1. Design, Pricing and Scheduling of Flexible Transit Systems (FTS)
- New Approaches and Case Studies in Jinan, China
Nan Zou, Shandong University, China

2. Location of Shandong University (SDU)

3. Flexible Transit Service (FTS)
Outline
Introduction
Flexible Transit Service (FTS)
Types and definition
Pricing
Design
Scheduling

4. Questions to be discussed
What is FTS
Who may want to use FTS
How much can people afford the service What are FTS design principals
How to schedule FTS
Case studies 1 2 3 4 5 6

5. Private motor vehicles
Service needs for FTS
Illustration only
Flexibility vs. cost only
Private motor vehicles
High
High
Taxi
Didi, Uber etc.
Flexibility
Car pool
Flexibility
Traditional Public Transit (light rail, metro, BRT, buses)
Low
Low
Low
High
Cost

6. Private motor vehicles
Service needs for FTS
Illustration only
Flexibility vs. cost only
Private motor vehicles
High
High
Taxi
Didi, Uber etc.
Flexibility
Car pool
Flexibility
Flexible Transit System
Traditional Public Transit (light rail, metro, BRT, buses)
Low
Low
Low
High
Cost

7. Purposes of FTS
With
Better flexibility
Mid-level cost
Improve public transit service to compete with other trip modes
Better sustainability of the entire transportation system
More riders of PT systems

8. What is FTS
Flexible route
Flexible station
Flexible service frequency

9. Review on Flexible Transit Systems
» Different types of FTS
1. Route deviation system
2. Point deviation system 3. Demand-responsive connector system
4. Request stops system
5. Zone route system
6. Flex-route segments system

10. Pricing analysis for FTS (Case 1)
Pricing study of converting an existing traditional transit route No. 131 to a FTS route (Jinan, Shandong Province, China)
Number of connecting routes
Transit hub: pink
Residential communities: dark blue
Newly developed office area: green Village: light blue

11. Same service frequency (Case 1)
B23d
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
5.5
6.0
6.5
7.0
7.5
8.0
8.5
9.0
9.5
10.0
g=1
-71
-69
-66
-64
-61
-59
-56
-54
-51
-49
-46
-44
-41
g=0.9
-39
-36
-34
g=0.8
-57
-52
-47
-42
-37
-32
-29
-27
g=0.7
-50
-45
-40
-35
-30
-25
-22
-20
g=0.6
-17
-15
-12
g=0.5
-33
-28
-23
-18
-13
-10 -8 -5
g=0.4 -3 2
g=0.3
-21
-16
-11 -6 -1 4 7 9
g=0.2
-14 -9 -4 1 6 11 14 16
g=0.1 19 21 24
ØYellow cells: fare too high, higher than taxi (7.5 Yuan)
ØGreen cells: feasible, but high subsidy rate required (>50%)
High subsidy is required if same service frequency during off-peak hours

12. Optimized service frequency (Case 1)Bd
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
5.5
6.0
6.5
7.0
7.5
8.0
8.5
9.0
9.5
10.0 g= 1
-45
-35
-25
-15 -5 5 15 25 35 45 55 65 75
0.9
-41
-31
-21
-11 -1 9 19 29 39 49 59 69 79
0.8
-37
-27
-17 -7 3 13 23 33 43 53 63 73 83
0.7
-32
-22
-12 -2 8 18 28 38 48 58 68 78 88
0.6
-28
-18 -8 2 12 22 32 42 52 62 72 82 92
0.5
-24
-14 -4 6 16 26 36 46 56 66 76 86 96
0.4
-19 -9 11 21 31 41 51 61 71 81 91
101
0.3 85 95
105
0.2 89 99
109
0.1 -6 4 14 24 34 44 54 64 74 84 94
104
114
ØBlue circles: feasible fare and subsidy rate
Conclusion: with optimized service frequency, it is possible to run the FTS without subsidy

13. Survey on FTS service In Jinan 3 main categories
Questionnaire survey in Qilu soft park
About 13,000 employees working in the park.
20% sampling rate
3000 copies are distributed
2403 copies are confirmed to be qualified
response rate > 75%
3 main categories
Demographic characteristics
Public transit satisfaction (RP)
Flexible transit system related (SP)
RP: revealed preference survey
SP: stated preference survey

14. Survey on FTS service Flexible transit system related results:
58.8%: willing to use this type of system
20.5%: were very likely to use the system
For those who unwilling to use:
56.8% don’t want to pay the additional fee
27.0% worried that the vehicle can’t arrive on time
Top valued characteristic:
Flexibility
Reliability of the arrival time
Acceptable maximal fare
3-4 RMB (Bus: 1-2 RMB; Taxi: 8 RMB)

15. Scheduling model for FTS
(Serving 2 transit hubs)
» Objectives
Minimize
Total difference between the actual and the expected departure time
ååålijYijk + å(åå XrktTt - tar ) + å(| åå XrktTt - trr |)
i j k r k t r k t
(6.2a)
Total transfer time
Total travel time
» Target linearization
Zr =| åå XrktTt - trr |
k t
åå XrktTt - trr £ Zr k t
trr - åå XrktTt £ Zr k t

16. Optimization of total travel time and the service quality1
é nk ìï
ùüï K å å
MIN a t
+ tr y (nk )úý ûïþ í ê
k =1 ë i=1 2Z
r r r ïî
k ( i-1) ki
knk k 0 2Z å j
( )
( ) å j
+ b é ù
+ d é ù
D max
a - s , 0
D max
s - b , 0 ë û ë û j j j j j j 2 3
Ø Ø Ø
Total travel time of the fleet Early arrival
ate arrival 1 2 3

17. Case study in Jinan 2 118 20座 30座 车型 配车数量 (辆) 运行线路 运行时间 (min)5 14
20座车型线路 6
30座车型线路 1 18 15 T 7 19 16 2 11 8 9 10 13 20 3 4 17 12 车型
配车数量 (辆)
运行线路
运行时间 (min)
20座 2
118
30座

18. Research contributors
Dr. Shuliang Pan
Ph.D. of 2015
Lin Zhu
Ph.D. candidate
Ying Wang
Master of 2013
Shuai Ding
Master of 2016
Dr. Jie Yu
Associate Professor
Dr. Nan Zou

19. Conclusions and remarks
Needs of FTS
Different purposes and types
Still a challenge to operate a real dynamic FTS

20. Conclusions and remarks
But, can FTS “win”?

21. Nan Zou nanzou@sdu.edu.cn
Mobilize Yichang
Design, Pricing and Scheduling of Flexible Transit Systems (FTS)
- New Approaches and Case Studies in Jinan, China
Thanks.
Comments please.
Nan Zou