITE
ITE says:

59. ITE Updates Trip Gen Manual
 Banking Industry, for example…
 ITE examined trip data for banks before and after
technology opened up ATMs and now Internet
Banking.
 Vehicle and Ped trips to the bank have gone down
significantly.
 Because of technology advances
 OlderTrip data for Banks (pre 2000) have been
removed to prevent skewing of data.
 Older data is discarded as our world changes.
 China is changing fast in many ways with vehicle
ownership UP, and large expansion of METRO lines.

60. ITE FORM only itemizes forTRUCKS. No PEDS. Mindset. Demographic
In China we also need to Count PEDESTRIANS and other MODES

61. Why would we need a
Trip Generation Survey?
 Lacking Data
 The ChinaTG Manual does not have rates for many land use
categories (such asVILLA, which is not in there)
 We,TYLIN, conducted aVILLA count because LongHu Project
hadVillas as a part of project.
 Villas have much higher vehicle trip counts than apts.
 Data Not Local. From another area of China
 Is it applicable?You will not know until you conduct aTG
Survey to find out if there are similarities.
 Are Demographics different?
 The Client has a New Land UseType, or a Hybrid
 Maybe the ChinaTG Manual does NOT have a hybrid but an
existing hybrid land use exists, and can be surveyed…
 If so, DO IT !

62. How to Scope a
Trip Generation Survey
 Define the Area to be surveyed
 The area should be a single land use type, such as
residential, or commercial, or institutional, etc.
 Identify all exit and entrance points.
 Trip Purpose:
 Find out the MODE SPLIT (car, ped, bike, etc)
 Find out theTrip Purpose (traffic model purposes)
 Training of Staff.
 Diagrams to help define specific duty.
 Photos to familiarize staff with area
 Execution coordinated by clock, overseen by supervisor

63. Example Project:
 礼嘉A区龙湖地块(A61-68)交通研究
 We had BeiJingTrip Rates already… but
 What should we use forTrip Generation?
 Since there is a residential apartment complex in the
City of ChongQing that was also developed by Long Hu
company (龙湖西苑 Long Hu Xi Juan), this is ideal and
similar. There are alsoVILLAS nearby across the street
 Find out pedestrian traffic
 Find out auto traffic
 This can be used forTraffic Study Project
 Also the 美地 MeiDiVillas development was surveyed
to get a sample of northern CQVilla trip generation.

64. PM Peak Person Trips / 100户数
(小户型)
Source:
ITE does not have PED data

65. PM Peak Person Trips / 100户数
(中户型)
Source:
ITE does not have PED data

66. PM Peak Person Trips / 100户数
(大户型)
Source:
ITE does not have PED data

67. PM Peak AUTO Trips / 100户数
(小户型)
Source:

68. PM Peak AUTO Trips / 100户数
(中户型)
Source:

69. PM Peak AUTO Trips / 100户数
(大户型)
Source:

70. Example: RESIDENTIAL Landuse
 Area in red is a
“closed” land use
area, gated, and filled
with 1683 residential
apartment units.
 There are several
locations to count
outside the fence
 Car entry/exit
 Pedestrian entry/exit
1683
DU

71. Example: RESIDENTIAL Landuse
1
3
5
4
4
2
 LongHuXiJuan
 Car Entry/Exit
 Ped Entry/Exit
 Also conduct an
O&D interview
 These areas all need
to be counted.
 6 locations.
 6 people.

72. Variables We Need to Know:
1
3
5 2
 how many cars total
(count at night,
garage, and street at
say, 2 am)
 population
 parking spaces
 shopping internal?
 other amenities
internal?
 Knowing these
variables lets us refine
ourTG information,
and even determine
parking needs, etc.
1683
DU

73. Count Location Photos
1
3
5
4
4
2
COUNT PEDESTRIANS
AND CARSTHAT GO IN
AND OUT OFTHESE
AUTO AND PED GATES,
FOR 3 HOURS

74. Count Location Photos
3
25
4
4
1
COUNT PEDESTRIANS
THAT GO UP AND
DOWNTHESE STAIRS
INTO LONGHUXIJUAN,
FOR 3 HOURS

75. Count Location Photos
3
1
5
4
4
2
COUNT PEDESTRIANS
AND CARSTHAT GO IN
AND OUT OFTHESE
AUTO AND PED GATES,
FOR 3 HOURS

76. Count Location Photos
3
5
4
4
2
1
COUNT PEDESTRIANS
THAT GOTO AND FROM
THIS SIDEWALK, FROM
LONGHUXIJUAN

77. Count Location Photos
3
1
5
4
4
2
COUNT PEDESTRIANS
THAT GO IN AND OUT
OFTHESE GATES FOR
3 HOURS (and how many
just go “through”)

78. Taking the Count: Location 1
3
1
5
4
4
2
COUNT PEDESTRIANS
AND CARS FORALL 6
MOVEMENTSON
DIAGRAM, FOR 3 HRS.
Peak hour:
5:15 pm-
6:15 pm

79. What We Get From Count:
 We get the total PEDESTRIANTraffic
that travels outside of the control area,
and “impacts” the street network and
sidewalks
 It is unknown how much of this traffic visits the
local shops and restaurants, but likely is a high
source.
 We get the total AUTOTraffic that
travels outside of the control area, and
“impacts” the street network.
 What we don’t know is how many
LongHuXiJuan residents who own cars, also
park their cars on the local street instead of the
internal garage. The streets are filled with
parked cars at night. It is likely that our “true”
AUTO trip generation rate is LOW in light of this.
Peds & Cars

80. COUNT RESULTS: Location 2
Peak
hour is
5:15-
6:15 pm

81. COUNT RESULTS: Location 4
Peak
hour is
5:00-
6:00 pm

82. COUNT RESULTS: Location 5
Peak
hour is
5:15-
6:15 pm

83. Comparing New with the OldPEDAUTO
MeiDi was higher, so
we used it
MeiDi was lower, so
we did not use it
LongHuXiJuan was
similar, so we used it
LongHuXiJuan was
similar, so we used it

84. Pedestrian Trip Generation Rates

85. Automobile Trip Generation Rates