MATSUYAMA CITY (USING PROBE PERSON DATA) 16-Sep TEAM G 2018 The - - PowerPoint PPT Presentation
ANALYSIS OF CAR BEHAVIOR IN MATSUYAMA CITY (USING PROBE PERSON DATA) 16-Sep TEAM G 2018 The Unive r sity o f To kyo, Japan & The Unive r sity o f Ce ntr al Punjab, Laho r e, Pakistan GROUP INTRODUCTION Ahsan Umer 1 University
(USING PROBE PERSON DATA)
The Unive r sity o f To kyo, Japan & The Unive r sity o f Ce ntr al Punjab, Laho r e, Pakistan
16-Sep 2018
University of Central Punjab, Lahore Pakistan The University of Tokyo, Japan
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❖ According to the PT survey conducted in 2007, car
usage is more than half showing the Expanding Car Usage in Matsuyama City ➢ Located in Ehime Prefecture on Shikoku Island (Western part of
Japan)
➢ Capital and Largest City
Ehime Prefecture with Population = 516, 643 (as of January 1, 2014), Area = 429.06 m2 and No. of Households = 229,916.
MATSUYAMA CITY
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Data Preparation for reducing computational load on RL Model Data (Given for Exercise) Probe Person (PP Data) Network Data Location Data
(Sequential GPS Log i.e. Latitude & Longitude)
Trip Data
(OD, Duration, Mode, Purpose)
Path Choice Can be Assumed
Combination Problem Approach
How to assume the Actual Path? Map Matching Algorithm FOCUS Central Area of Matsuyama City Extracted the OD Data and Network Data for Central Area of Matsuyama City Extraction of Data Reason of Extraction
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Focus on Central Area Attempts to make some roads Pedestrian Friendly Car Flow Restraint
(In central Area) 4
Whole City Central Area
Purpose of Trip Percentage shared by each Mode Purpose of Trip Percentage shared by each Mode
Legend
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➢ 𝜸-SCALED RECURSIVE LOGIT MODEL; OYAMA AND HATO 2016
➢ Consider a directed connected graph; 𝐻 = 𝐵, 𝑂 , where 𝐵 − set of links, 𝑂 − set of nodes ➢ The instantaneous random utility of a link 𝑏𝑘 condition on being in state 𝑏𝑘−1 is given by, ➢ The total utility of link 𝑏𝑘 given the state 𝑏𝑘−1 is formulated by sum of the instantaneous utility 𝒗𝒐 𝒃𝒌|𝒃𝒌−𝟐 and maximum expected downstream utility up to the destination link 𝑒, denoted as value function 𝑾𝒐
𝒆 𝒃𝒌
and defined by the Bellman equation (Bellman, 1957);
𝑾𝒐
𝒆 𝒃𝒌 = 𝐅
𝐧𝐛𝐲
𝒃𝒌+𝟐∈𝑩 𝒃𝒌
𝒘𝒐 𝒃𝒌+𝟐|𝒃𝒌 + 𝜸𝑾𝒐
𝒆 𝒃𝒌+𝟐 + 𝝂𝜻𝒐 𝒃𝒌+𝟐
∀𝒃𝒌𝝑𝑩
𝜸 is time discount rate represents the spatial cognition of driver for downstream links
𝑸𝒐
𝒆 𝒃𝒌+𝟐|𝒃𝒌 =
𝒇
𝟐 𝝂 𝒘𝒐 𝒃𝒌+𝟐|𝒃𝒌 +𝜸𝑾𝒐
𝒆 𝒃𝒌+𝟐
σ𝒃𝒌+𝟐
′
∈𝑩 𝒃𝒌 𝒇 𝟐 𝝂 𝒘𝒐 𝒃𝒌+𝟐
′
|𝒃𝒌 +𝜸𝑾𝒐
𝒆 𝒃𝒌+𝟐 ′
➢ LINK CHOICE PROBABILITY (MULTINOMIAL LOGIT MODEL)
𝒗𝒐 𝒃𝒌|𝒃𝒌−𝟐 = 𝒘𝒐 𝒃𝒌|𝒃𝒌−𝟐 + 𝝂𝜻𝒐 𝒃𝒌
Spatial Cognition about downstream, Degree of Spatial Cognition Existing Route Choice Models Sequential Route Choice Models IIA, Path Enumeration
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Variables Parameters t-Value
Travel Time
Right-Turn Dummy
β 0.4506658
L (0)
LL
Rho-Square 0.05146568 Adjusted Rho-Square 0.04910091
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Focus on Central Area of Matsuyama City Making “Transit Mall”
(A Pedestrian Friendly area)
Car Flow Restraint
(In central Area)
PROPOSED POLICY PRECEDING POLICY Hanazonomachi Avenue
Reduced the No. of Car Lanes from 4 to 2
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➢ 𝜸-SCALED RECURSIVE LOGIT MODEL; OYAMA AND HATO 2016 𝒗𝒐 𝒃𝒌|𝒃𝒌−𝟐 = Ѳ𝒖𝒖 𝒃𝒌|𝒃𝒌−𝟐 ∗ 𝑼𝑼 + Ѳ𝑺𝑼 𝒃𝒌|𝒃𝒌−𝟐 ∗ 𝑺𝑼 + 𝝂𝜻𝒐 𝒃𝒌
𝑸𝒐
𝒆 𝒃𝒌+𝟐|𝒃𝒌 =
𝒇
𝟐 𝝂 𝒘𝒐 𝒃𝒌+𝟐|𝒃𝒌 +𝜸𝑾𝒐
𝒆 𝒃𝒌+𝟐
σ𝒃𝒌+𝟐
′
∈𝑩 𝒃𝒌 𝒇 𝟐 𝝂 𝒘𝒐 𝒃𝒌+𝟐
′
|𝒃𝒌 +𝜸𝑾𝒐
𝒆 𝒃𝒌+𝟐 ′
𝒇𝑾𝒐,𝒖
𝒆
𝒃𝒌 = ቐ 𝟐 𝝂 σ𝒃𝒌+𝟑∈𝑩 𝒃𝑲+𝟐 𝒇 𝒘𝒐,𝒆 𝒃𝒌+𝟑|𝒃𝒌+𝟐 +𝜸𝑾𝒐
𝒆 𝒃𝒌+𝟑
aj+1 ≠ 𝑒 𝟏 aj+1 = 𝒆 𝐴 = 𝐍𝐴 + 𝐜 𝐴 = (𝑱 − 𝑵)−𝟐∗ 𝒄 𝐉 − 𝑸𝑼 𝐆 = 𝐇
Link Flows Equation:
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Central Area
(Without any change)
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Prohibit Cars in two (2) links
(The road in front of Central Station)
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Prohibit Cars in ten (10) links
(Case-1 + Hanazonomachi Avenue)
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Prohibit Cars in sixteen (16) links
(Case-1,2 + Making a Small Traffic Cell)
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Prohibit Cars in sixty (60) links
(Making a Large Traffic Cell)
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CASE-0 CASE-1 CASE-2 CASE-3 CASE-4
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