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Microscopic pedestrian studies consider detailed interaction
of pedestrians to control their movement in pedestrian traffic
flow. The tools to collect the microscopic data and to analyze
microscopic pedestrian flow are still very much in its infancy.
The microscopic pedestrian flow characteristics need to be understood.
Manual, semi manual and automatic image processing data collection
systems were developed. It was found that the microscopic speed
resemble a normal distribution with a mean of 1.38 m/second and
standard deviation of 0.37 m/second. The acceleration distribution
also bears a resemblance to the normal distribution with an average
of 0.68 m/ square second.
A physical based microscopic pedestrian simulation
model was also developed. Both Microscopic Video Data Collection
and Microscopic Pedestrian Simulation Model generate a database
called  TXY
database. The formulations of the flow performance or microscopic
pedestrian characteristics are explained. Sensitivity of the simulation
and relationship between the flow performances are described.
Validation of the simulation using real world data is then explained
through the comparison between average instantaneous speed distributions
of the real world data with the result of the simulations.
The simulation model is then applied for some
experiments on a hypothetical situation. The main purposes are
to gain more understanding of pedestrian behavior in one way and
two way situations, to know the behavior of the system if the
number of elderly pedestrian increases and to evaluate a policy
of lane-like segregation toward pedestrian crossing and inspects
the performance of the crossing. It was revealed that the microscopic
pedestrian studies have been successfully applied to give more
understanding to the behavior of microscopic pedestrians flow,
predict the theoretical and practical situation and evaluate some
design policies before its implementation.
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Abstract : The lack of information
about parkers' behavior in choosing a parking location in the
Central Business District makes it difficult to develop an effective
parking policy. The purpose of this study is to understand parkers'
behavior in choosing a parking location in the CBD of Surabaya.
Three types of parking location choice models were developed,
namely Parking Demand Regression Models, Analytic Hierarchy Process
and Multinomial Logit Models. The parkers' behavior in choosing
a parking location is mainly influenced by the availability of
parking spaces, trip purpose, search & queue time, walking
time, parking fee, security, and comfortability.
Source: Teknomo,
Kardi, and Kazunori Hokao, Parking Behavior
in Central Business District- A Case Study of Surabaya, Indonesia,
EASTS Journal, Vol. 2, 1997.
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Abstract: Toll collection can
have an open or closed system. In an open system, the users pay
the toll in either entrance or exit gate, while in a closed system,
they take a ticket in the entrance gate and pay the toll in the
exit gate. The structure of open and closed toll collection systems
can be simulated to get optimum locations that would generate
the highest revenue. Secondary data from the Tollway Authority
was used to construct an OD matrix. Elasticity of demand by changing
the price was used to model the reduced demand due to change in
structure of the toll collection. Several scenarios of structure
changes were proposed, simulated and evaluated. Evaluation concludes
that two open systems were the best scenarios for the tollway
and improvement in the toll collection of about 8% compared with
the existing condition.
Source: Teknomo,
Kardi and Gloria P. Gerilla, Simulation
of Toll Collection System in Surabaya-Gempol Toll way, EASTS
Journal, Vol. 3, no 6 1999.
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Teknomo,
Kardi, Yasushi Takeyama And Hajime Inamura, Tracking
System to Automate Data Collection of Microscopic Pedestrian Traffic
Flow, Proceeding of The 4th Eastern Asia Society For Transportation
Studies, Hanoi, Vietnam, pp. 11-25, Oct. 2001.
Kardi Teknomo, Yasushi Takeyama, Hajime
Inamura, Tohoku University, Japan
Abstract: To deal with many
pedestrian data, automatic data collection is needed. This paper
describes how to automate the microscopic pedestrian flow data
collection from video files. The study is restricted only to pedestrians
without considering vehicular - pedestrian interaction. Pedestrian
tracking system consists of three sub-systems, which calculates
the image processing, object tracking and traffic flow variables.
The system receives input of stacks of images and parameters.
The first sub-system performs Image Processing analysis while
the second sub-system carries out the tracking of pedestrians
by matching the features and tracing the pedestrian numbers frame
by frame. The last sub-system deals with a NTXY database to calculate
the pedestrian traffic-flow characteristic such as flow rate,
speed and area module. Comparison with manual data collection
method confirmed that the procedures described have significant
potential to automate the data collection of both microscopic
and macroscopic pedestrian flow variables.
Key Words: Microscopic, Pedestrian,
Image Processing, Automation, Tracking
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Teknomo,
Kardi, Yasushi Takeyama and Hajime Inamura, Measuring
Microscopic Flow Performance for Pedestrians, Proceeding
of the 9th World Conference on Transport Research,
Seoul, Korea, July 2001.
Kardi Teknomo, Yasushi Takeyama, Hajime
Inamura, Tohoku University, Japan
Abstract: A paradigm to improve the quality
of pedestrian movement by considering their interactions in the
microscopic level is introduced. By this approach, design of pedestrian
facilities is not merely space allocation but it can also utilize
other form of flow controls in space, time and direction. Although
microscopic pedestrian analysis exists, the microscopic pedestrian
data collection has not been developed. Once such microscopic
data is collected, another problem on how to measure the flow
performance from the microscopic data collection arises. This
paper describes how data reduction can be made to obtain pedestrian
flow performances. The automation of microscopic pedestrian data
from video files is also explained. The video data is converted
into numbers as a NTXY database. Following this conversion, the
rest of the process can be done using computers that reduce the
processing cost and speed, and improve accuracy. The data reduction
of NTXY database into well-established traffic flow variables
and some prominent flow performance was formulated. It was confirmed
that the procedures described have significant potential to automate
measurement of both microscopic and macroscopic pedestrian flow
performances.
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