GUJARAT TECHNOLOGICAL

UNIVERSITY

BIRLA VISHWAKARMA MAHAVIDHYALAYA

PAPER REVIEWED

1. Assessment of Link Reliability as Function of Congestion

components.

KUSHALKUMAR G PATEL

140080713009

Assessment of Link Reliability as a Function of Congestion Components

This paper is written by Srinivas S. Pulugurtha,

Associate Professor, Civil and Environmental Engineering

dept., Univ. of North Carolina at Charlotte. & Nagaswetha

Pasupuleti Graduate Student, Civil and Environmental

Engineering, Univ. of North Carolina at Charlotte.

This paper is part of the Journal of Transportation

Engineering, Vol. 136, No. 10, October 1, 2010.

INTRODUCTION

Increasing travel congestion has been a growing concern to

engineers and planners of the states’ DOT, responsible local

agencies, the general public and elected officials due to its

impact on mobility and economy.

Congestion, in general, reduces the capacity of the roadway

and makes the traffic condition unstable.

As congestion increases, reliability of travel becomes an

increasingly important attribute for users of transportation

networks

ABSTRACT

The focus of this paper is to develop and illustrate the

working of a geographic information systems GIS based

methodology to estimate congestion and assess reliability of

links on a road network considering both recurring and

nonrecurring congestion components by time period of the

day.

The estimated reliability can be used to identify optimal travel

paths and make better routing decisions

For this research data collected was for the city of Charlotte

in Mecklenburg County, North Carolina which are used to

demonstrate the methodology.

LITERATURE REVIEW

This paper is an extension of earlier efforts by the writers

Pulugurtha and Pasupuleti in 2008, to address the limitations

of past research by defining and estimating reliability of each

link in the transportation network as a function of travel time

variation and travel delay index due to crashes.

Past research does not consider the effect of factors such as

crashes related to nonrecurring congestion component

along with recurring congestion component in estimating

congestion and/or reliability for all the links on major roads in

the transportation network.

METHODOLOGY

The purposed methodology used to determine the travel time

and travel delay due to crash recurring and non- recurring

congestion include the following steps:

◦ Data collection.

◦ Estimate travel time and its variation under recurring congestion

conditions.

◦ Estimate travel delay due to crashes under nonrecurring

congestion conditions.

◦ Integrate congestion components to compute congestion

score and reliability.

Four different time periods were considered for research

purpose in this paper:

◦ AM Peak period - 6.30am to 9.30am

◦ MIDDAY Off-peak period - 9.30am to 3.30am

◦ PM Peak period - 3.30pm to 6.30pm

◦ NIGHT Off-peak period – 6.30pm to 6.30am

For calculating recurring congestions (RC) travel time and its

variation data for each link requires link capacity, travel

speeds, and traffic volumes for each time period.

While for Non-recurring congestions (NRC) past crash data,

temporary changes in networks and the delays related to it

will be needed such historical data information will be

available from local agencies.

The Data was collected for total of 1053.2 miles in

Charlotte city

METHODOLOGY- Step: 1 Data collection

For calculating travel time equation by fundamental bureau of

public roads was used.

Once the travel time is known RC will also be determined

from it by using the below equation.

METHODOLOGY- Step: 2 Estimate travel time

and its variation under recurring congestion

conditions.

NRC occurred in a particular link can be calculated by using

the following equation:

METHODOLOGY- Step: 3 Estimate travel delay

due to crashes under nonrecurring congestion

conditions.

TYPE OF CRASH CRASH SEVERITY VALUE

A FATAL 8

B SEVERE 6

C LESS SEVERE 3

O(PDO) PROPERTY DAMAGE

ONLY

1

METHODOLOGY- Step: 4 To compute

congestion score and reliability.Congestion score can be calculated by using the following

series of equations:

METHODOLOGY- Step: 4 To compute

congestion score and reliability.

In the above equations we need to note that Maximum

possible congestion for RC and NRC for any link is 100

And the term WR & WNR are the weight(Importance) for the

link has to be logically decided by looking over the link

capacity and volume.

RESULT AND ANALYSIS

The data collected from the study areas in the city of

charlottes was of 1053.2 miles and the recurring

congestions, non recurring congestion and congestions

score were found out and plotted on map using GIS module.

The least the congestion score of the link the more the

reliable will be the link.

Travel time value per unit distance mile is calculated for each

link on selected major roads in the city of Charlotte, N.C.

The links are classified into the following five groups based

on their travel time per mile:

0.70 (speed=85 mi / h) to 1.00 min (speed=60 mi / h)

1.00 (speed=60 mi / h) to 1.33 min (speed=45 mi / h)

1.33 (speed=45 mi / h) to 1.71 min (speed=35 mi / h)

1.71 (speed=35 mi / h) to 2.40 min (speed=25 mi / h) and

2.40 min (speed=25 mi / h)

TRAVEL TIME OF EACH LINK

Group(Min) a.m. Midday p.m. Night

Total Travel Time

0.70 and =

1.0095.7 121.3 91.4 123.5

1.00 and =

1.33348.4 444.1 298.8 608.7

1.33 and =

1.71304 273 285.3 228.1

1.71 and =

2.40195.6 150.2 226.8 68.7

2.4 109.4 64.5 151 24.1

Total1,053.2

0

1,053.2

0

1,053.2

0

1,053.2

0

Group(Min) a.m. Midday p.m. Night

Variation in travel time

= 0 4.3 4.1 3.21,053.2

0

5 and = 15 456.9 680.2 386.3 0

15 and = 25 260.9 237.2 210.9 0

25 and = 50 218.4 96.8 236.2 0

50 112.7 34.9 216.6 0

Total1,053.2

0

1,053.2

0

1,053.2

0

1,053.2

0

Crash data were used to compute the travel delay index

due to crashes per mile. A total of 18,782crashes (47

fatal crashes, 6,202 injury crashes) and remaining are

PDO crashes were reported during 2006 on the

considered 1,053.2 center-lane miles.

The number of crashes per mile per year is

approximately 17.8

The links in the road network were classified based on

the travel delay index due to crashes per mile during a

time period on a day into the following five groups:

◦ 0.000 no crashes

◦ 0.000 to 0.003 one crash during a day;

◦ 0.003 to 0.008 two or three crashes during a day

◦ 0.008 to 0.016 four to six crashes during day

◦ 0.016 more than six crashes during a day

TRAVEL DELAY INDEX DUE TO CRASH PER MILE

Group a.m. Midday p.m. Night

Travel delay index due to crashes per mile

0 571.5 480.6 499.1 487.3

0.000 and =

0.00342.7 52.7 53.4 42.4

0.003 and =

0.008139.6 133.3 145.4 148.7

0.008 and =

0.016131.5 116.6 117 140.7

0.016 168 270 238.2 234.1

Total 1,053.20 1,053.20 1,053.20 1,053.20

Group a.m. Midday p.m. Night

Congestion score

0 4.1 4.1 3.2 487.3

0 and = 5 370.5 561.9 309.5 548.8

5 and = 15 263.9 293.6 202.8 16.2

15 and = 25 174.5 106.3 172.5 0.9

25 240.2 87.2 365.2 0

Total 1,053.20 1,053.20 1,053.20 1,053.20

From the results obtained, it can be concluded that 75% of

total congestion during a.m. and p.m. peak periods is due

to traffic volume on roads.

On the other hand, crashes and their severity contribute as

much as traffic volume to travel delays during off-peak

periods. On an average, reliability of links is lowest during

p.m. peak period and highest during night hours.

CONCLUSION