4. ? 5 laboratories in 2 departments (Civil Eng. and Interdisciplinary Eng.)
? 7 staffs and 2 affiliate professors
? Traffic engineering, transport planning, travel behaviour analysis, transport
economics, transportation in developing countries, and urban studies
? About 15 Ph. D., 35 MSc., and 12 Undergraduate Students
? http://transport-titech.jp
5. Staffs@TSU-TokyoTech
Yasuo ASAKURA (Professor)
? Traffic Engineering and Transport Planning
Tetsuo YAI (Professor)
? Regional and Urban Planning
? Transport for Environment
Shinya Hanaoka (Professor)
? Transport Development Studies
? Air Transport
? Transport Logistics
? Transport Infrastructure Management
17. 問題意識「電力自由化は,非平常時の安定的な電力供給を阻害するのでは?」
→日本の送電網ネットワークを模擬したシミュレーション分析
Maximum
power
output of
the plants
[1,000
kWh]
Importance Value of the largest plants in each region
Owned by
(General
Electric
Utility)
Type of
generating
of the plants
Before the deregulation
After the
deregulation
Hokkaido Coal-fired 1650 0.01013 0.01498
Tohoku LNG-fired 5202.8 0.00933 0.05305
Tokyo Oil-fired 5204 0.00012 0.00548
Chubu LNG-fired 4802 0.00713 0.01325
Hokuriku Oil-fired 1500 0.00012 0.00548
Kansai LNG-fired 2173 0.01396 0.00986
Chugoku LNG-fired 1400 0.00662 0.00802
Shikoku Oil-fired 1448 0.00012 0.00548
Kyusyu LNG-fired 2295 0.00787 0.00987
Okinawa LNG-fired 502 0.00269 0.00575
電力供給ネットワークの脆弱性分析
17
* All atomic power plants are not included
21. 1) Mobile device has its unique ID (MAC address) and
continuously
emits a probe request (PR) to connect access point2) WifiScanner automatically captures a PR which contains unique ID
Example of recorded data
WifiScanner
Capture
d Site Unique ID datetime
3 Iho 72 2017/8/14 12:00
3 Iho 72 2017/8/14 12:25
3 Iho 72 2017/8/14 15:00
WifiScanner
Detection of travel pattern
Principle of Wi-Fi Packet Sensing
4
22. Survey period: (45 days)
Aug. 6. 2017 - Sep. 19. 2017
Number of WifiScanners:
62 devices in 53 sites
Survey in Okinawa Main Island
5
Naha City
23. Appendix
Basic analysis:
Duration of stay Number of visit
Duration
(hour)
minimum median mean max
0.042 75.61 78.34 191.32
No. visit minimum median mean max
2 5 5.29 27
24. Appendix
Basic analysis: Area OD table
Inside Naha city trips
As the Entrance of Okinawa island
Area trips
Area origin and destination table
Naha city and other areas
Motobu peninsula and middle area
Statistical nalysis
Total tour patternTendency just between trips
26. 26
Structure of tourists’ travel behavior model
Rental car office
(Shin Chitose/Asahikawa)
Asahikawa Furano Sunagawa
First-destination choice
Duration of stay
Continue End
Excursion choice
Furano SunagawaAsahikawa
Explanatory variables
!"#$%&: Travel time between area " & (
)*+,-&: Number of tourism spots in area (
Indicator of attractiveness
)$.-+/&:Visits during lavender season
(Furano and Kamifurano)
Duration (stay time) 011"2.3&: Arrival time at area (
Continue End
Excursion choice
Furano SunagawaAsahikawa
4$5,,"#$: Remaining time for sightseeing
!"#$%&, )*+,-&, )$.-+/&
7"-",$8&: Number of visits in area (
i : origin
k : destination
Assumption: Tourists continue to choose each destination
sequentially while considering time constraints.
Continue to the next day…
27. 27
Number of staying people by time-of-day
(lavender season)
Policy (1) might attract more tourists to Kamifurano area
and mitigate the concentration in Furano area
Implementation of Policy (1)
<Simulation setting> Variable of “No. tourism spots” in Kamifurano area is multiplied by 1.2
Policy (1):Increase the attractiveness in Kamifurano area
Change in the no. visitors (by %)
for each area
Furano
Kamifurano
1
5
4
3
2
6
7
10km
-7.3%
+50%
-9%
-9.8%-12%
-5.6%
+4.2%
28. 28
Number of staying people by time-of-day
(lavender season)
Implementation of Policy (2)
Policy (2):
Increase the attractiveness in Furano area only during off-peak time
1
5
4
3
2
6
7
10km
-2.8%
+2.1%
+9%
-4.9%-0.7%
0
+1.1%
Furano
PeakOff-peak Off-peak
N=794
<Simulation setting> Variable of “No. tourism spots” in Furano area is multiplied by 1.2 during off-peak time
Change in the no. visitors (by %)
for each area
35. 36
Process and context in choice models
Moshe Ben-Akiva & André de Palma & Daniel McFadden & Maya Abou-Zeid &
Pierre-André Chiappori & Matthieu de Lapparent & Steven N. Durlauf &
Mogens Fosgerau & Daisuke Fukuda & Stephane Hess & Charles Manski &
Ariel Pakes & Nathalie Picard & Joan Walker
Mark Lett (2012) 23:439–456
DOI 10.1007/s11002-012-9180-7
Preferences
Plan Choice
Attitudes,Affect,
Perceptions / Beliefs
Opportunities,
Constraints,
Information