Cross-cutting Issues

This paper describes the situations of Intelligent Transport Systems (ITS hereinafter) in developing countries, especially Asian countries and a study of recommended approaches to introduce ITS in a provisional country. So far, ITS has been regarded as a system for the developed countries. However, looking at traffic problems such as accidents and congestion, we recognize that developing countries have the same or worse situations compared to the developed countries.

ITS America

Kobe University - Graduate School of Science and Technology

Presented at the 10th ITS Annual Conference and Exposition, May 1-4, 2000 Boston, MA

This paper investigates variations of road performance and traffic demand by the seasons on
urban expressway. Authors have been analysing the influence of several external factors such
as time of a day, day of a week, weather and commercial custom onto fluctuations of road
performance and traffic demand in the former study (1). And it was concluded that all the
factors except commercial custom have a big influence onto the performance and demand.
The season is considered as a new external factor in this study. Travel time obtained by
automatic license plate detector is used for grasping the road performance and its variation.
The path flows estimated by a dynamic path flow estimation model are used as a traffic
demand. For clarifying the reason of the road performance degradation, the relationship
between the performance and the demand is analysed utilising cluster analysis. It is found that
the season is one of the most important external factors on the variations of performance and
demand.

Kyoto Sangyo University

Gifu University

Presented at the 15th World Congress on Intelligent Transport Systems, November 16-20, 2008, New York, New York

Telvent Farradyne is a national leader in traffic technology planning, design, implementation,
operation, and maintenance. As part of the support rendered to the Kansas City Scout freeway
management system, Telvent conducted an evaluation of cellular probe technology for providing
real-time traffic information. The particular system evaluated, TrafficSense from Cellint, uses
cellular signals to assess a phone’s location and speed, and then data from all cell phone probes
on a given segment are aggregated and stripped of personal information. The travel times or spot
speeds are displayed on a web-based map or delivered to a transportation agency. Cellint and
the Kansas Department of Transportation (KDOT) agreed to conduct a pilot project in the
Kansas City area. From June 20 t o August 20, 2006, Cellint logged speed data for both
directions of traffic on I-435 from Pflumm on the west end to the intersection of I-435, I-470,
and US-71 on the east end. The Cellint data was compared with analogous data logged by
Scout’s vehicle detector stations (VDS), which at that time were all inductive loop detectors.
Following the completion of the evaluation period, several performance measures were
investigated to determine their utility in comparing the two data sets. It should be noted that
while Cellint can provide point to point travel times, the Scout VDS array on I-435 was too
sparse at the time of the test to accommodate the calculation of travel times.

Telvent Farradyne Inc.

Presented at the 15th World Congress on Intelligent Transport Systems, November 16-20, 2008, New York, New York

The primary objective of this paper is to study and analyze the temporal characteristics of
traffic congestions and the associated speed distributions for congested expressways based on
the Floating Car Data (FCD) in Beijing. First, the temporal distributions of congestions with
different intensities are analyzed using the FCD of 5 workdays for a particular expressway
Link N26376. Results show that the longer the continuous congestion lasts, the lower the
speed distribution interval is. Then, the distribution curve is fitted, which finds that the
Log-Logistic model can well describe the survival function distribution of the severe
congestion durations for morning peak-hours of Tuesday. By comparison, it is found that the
duration distribution value of severe congestions at the aggregation interval of 2-minute is
lower than that at the 5-minute interval, and the duration distribution value of severe
congestions on Link N26376 is higher than that on its downstream Links N24162 and N23971.
Finally, the speed distributions in two proposed categories of congestion periods are analyzed
and compared. Results show that if the speed in the present time period falls in a higher
distribution interval, then the probability that the severe congestion will dissipate in the next
time period will be higher.

Authors: Lin Zhu, Lei Yu, Huimin Wen

Presented at the 18th World Congress on ITS, October 2011, Orlando, Florida

The primary objective of this paper is to study and analyze the temporal characteristics of

traffic congestions and the associated speed distributions for congested expressways based on

the Floating Car Data (FCD) in Beijing. First, the temporal distributions of congestions with

different intensities are analyzed using the FCD of 5 workdays for a particular expressway

Link N26376. Results show that the longer the continuous congestion lasts, the lower the

speed distribution interval is. Then, the distribution curve is fitted, which finds that the

Log-Logistic model can well describe the survival function distribution of the severe

congestion durations for morning peak-hours of Tuesday. By comparison, it is found that the

duration distribution value of severe congestions at the aggregation interval of 2-minute is

lower than that at the 5-minute interval, and the duration distribution value of severe

congestions on Link N26376 is higher than that on its downstream Links N24162 and N23971.

Finally, the speed distributions in two proposed categories of congestion periods are analyzed

and compared. Results show that if the speed in the present time period falls in a higher

distribution interval, then the probability that the severe congestion will dissipate in the next

time period will be higher.

School of Traffic and Transportation, Beijing Jiaotong University

Texas Southern University

Beijing Transportation Research Center

Presented at the 18th World Congress on ITS, October 2011, Orlando, Florida