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Mode Choice Analysis with Imprecise Location Information Toshiyuki - - PowerPoint PPT Presentation

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Mode Choice Analysis with Imprecise Location Information Toshiyuki Yamamoto & Ryosuke Komori Nagoya University Background Public transit such as LRT and Flexible bus is regarded one of the alternatives for EST projects, which improves

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Mode Choice Analysis with Imprecise Location Information

Toshiyuki Yamamoto & Ryosuke Komori Nagoya University

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2006/08/17 2 IATBR2006

Background

 Public transit such as LRT and Flexible bus is

regarded one of the alternatives for EST projects, which improves the access and egress conditions to public transit.

 Centroid of TAZ is used as the origin and

destination in conventional mode choice models

Location information of trip is not precise enough

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2006/08/17 3 IATBR2006

Objective Effective use of large-scale person trip data to investigate the effects of access condition to the station and bus stop by

 Combine information to get precise location

information

 Develop a model to overcome the

impreciseness

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2006/08/17 4 IATBR2006

Chukyo Metro. Person trip data

10 10 10. 10.5 9. 9.9 8. 8.3 1. 1.4 2. 2.1 3. 3.1 6. 6.4 56. 56.3 49. 49.4 39. 39.2 31. 31.3 14. 14.5 16. 16.9 17. 17.9 12. 12.9 17. 17.8 21. 21.1 29. 29.9 41. 41.2 0% 0% 20% 20% 40% 40% 60% 60% 80% 80% 100% 100% 2001 2001 1991 1991 1981 1981 1971 1971 Trai ain Bu Bus Car ar Mot

  • to.
  • .

Wal alk

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2006/08/17 5 IATBR2006

Zone system

 True access = 730 m

Ground truth

Destination

Station A Station B

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2006/08/17 6 IATBR2006

Zone system

 True access = 730 m  Access to zonal centroid = 490 m

Zone system

Destination

Station A Station B

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2006/08/17 7 IATBR2006

Zone system

 True access = 730 m  Access to zonal centroid = 490 m  If larger zone system is used = 330 m

Larger zone system

Destination

Station A Station B

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2006/08/17 8 IATBR2006

Choice structure

Nested logit model with

 Line haul mode in upper level  Access and egress modes for train in lower level Train Bus Car Line haul Walk Walk Access & egress Walk Bus Bus Walk Bus Bus Car Walk Car Bus

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2006/08/17 9 IATBR2006

Our approach: egress

 Trip to governmental office, hospital and school

can be identified by information on destination type

 Multiple governmental offices are not located

together, and usually, one zone contain at most

  • ne governmental office

 The same thing applies hospital and school

 Note: trips to small clinics might be included as noise

 Precise location and access to station and bus

stop is calculated by using GIS data

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2006/08/17 10 IATBR2006

Gifu City Nagoya City Toyota City Yokkaichi City Destination

Destinations 20 zones with largest number of trip destinations for each type

  • f destination

are used

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2006/08/17 11 IATBR2006

Descriptive analysis

Relationship between egress and auto share

0% 20% 40% 60% 80% 100% 1 2 3 4

イグレス距離（km） 自 動 車 分 担 率 （％）

官公庁 病院 学校

Auto share Egress (km)

Gov. Hospital School

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2006/08/17 12 IATBR2006

  • Gov. office: 1981 to 2001

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60 距離（km） 自動車分担率 1981 1991 2001

Auto share Distance (km)

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2006/08/17 13 IATBR2006

Hospital: 1981 to 2001

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 1 2 3 4 5 6 距離（km） 自動車分担率 1981 1991 2001

Auto share Distance (km)

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2006/08/17 14 IATBR2006

School: 1981 to 2001

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 1 2 3 4 5 6 距離(km) 自動車分担率 1981 1991 2001

Auto share Distance (km)

This university operated school bus from station

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2006/08/17 15 IATBR2006

Location choice in motorization

Hospitals which located after 1970 Year Length (km) Rank Hospital A 1984 4.9 1st/16 Hospital B 1974 2.9 4th/16 Hospital C 1972 2.8 5th/16 Buildings which moved after 1960 Length （km） Year Before After Municipality Hall D 1966 1.1 1.4 City Hall E 1976 0.2 1.0 Hospital F 1974 0.4 0.8 Hospital G 1978 0.6 0.6

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2006/08/17 16 IATBR2006

Our approach: access

 About home-based trip, it is impossible to

identify the house, origin of the trip

 Census data provide distribution of

residents of specific age/sex within survey zone

 Access length is treated as probabilistic

variable in estimating the mode choice model

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2006/08/17 17 IATBR2006

Calculation of choice probability

Access ＝２４０ｍ Probability of living this city block e.g.）２０ yrs. Male →３.３％ ４０ yrs. Male →７.７％ Smaller city block

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2006/08/17 18 IATBR2006

Calculation of choice probability

 Q(j): Probability of living in city block j

 Calculated by census and treated as known

 P(i| j): Probability of choosing mode i given that

he lives in city block j

 Precise access information is used as explanatory

variable

 P(i): Marginal probability of choosing mode i is

calculated by P(i| j)Q(j)

 Unknown parameters to be estimated are only

utility function, which is indifferent among Q(j)

∑

j

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2006/08/17 19 IATBR2006

Effects of preciseness of egress info. （zone system is used for access）

GIS based egress has

 Better log-likelihood  Larger coefficient estimates in absolute value

GIS based Zone system Upper level Bus egress

  • 2.0 (-3.4)
  • 1.7 (-4.2)

Lower level

  • Sta. egress
  • 2.8 (-18.9)
  • 1.8 (-17.8)

Log-likelihood

  • 2944
  • 3063

Coefficient estimate and t-stat. in parenthesis

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2006/08/17 20 IATBR2006

Effects of preciseness of access （GIS base is used for egress）

Proposed model Zone system Larger zone Upper level Bus access

  • 9.2 (-5.6)
  • 2.5 (-8.8)
  • 2.5 (-9.3)

Lower level Bus access

  • 1.4 (-4.0)
  • 1.2 (-4.6)
  • 1.1 (-4.7)
  • Sta. access
  • 1.4 (-11.9) -0.8 (-11.8)
  • 0.7 (-11.0)

Log-likelihood

  • 2900
  • 2944
  • 2944

Coefficient estimate and t-stat. in parenthesis Proposed model has

 Better log-likelihood  Larger coefficient estimates in absolute value

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2006/08/17 21 IATBR2006

Comparison between access & egress

Use of bus: access to bus stop from home is dominant

Terminal mode for train: egress has larger effect than access

Access: proposed method Egress： GIS based Upper level Coef. t-stat. Bus access

  • 9.2

(-5.6) Bus egress

  • 1.8

(-3.2) Lower level

  • Sta. access
  • 1.4

(-11.8)

  • Sta. egress
  • 2.9

(-18.7)

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2006/08/17 22 IATBR2006

Conclusion

 Efficient use of conventional person trip data is

proposed, and confirmed by empirical analysis

 Rail ridership can be increased by locating

closer to station, but move from 3 km to 2 km doesn’t mean anything

 Egress from station is more important than

access to station

2

ρ