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International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 948
STUDY OF AUTOMATED HIGHWAY SYSTEM
Shivam B. Gawande1, Prof. Y. S. Khandekar2, Prof. Ashish R. Bijwe3
1PG Scholar, Department of Civil Engineering, DRGIT&R, Amravati, Maharashtra, India.
2 Professor, Department of Civil Engineering, Sipna College of engineering and technology, Amravati,
Maharashtra, India
3Assistance Professor, Department of Civil Engineering, DRGIT&R, Amravati, Maharashtra, India
---------------------------------------------------------------------***----------------------------------------------------------------------
The problems associated with the annual growth of
automobile transport start spreading from large
metropolitan cities to small towns. [1] For many years,
scientists and engineers have envisioned building an
automated highway system (AHS) to increase both the
safety and efficiency of the nation's highways. In such a
system, the vehicles become driving robots, capable of
sensing and reacting to the surrounding environment
while the driver is free to do other tasks. Automating the
vehicle has significant potential it can reduce accidents
caused by driver error and can potentially increase traffic-
carrying capacity and fuel economy by eliminating human
driver inefficiencies. [2]
1.1 Need and Necessity
 Improvement safety by significantly reducing
fatalities, personal injuries, pain and suffering,
anxiety and stress of driving.
 Improvement in accessibility and mobility for
reducing delays, smooth flow of traffic, making
driving more accessible to less able to drivers.
 Ensuring exchange of road and route data as well
as other information between the respective
transport information centers and the traffic
control in different regions and different states.
 Taking measures required for automated highway
systems associated with safety into vehicles and
traffic infrastructure as well as ensuring the
elaboration of interaction as to safety in person-
machine terms.
 Development of alert systems for passengers and
road users, development of traffic demand control
systems in urban and rural region.
 Fuel consumption and polluting emissions might
be reduced by smoothing traffic flow and running
vehicles close enough to each other to benefit
from aerodynamic drafting.
1.2 Objectives
 Introduce new tools for managing urban
transport. Automated highway system will
develop tools that can help cities to cross the
thresholds that are preventing them from
introducing innovative systems.
 Studies will be carried out to show that an
automated transport system is not only feasible,
but will also contribute to a sustainable solution
for the city’s mobility problems, now and in the
future.
 To study the effect of Traffic volume, Capacity,
Road feature, Surface properties on accident rate
on highway road.
 To study the defects on highway and annual,
monthly accidents rates on the selected highway
road.
 To survey and document automated highway
system with driver and passenger safety systems
on roads.
 The reliable intelligent driver assistance systems
and safety warning systems is still a long way to
go.
 To study eliminate the more than ninety percent
of traffic crashes that are caused by human errors
such as misjudgments and in-attention.
Abstract - Automated highway system (AHS), which
promises an increase in traffic capacity. The core of this
protocol to achieve a fully automated highway system is
four-layer hierarchical control architecture. Automated
Highway System, abbreviated as AHS is newly developed
idea which uses different sensors and microprocessors for
automatic design process. The management and control of
traffic system using roadside controllers and intelligent
vehicles is innovative technique for the design of highway
system. The Automated Highway System is the design
concept introduced to enhance safety, efficiency and many
other vehicular as well as user characteristics of highways.
This concept has introduced for the improved architectural
layout of highway design and also helped in reducing the
environmental effects of the vehicles running on the
highways
Key Words: AHS Functional Evolution, Incremental
Deployment, Reducing Accident Rate, Smart Highway.
1. INTRODUCTION
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 949
2. Automated Highway System (AHS)
It is driverless technique which uses an automatic control
system for operation of vehicles. Different techniques
related with computing ideas, microelectronics, various
sensors and advanced civil engineering techniques are
used for design of an automated highway system. The
major components of any mechanically operated vehicles
i.e. throttle, steering and braking are automatically
operated in automated highway system. The major
requirement of any traffic facilities such as coordinated
movement of vehicles, removal of obstacles, improvised
traffic system and safety are easily provided by an
automated highway system.
The increment in capacity of vehicles running on the road
with fully controlled traffic system is basic concept used
for design of automated highway system. With comparison
to behavior of human drivers, the innovative concept of
automated highway system has played crucial role in
management of transportation network in developed
cities.
2.1 Component and function of automated
highway system
The component and function presents the evolution of
vehicle automation capabilities in terms of lateral motion
handling, longitudinal motion handling, and obstacle
handling.
2.1.1 Lateral Motion Handling
The lateral (side-to-side) motion of the vehicle has a
number of different functions, from vehicle-centric
maneuvers such as lane keeping to those involving
merging in heavy traffic. First, if the vehicle is to stay
within the lane, it needs to know where the lane
boundaries are lane detection is currently achieved
through a number of different technologies, including a
vision system, magnetic nails buried in the roadway which
are then sensed by the vehicle, or a radar-reflective stripe.
Fig -1: Sensor for lateral motion
Simple lane changing is the ability of the vehicle to
move smoothly out of one lane and into another in light
traffic conditions. The technical requirements for such a
system include side-looking sensors that detect a gap, and
the ability to cross between adjacent lanes and begin lane
keeping in the new lane. Such a system could be
considered “simple” if it changes lanes only in the absence
of nearby vehicles, thus being assured of no risk of
collision during the lane changing operation. Simple lane
changing requires elementary, side looking vehicle
detection
2.1.2 Longitudinal Motion Handling
The longitudinal (front-to-back) motion of the vehicle also
has a variety of functions which range from simplistic in-
vehicle handling to tactical driving within a congested
traffic scene. Speed keeping is the most elementary
function within this category, involving the maintenance of
a constant travel speed. It is widely deployed in the form
of “cruise control.” Headway keeping, also known as
adaptive cruise control is a function which adapts the
speed of the vehicle to match that of a lead vehicle while
maintaining a safe distance. Headway keeping is currently
being deployed on a limited scale in foreign markets.
Headway keeping, like all of the advanced functions in this
category, depends upon reliable vehicle detection &
vehicle motion detection. This is the ability to ascertain
fundamental information about surrounding vehicles and
their behavior. This capability will likely evolve from
simple look-ahead functions to include look-behind and
look-to-the-side as well. The term “look” is used loosely in
this context, and refers to an ability to obtain information
about surrounding areas in a particular direction. It does
not mean to imply that vision-based systems must
necessarily be used; indeed radar, ladder, and sonar
systems may prove far more useful than vision systems,
especially in reduced visibility situations such as rain and
fog. Given the ability to detect vehicle and vehicle motion,
longitudinal collision warning becomes possible.
Fig -2: Sensor for longitudinal motion
2.1.3 Obstacle Handling
Obstacle avoidance capabilities reduce or eliminate safety
hazards caused by obstacles on the automated highway
system. This includes rocks, vegetation, dropped vehicle
parts, disabled vehicles and animals. Obstacle detection
and threat determination is a much more difficult task
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 950
than vehicle detection due to the technical difficulties of
sensing obstacles and identifying whether those obstacles
present a threat. For determine the obstacle radar and
sonar systems may be used. One way to reduce the need
for obstacle avoidance is to implement obstacle exclusion.
To a limited degree this is already deployed with fencing
and highway department maintenance of the interstate
highway system. Obstacle exclusion can significantly
reduce the frequency of obstacles on the roadway, but it
seems implausible that any exclusion method can be
effective.
Fig -3: Sensor for obstacle motion
Obstacle motion detection & prediction may be a
particularly difficult capability to develop. Unlike vehicles,
which are physically constrained in realizable maneuvers,
obstacles may not behave in readily predictable ways.
Animals may run into the road and stop abruptly. Loose
tires can bounce randomly, depending on road surface,
tire wear, and angle of incidence. That obstacle motion
prediction can be achieved; the vehicle can achieve
avoidance via lane change. This becomes a unique
capability that depends heavily on good prediction, not
only of the motion of the obstacle, but also of how other
vehicles will react to that obstacle.
2.2 ETC (Electronic Toll Collection)
The Electronic Toll Collection (ETC) System is a new toll
system designed to enhance convenience for drivers by
enabling cashless toll collection and thus reducing
congestion at High-way tollgates.
ETC toll collection is a technology enabling the electronic
collection of toll payment. It has been studied by
researchers and applied in various highways, bridges, and
tunnel requiring such a process. This system can
determine if the car is registered or not, and then
informing the authorities of toll payment violation, debits
and participating accounts. The most advantage of this
technology is the opportunity to eliminate congestion in
toll booths, especially during festive seasons when traffic
trends to be heavier than normal. Other general
advantages for the motorists include fuel savings and
reduced mobile emissions by reducing or eliminating
deceleration, waiting time, and acceleration.
Fig -4: ETC mechanism
3.0 Methodology and Data
3.1 Information of study area Amravati to
Talegaon National Highway.
The Amravati to Talegaon is India's national highway
number 6 (NH 6 has been renumbered NH 53 after
renumbering of all national highways by National Highway
Authority of India in 2010 year.) high-speed, access
controlled tolled highway. It spans a distance of 55.1 km
connecting Amravati to Talegaon.
The highway is part of major East - West national highway
NH-6 commonly referred to as NH-6 or the G.E. Road
(Great Eastern Road). NH-6 is a busy National Highway
that runs through Gujarat, Maharashtra, Chhattisgarh,
Orissa, Jharkhand and West Bengal state in India. The
highway passes through the cities of Surat, Dhule,
Amravati, Nagpur, Raipur, Sambalpur & Kolkata. NH 6
runs over 1,949 km from Hazira to Kolkata forming
important east-west connectivity across region.
This study section of NH-6 caters to various types of traffic
such as urban, suburban and regional traffic. The
development alongside the highway indicates mixed land
use on both sides of the highway consisting of agricultural
and barren lands, residential, commercial, small &
medium scale industrial establishments such as textiles,
woolen blankets, ropes, watches etc. The corridor in
general has significant potential for future development
along the highway and in the influence area, discussed
further in this Report. Dominant land use of both side of
project corridor is rural agriculture land. Since this stretch
is part of Great Eastern Highway which connect two major
ports of country namely Kolkata and Hazira, it carries
good amount of commercial bulk transportation traffic.
Fig -5: Satellite view study area
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 951
The project highway corridor is in the state of
Maharashtra and passes through Amravati district. En-
route, it passes few major/minor urban centers, viz.
Nandgaon Peth, Mozri, Tivsa, and Ramdara etc. along its
length before reaching end of project stretch at Talegaon.
Corridor is also known as Amravati – Nagpur Highway.
The highway has two carriageways each with two lanes,
having a central divider, paved shoulders; side drains on
both side and flyovers at major intersections.
The silent features of the study area are as given below;
Four Laning of Carriageway = 55.1 Km.
Major Bridges = 1 No.
Minor Bridges = 25 Nos.
Flyovers = 2 Nos.
Railway Over Bridge= 1 No.
Culverts = 86 Nos.
Pedestrian Under passes = 11 Nos.
Vehicular Under passes = 11 Nos.
Major intersection = 36 Nos.
Service Road = 26.50 Km.
Bus Bays = 15 Nos.
Toll Plaza Complex = 1 Nos.
3.2 Classified Traffic Volume Count
The objective of conducting a Classified Traffic Volume
Count is to understand the traffic flow pattern including
modal split on a roadway. The Classified Traffic Volume
Count survey has been provided by concessionaire of
project highway from actual traffic data gathered at toll
plaza locations based on monthly data. The vehicles can
broadly be classified into fast moving / motorized and
slow moving / non-motorized vehicles, which can be
further classified into specific categories of vehicles. The
groupings of vehicles are further segregated to capture the
toll able vehicle categories specifically and toll exempted
vehicles are counted separately. The detailed vehicle
classification system as per IRC: 64-1990 is given in Table
Table -1: Vehicle Classification System
Vehicle Type
Auto Rickshaw
Passenger Car
Car, Jeep, Taxi & Van (Old / new
technology)
Bus
Mini Bus
Standard Bus
Truck
Light Goods Vehicle (LCV)
2 – Axle Truck
3 Axle Truck (HCV)
Multi Axle Truck (4-6 Axle)
Oversized Vehicles (7 or more axles)
Other Vehicles Agriculture Tractor, Tractor & Trailer
3.3 Traffic Characteristics
Toll revenue of the highway does not solely depend on
traffic volume. There are certain characteristics of traffic
which have significant potential to affect toll revenue.
Component of local traffic, component of passenger and
commercial traffic, portion of return journey traffic,
portion of monthly pass traffic are some such
characteristics of traffic.
Fig -5: Toll Plaza Location as TP1
3.4 Traffic Data
The highway is currently under toll operation, the data
collected is corresponding to category of toll able vehicles.
Table -2: Traffic Data
Sr.
no.
Type of
Vehicle
Annual
Average
Daily
Traffic
For 2015-
16
Annual
Average
Daily
Traffic
For 2016-
17
Annual
Average
Daily
Traffic
For 2017-
18
1 Car 5105 5770 5918
2
Mini Bus /
LCV
1253 1333 1421
3 Truck / Bus 1238 1244 1426
4 Multi Axel 1742 1808 2031
5
Oversized
Vehicles
2 1 2
Total 9337 10156 10798
3.5 Analysis of traffic count
Understanding the character of existing traffic forms the
basis of traffic forecast. The various vehicle types having
different sizes and characteristics can be converted into a
single unit called Passenger Car Unit (PCU). Passenger Car
equivalents for various vehicles are adopted based on
recommendations of Indian Road Congress prescribed in
“IRC-64-1990: Guidelines for Capacity of Roads in Rural
areas”. The adopted passenger car unit values (PCU) are
presented in following table.
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 952
Table -3: PCU Factor Adopting For Study
Vehicle type PCUs
Car/Van 1.0
Mini Bus 1.5
Standard Bus 3.0
LCV 1.5
2-Axel Truck 3.0
3-6 Axel Truck 4.5
Multi Axel Vehicle 4.5
Auto Rickshaw 1.0
Agriculture Tractor with Trailer 4.5
Agriculture Tractor without Trailer 1.5
Table -4: Traffic in PCU
Period
Traffic
No
PCU PCU
Index
For year
2015-16
9337 18543.5 1.99
For year
2016-17
10156 19642 1.93
For year
2017-18
10798 21476 1.99
It can be observed from above that project traffic has PCU
index close to 2.0 which indicates good mix of commercial,
goods traffic and passenger traffic.
3.6 Analysis of accident data
Road transport is essential for development as it provides
mobility to people and goods. However, it also exposes
people to the risk of road accidents, injuries and fatalities.
Exposure to adverse traffic environment is high in India
because of the unprecedented rate of motorization and
growing urbanization fueled by high rate of economic
growth. As a result, incidents of road accidents, traffic
injuries and fatalities have remained unacceptably high in
the India.
Previous year data of accidents on study highway as
following
Accident Data for the Month of April-2015 to April-2018
Table -5: Accident Data Amravati to Talegaon
Sr.
No.
Year
Fata
l
Grievou
s
Mino
r
Tota
l
1
Apr-2015 to Dec-
2015
7 39 47
93
2
Jan-2016 to Dec-
2016
20 34 52
106
3
Jan-2017 to Dec-
2017
17 22 25
64
4
Jan-2018 to Apr -
2018
4 11 20
35
Total 48 106 144 298
Chart -1: Accident data of April 2015- April2018
Accident Data of Dead Animals
Table -6: Accident Data of Animals Amravati to Talegaon
Animals
Mo
nth
s
Cat
Go
at
Dog
P
i
g
C
o
w
O
x
Don
key
B
uf
fa
lo
Tot
al
1
Jun-
15
2 1 58 0 0 0 3 1 65
2
Jan-
17
1 0 17 2 1 2 0 0 23
3
Mar
-18
9 1 34 4 2 1 1 0 52
4
Apr
-18
12 0 32 3 0 3 2 0 52
Tot
al
24 2 141 9 3 6 6 1 192
Chart -2: Accident data of Animals
3.7 Case Study of Japan Automated Highway
Japan, with a population density almost 12 times greater
than the United States, has an abiding interest in
developing intelligent transportation systems (ITS) to
resolve its traffic congestion and other transportation
problems. Indeed, the Japanese Comprehensive
Automobile Traffic Control System (CACS) program.
But recently, Japanese officials have started looking at ITS
from a much greater perspective. ITS is an essential
element in creating a global advanced information and
telecommunications society. This advanced society will
0
20
40
60
2015 2016 2017 2018
Fatal
Grievous
Minor
0
10
20
30
40
50
60
70
Jun-15
Jan-17
Mar-18
Apr-18
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 953
realize the free generation, circulation, and sharing of
information and knowledge that are the products of all
human intellectually creative activities, thus leading to a
new socioeconomic system that can forge a balance
between living/culture, industry/business, and
nature/environment. As a result, it is expected that there
will be an expansion of economic frontiers, balanced
national land development, and the creation of a standard
of living for the people such that they can realize a truly
comfortable and affluent lifestyle.
Accident rate before & After Automation in Japan in a year
Table -7: Accident Data of Japan before Automation
Sr. No. Vehicle Type Accident
1 Bus 545
2 Heavy / Truck 85
3 Passenger Vehicle 654
4 Two Wheeler 850
5 Car 541
6 Other 658
Table -8: Accident Data of Japan after
Sr. No. Vehicle Type Accident
1 Bus 246
2 Heavy / Truck 32
3 Passenger Vehicle 342
4 Two Wheeler 352
5 Car 152
6 Other 354
From the table 7 & 8 the use of ITS automation System the
accident rate are nearly 50% reduces.
Chart -3: Before and After Automation of highway
Accident
4.0 Result
4.1 Accident rate
On this basis the total accident hazard is expressed as the
number of accidents of all types per km of each highway
and street classification.
R=A/L
Where,
R = total accident rate per km for one year,
A = total number of accident occurring in one year,
L = length of control section in km.
Accident rate April 2015 to April 2018 including all
accidents (Fatal, Grievous, Minor)
Table -9: Total Accident Rate Amravati to Talegaon
Years
Length
(km)
Total No. of
accident
Accident
rate per km
Apr-2015 to Dec-
2015
55 93 1.70
Jan-2016 to Dec-
2016
55 106 1.93
Jan-2017 to Dec-
2017
55 64 1.16
Jan-2018 to Apr-
2018
55 35 0.64
Chart -4: Total Accident Rate per km
Accident rate April 2015 to April 2018 for Fatal
Table -10: Accident Rate of Fatal Amravati to Talegaon
Years
Length
(km)
No. of
accident
Accident
rate per
km
%Accident
rate per
km
Apr-2015 to
Dec-2015
55 7 0.13 13%
Jan-2016 to
Dec-2016
55 20 0.36 36%
Jan-2017 to
Dec-2017
55 17 0.31 31%
Jan-2018 to
Apr-2018
55 4 0.07 7%
0
200
400
600
800
1000
0
0.5
1
1.5
2
2.5
Accident rate
per km
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 954
Chart -5: Percentage of accident rate of fatal
4.2 Accident rate for animal
On this basis the total accident hazard is expressed as the
number of accidents of all types per km of each highway
and street classification.
R=A/L
Where,
R = total accident rate per km for one year,
A = total number of accident occurring in one year,
L = length of control section in km.
Table -11: Accident Rate of Animals Amravati to Talegaon
Months
Length
(km)
No. of
accident
Accident
rate per km
Jun-15 55 65 1.81
Jan-17 55 23 0.42
Mar-18 55 52 0.95
Apr-18 55 52 0.95
Chart -6: Accident Rate of Animals
5. CONCLUSION
In this paper, we study Traffic volume, Capacity, Road
feature, Surface properties on accident rate on highway
road. The defects on highway and annual, monthly
accidents rates on the selected highway road. Survey and
document automated highway system with driver and
passenger safety systems on roads. The reliable intelligent
driver assistance systems and safety warning systems is
still a long way to go. We study eliminate the more than
ninety percent of traffic crashes that are caused by human
errors such as misjudgments and in-attention. Studies will
be carried out to show that an automated transport
system is not only feasible, but will also contribute to a
sustainable solution for the city’s mobility problems, now
and in the future.
REFERENCES
[1]Alexander Novikov & Pavel Pribyl, “ITS Control of
Highways Capacity” 12th International Conference
"Organization and Traffic Safety Management in large
cities", SPbOTSIC-2016, 28-30 September 2016, St.
Petersburg, Russia.
[2]Sangeeta Mishra, Ajinkya Bavane, “Automated Highway
System (Pune to Mumbai) In India” International Journal
of Innovative Research in Science, Engineering and
Technology. Vol. 7, Issue 5, May 2018
[3]Nayan R. Wasekar , Asst. Prof. Feroz H. Khan,
“Automated Highway System” International Journal of
Advance Engineering and Research Development (IJAERD)
Volume 4, Issue 1, January -2017, e-ISSN: 2348 - 4470,
print-ISSN: 2348-6406
[4] Sanju Meena & Dr. Om Prakash, “The Study on
Automated Highway Systems” Imperial Journal of
Interdisciplinary Research (IJIR) Vol-3, Issue-4, and 2017
ISSN: 2454-1362.
[5] Petros A. Ioannou, “Automated Highway Systems”
Includes bibliographical references and index. ISBN 978-1-
4419-3264-8 ISBN 978-1-4757-4573-3 (eBook) DOI
10.1007/978-1-4757-4573-3
[6] “IRB OFFER DOCUMENT” Dated April 20, 2017 Book
Built Issue.
0%
5%
10%
15%
20%
25%
30%
35%
40%
%Accident rate
per km
0
0.5
1
1.5
2
Accident rate per km
Jun-15
Jan-17
Mar-18
Apr-18

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IRJET- Study of Automated Highway System

  • 1. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 948 STUDY OF AUTOMATED HIGHWAY SYSTEM Shivam B. Gawande1, Prof. Y. S. Khandekar2, Prof. Ashish R. Bijwe3 1PG Scholar, Department of Civil Engineering, DRGIT&R, Amravati, Maharashtra, India. 2 Professor, Department of Civil Engineering, Sipna College of engineering and technology, Amravati, Maharashtra, India 3Assistance Professor, Department of Civil Engineering, DRGIT&R, Amravati, Maharashtra, India ---------------------------------------------------------------------***---------------------------------------------------------------------- The problems associated with the annual growth of automobile transport start spreading from large metropolitan cities to small towns. [1] For many years, scientists and engineers have envisioned building an automated highway system (AHS) to increase both the safety and efficiency of the nation's highways. In such a system, the vehicles become driving robots, capable of sensing and reacting to the surrounding environment while the driver is free to do other tasks. Automating the vehicle has significant potential it can reduce accidents caused by driver error and can potentially increase traffic- carrying capacity and fuel economy by eliminating human driver inefficiencies. [2] 1.1 Need and Necessity  Improvement safety by significantly reducing fatalities, personal injuries, pain and suffering, anxiety and stress of driving.  Improvement in accessibility and mobility for reducing delays, smooth flow of traffic, making driving more accessible to less able to drivers.  Ensuring exchange of road and route data as well as other information between the respective transport information centers and the traffic control in different regions and different states.  Taking measures required for automated highway systems associated with safety into vehicles and traffic infrastructure as well as ensuring the elaboration of interaction as to safety in person- machine terms.  Development of alert systems for passengers and road users, development of traffic demand control systems in urban and rural region.  Fuel consumption and polluting emissions might be reduced by smoothing traffic flow and running vehicles close enough to each other to benefit from aerodynamic drafting. 1.2 Objectives  Introduce new tools for managing urban transport. Automated highway system will develop tools that can help cities to cross the thresholds that are preventing them from introducing innovative systems.  Studies will be carried out to show that an automated transport system is not only feasible, but will also contribute to a sustainable solution for the city’s mobility problems, now and in the future.  To study the effect of Traffic volume, Capacity, Road feature, Surface properties on accident rate on highway road.  To study the defects on highway and annual, monthly accidents rates on the selected highway road.  To survey and document automated highway system with driver and passenger safety systems on roads.  The reliable intelligent driver assistance systems and safety warning systems is still a long way to go.  To study eliminate the more than ninety percent of traffic crashes that are caused by human errors such as misjudgments and in-attention. Abstract - Automated highway system (AHS), which promises an increase in traffic capacity. The core of this protocol to achieve a fully automated highway system is four-layer hierarchical control architecture. Automated Highway System, abbreviated as AHS is newly developed idea which uses different sensors and microprocessors for automatic design process. The management and control of traffic system using roadside controllers and intelligent vehicles is innovative technique for the design of highway system. The Automated Highway System is the design concept introduced to enhance safety, efficiency and many other vehicular as well as user characteristics of highways. This concept has introduced for the improved architectural layout of highway design and also helped in reducing the environmental effects of the vehicles running on the highways Key Words: AHS Functional Evolution, Incremental Deployment, Reducing Accident Rate, Smart Highway. 1. INTRODUCTION
  • 2. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 949 2. Automated Highway System (AHS) It is driverless technique which uses an automatic control system for operation of vehicles. Different techniques related with computing ideas, microelectronics, various sensors and advanced civil engineering techniques are used for design of an automated highway system. The major components of any mechanically operated vehicles i.e. throttle, steering and braking are automatically operated in automated highway system. The major requirement of any traffic facilities such as coordinated movement of vehicles, removal of obstacles, improvised traffic system and safety are easily provided by an automated highway system. The increment in capacity of vehicles running on the road with fully controlled traffic system is basic concept used for design of automated highway system. With comparison to behavior of human drivers, the innovative concept of automated highway system has played crucial role in management of transportation network in developed cities. 2.1 Component and function of automated highway system The component and function presents the evolution of vehicle automation capabilities in terms of lateral motion handling, longitudinal motion handling, and obstacle handling. 2.1.1 Lateral Motion Handling The lateral (side-to-side) motion of the vehicle has a number of different functions, from vehicle-centric maneuvers such as lane keeping to those involving merging in heavy traffic. First, if the vehicle is to stay within the lane, it needs to know where the lane boundaries are lane detection is currently achieved through a number of different technologies, including a vision system, magnetic nails buried in the roadway which are then sensed by the vehicle, or a radar-reflective stripe. Fig -1: Sensor for lateral motion Simple lane changing is the ability of the vehicle to move smoothly out of one lane and into another in light traffic conditions. The technical requirements for such a system include side-looking sensors that detect a gap, and the ability to cross between adjacent lanes and begin lane keeping in the new lane. Such a system could be considered “simple” if it changes lanes only in the absence of nearby vehicles, thus being assured of no risk of collision during the lane changing operation. Simple lane changing requires elementary, side looking vehicle detection 2.1.2 Longitudinal Motion Handling The longitudinal (front-to-back) motion of the vehicle also has a variety of functions which range from simplistic in- vehicle handling to tactical driving within a congested traffic scene. Speed keeping is the most elementary function within this category, involving the maintenance of a constant travel speed. It is widely deployed in the form of “cruise control.” Headway keeping, also known as adaptive cruise control is a function which adapts the speed of the vehicle to match that of a lead vehicle while maintaining a safe distance. Headway keeping is currently being deployed on a limited scale in foreign markets. Headway keeping, like all of the advanced functions in this category, depends upon reliable vehicle detection & vehicle motion detection. This is the ability to ascertain fundamental information about surrounding vehicles and their behavior. This capability will likely evolve from simple look-ahead functions to include look-behind and look-to-the-side as well. The term “look” is used loosely in this context, and refers to an ability to obtain information about surrounding areas in a particular direction. It does not mean to imply that vision-based systems must necessarily be used; indeed radar, ladder, and sonar systems may prove far more useful than vision systems, especially in reduced visibility situations such as rain and fog. Given the ability to detect vehicle and vehicle motion, longitudinal collision warning becomes possible. Fig -2: Sensor for longitudinal motion 2.1.3 Obstacle Handling Obstacle avoidance capabilities reduce or eliminate safety hazards caused by obstacles on the automated highway system. This includes rocks, vegetation, dropped vehicle parts, disabled vehicles and animals. Obstacle detection and threat determination is a much more difficult task
  • 3. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 950 than vehicle detection due to the technical difficulties of sensing obstacles and identifying whether those obstacles present a threat. For determine the obstacle radar and sonar systems may be used. One way to reduce the need for obstacle avoidance is to implement obstacle exclusion. To a limited degree this is already deployed with fencing and highway department maintenance of the interstate highway system. Obstacle exclusion can significantly reduce the frequency of obstacles on the roadway, but it seems implausible that any exclusion method can be effective. Fig -3: Sensor for obstacle motion Obstacle motion detection & prediction may be a particularly difficult capability to develop. Unlike vehicles, which are physically constrained in realizable maneuvers, obstacles may not behave in readily predictable ways. Animals may run into the road and stop abruptly. Loose tires can bounce randomly, depending on road surface, tire wear, and angle of incidence. That obstacle motion prediction can be achieved; the vehicle can achieve avoidance via lane change. This becomes a unique capability that depends heavily on good prediction, not only of the motion of the obstacle, but also of how other vehicles will react to that obstacle. 2.2 ETC (Electronic Toll Collection) The Electronic Toll Collection (ETC) System is a new toll system designed to enhance convenience for drivers by enabling cashless toll collection and thus reducing congestion at High-way tollgates. ETC toll collection is a technology enabling the electronic collection of toll payment. It has been studied by researchers and applied in various highways, bridges, and tunnel requiring such a process. This system can determine if the car is registered or not, and then informing the authorities of toll payment violation, debits and participating accounts. The most advantage of this technology is the opportunity to eliminate congestion in toll booths, especially during festive seasons when traffic trends to be heavier than normal. Other general advantages for the motorists include fuel savings and reduced mobile emissions by reducing or eliminating deceleration, waiting time, and acceleration. Fig -4: ETC mechanism 3.0 Methodology and Data 3.1 Information of study area Amravati to Talegaon National Highway. The Amravati to Talegaon is India's national highway number 6 (NH 6 has been renumbered NH 53 after renumbering of all national highways by National Highway Authority of India in 2010 year.) high-speed, access controlled tolled highway. It spans a distance of 55.1 km connecting Amravati to Talegaon. The highway is part of major East - West national highway NH-6 commonly referred to as NH-6 or the G.E. Road (Great Eastern Road). NH-6 is a busy National Highway that runs through Gujarat, Maharashtra, Chhattisgarh, Orissa, Jharkhand and West Bengal state in India. The highway passes through the cities of Surat, Dhule, Amravati, Nagpur, Raipur, Sambalpur & Kolkata. NH 6 runs over 1,949 km from Hazira to Kolkata forming important east-west connectivity across region. This study section of NH-6 caters to various types of traffic such as urban, suburban and regional traffic. The development alongside the highway indicates mixed land use on both sides of the highway consisting of agricultural and barren lands, residential, commercial, small & medium scale industrial establishments such as textiles, woolen blankets, ropes, watches etc. The corridor in general has significant potential for future development along the highway and in the influence area, discussed further in this Report. Dominant land use of both side of project corridor is rural agriculture land. Since this stretch is part of Great Eastern Highway which connect two major ports of country namely Kolkata and Hazira, it carries good amount of commercial bulk transportation traffic. Fig -5: Satellite view study area
  • 4. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 951 The project highway corridor is in the state of Maharashtra and passes through Amravati district. En- route, it passes few major/minor urban centers, viz. Nandgaon Peth, Mozri, Tivsa, and Ramdara etc. along its length before reaching end of project stretch at Talegaon. Corridor is also known as Amravati – Nagpur Highway. The highway has two carriageways each with two lanes, having a central divider, paved shoulders; side drains on both side and flyovers at major intersections. The silent features of the study area are as given below; Four Laning of Carriageway = 55.1 Km. Major Bridges = 1 No. Minor Bridges = 25 Nos. Flyovers = 2 Nos. Railway Over Bridge= 1 No. Culverts = 86 Nos. Pedestrian Under passes = 11 Nos. Vehicular Under passes = 11 Nos. Major intersection = 36 Nos. Service Road = 26.50 Km. Bus Bays = 15 Nos. Toll Plaza Complex = 1 Nos. 3.2 Classified Traffic Volume Count The objective of conducting a Classified Traffic Volume Count is to understand the traffic flow pattern including modal split on a roadway. The Classified Traffic Volume Count survey has been provided by concessionaire of project highway from actual traffic data gathered at toll plaza locations based on monthly data. The vehicles can broadly be classified into fast moving / motorized and slow moving / non-motorized vehicles, which can be further classified into specific categories of vehicles. The groupings of vehicles are further segregated to capture the toll able vehicle categories specifically and toll exempted vehicles are counted separately. The detailed vehicle classification system as per IRC: 64-1990 is given in Table Table -1: Vehicle Classification System Vehicle Type Auto Rickshaw Passenger Car Car, Jeep, Taxi & Van (Old / new technology) Bus Mini Bus Standard Bus Truck Light Goods Vehicle (LCV) 2 – Axle Truck 3 Axle Truck (HCV) Multi Axle Truck (4-6 Axle) Oversized Vehicles (7 or more axles) Other Vehicles Agriculture Tractor, Tractor & Trailer 3.3 Traffic Characteristics Toll revenue of the highway does not solely depend on traffic volume. There are certain characteristics of traffic which have significant potential to affect toll revenue. Component of local traffic, component of passenger and commercial traffic, portion of return journey traffic, portion of monthly pass traffic are some such characteristics of traffic. Fig -5: Toll Plaza Location as TP1 3.4 Traffic Data The highway is currently under toll operation, the data collected is corresponding to category of toll able vehicles. Table -2: Traffic Data Sr. no. Type of Vehicle Annual Average Daily Traffic For 2015- 16 Annual Average Daily Traffic For 2016- 17 Annual Average Daily Traffic For 2017- 18 1 Car 5105 5770 5918 2 Mini Bus / LCV 1253 1333 1421 3 Truck / Bus 1238 1244 1426 4 Multi Axel 1742 1808 2031 5 Oversized Vehicles 2 1 2 Total 9337 10156 10798 3.5 Analysis of traffic count Understanding the character of existing traffic forms the basis of traffic forecast. The various vehicle types having different sizes and characteristics can be converted into a single unit called Passenger Car Unit (PCU). Passenger Car equivalents for various vehicles are adopted based on recommendations of Indian Road Congress prescribed in “IRC-64-1990: Guidelines for Capacity of Roads in Rural areas”. The adopted passenger car unit values (PCU) are presented in following table.
  • 5. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 952 Table -3: PCU Factor Adopting For Study Vehicle type PCUs Car/Van 1.0 Mini Bus 1.5 Standard Bus 3.0 LCV 1.5 2-Axel Truck 3.0 3-6 Axel Truck 4.5 Multi Axel Vehicle 4.5 Auto Rickshaw 1.0 Agriculture Tractor with Trailer 4.5 Agriculture Tractor without Trailer 1.5 Table -4: Traffic in PCU Period Traffic No PCU PCU Index For year 2015-16 9337 18543.5 1.99 For year 2016-17 10156 19642 1.93 For year 2017-18 10798 21476 1.99 It can be observed from above that project traffic has PCU index close to 2.0 which indicates good mix of commercial, goods traffic and passenger traffic. 3.6 Analysis of accident data Road transport is essential for development as it provides mobility to people and goods. However, it also exposes people to the risk of road accidents, injuries and fatalities. Exposure to adverse traffic environment is high in India because of the unprecedented rate of motorization and growing urbanization fueled by high rate of economic growth. As a result, incidents of road accidents, traffic injuries and fatalities have remained unacceptably high in the India. Previous year data of accidents on study highway as following Accident Data for the Month of April-2015 to April-2018 Table -5: Accident Data Amravati to Talegaon Sr. No. Year Fata l Grievou s Mino r Tota l 1 Apr-2015 to Dec- 2015 7 39 47 93 2 Jan-2016 to Dec- 2016 20 34 52 106 3 Jan-2017 to Dec- 2017 17 22 25 64 4 Jan-2018 to Apr - 2018 4 11 20 35 Total 48 106 144 298 Chart -1: Accident data of April 2015- April2018 Accident Data of Dead Animals Table -6: Accident Data of Animals Amravati to Talegaon Animals Mo nth s Cat Go at Dog P i g C o w O x Don key B uf fa lo Tot al 1 Jun- 15 2 1 58 0 0 0 3 1 65 2 Jan- 17 1 0 17 2 1 2 0 0 23 3 Mar -18 9 1 34 4 2 1 1 0 52 4 Apr -18 12 0 32 3 0 3 2 0 52 Tot al 24 2 141 9 3 6 6 1 192 Chart -2: Accident data of Animals 3.7 Case Study of Japan Automated Highway Japan, with a population density almost 12 times greater than the United States, has an abiding interest in developing intelligent transportation systems (ITS) to resolve its traffic congestion and other transportation problems. Indeed, the Japanese Comprehensive Automobile Traffic Control System (CACS) program. But recently, Japanese officials have started looking at ITS from a much greater perspective. ITS is an essential element in creating a global advanced information and telecommunications society. This advanced society will 0 20 40 60 2015 2016 2017 2018 Fatal Grievous Minor 0 10 20 30 40 50 60 70 Jun-15 Jan-17 Mar-18 Apr-18
  • 6. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 953 realize the free generation, circulation, and sharing of information and knowledge that are the products of all human intellectually creative activities, thus leading to a new socioeconomic system that can forge a balance between living/culture, industry/business, and nature/environment. As a result, it is expected that there will be an expansion of economic frontiers, balanced national land development, and the creation of a standard of living for the people such that they can realize a truly comfortable and affluent lifestyle. Accident rate before & After Automation in Japan in a year Table -7: Accident Data of Japan before Automation Sr. No. Vehicle Type Accident 1 Bus 545 2 Heavy / Truck 85 3 Passenger Vehicle 654 4 Two Wheeler 850 5 Car 541 6 Other 658 Table -8: Accident Data of Japan after Sr. No. Vehicle Type Accident 1 Bus 246 2 Heavy / Truck 32 3 Passenger Vehicle 342 4 Two Wheeler 352 5 Car 152 6 Other 354 From the table 7 & 8 the use of ITS automation System the accident rate are nearly 50% reduces. Chart -3: Before and After Automation of highway Accident 4.0 Result 4.1 Accident rate On this basis the total accident hazard is expressed as the number of accidents of all types per km of each highway and street classification. R=A/L Where, R = total accident rate per km for one year, A = total number of accident occurring in one year, L = length of control section in km. Accident rate April 2015 to April 2018 including all accidents (Fatal, Grievous, Minor) Table -9: Total Accident Rate Amravati to Talegaon Years Length (km) Total No. of accident Accident rate per km Apr-2015 to Dec- 2015 55 93 1.70 Jan-2016 to Dec- 2016 55 106 1.93 Jan-2017 to Dec- 2017 55 64 1.16 Jan-2018 to Apr- 2018 55 35 0.64 Chart -4: Total Accident Rate per km Accident rate April 2015 to April 2018 for Fatal Table -10: Accident Rate of Fatal Amravati to Talegaon Years Length (km) No. of accident Accident rate per km %Accident rate per km Apr-2015 to Dec-2015 55 7 0.13 13% Jan-2016 to Dec-2016 55 20 0.36 36% Jan-2017 to Dec-2017 55 17 0.31 31% Jan-2018 to Apr-2018 55 4 0.07 7% 0 200 400 600 800 1000 0 0.5 1 1.5 2 2.5 Accident rate per km
  • 7. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 954 Chart -5: Percentage of accident rate of fatal 4.2 Accident rate for animal On this basis the total accident hazard is expressed as the number of accidents of all types per km of each highway and street classification. R=A/L Where, R = total accident rate per km for one year, A = total number of accident occurring in one year, L = length of control section in km. Table -11: Accident Rate of Animals Amravati to Talegaon Months Length (km) No. of accident Accident rate per km Jun-15 55 65 1.81 Jan-17 55 23 0.42 Mar-18 55 52 0.95 Apr-18 55 52 0.95 Chart -6: Accident Rate of Animals 5. CONCLUSION In this paper, we study Traffic volume, Capacity, Road feature, Surface properties on accident rate on highway road. The defects on highway and annual, monthly accidents rates on the selected highway road. Survey and document automated highway system with driver and passenger safety systems on roads. The reliable intelligent driver assistance systems and safety warning systems is still a long way to go. We study eliminate the more than ninety percent of traffic crashes that are caused by human errors such as misjudgments and in-attention. Studies will be carried out to show that an automated transport system is not only feasible, but will also contribute to a sustainable solution for the city’s mobility problems, now and in the future. REFERENCES [1]Alexander Novikov & Pavel Pribyl, “ITS Control of Highways Capacity” 12th International Conference "Organization and Traffic Safety Management in large cities", SPbOTSIC-2016, 28-30 September 2016, St. Petersburg, Russia. [2]Sangeeta Mishra, Ajinkya Bavane, “Automated Highway System (Pune to Mumbai) In India” International Journal of Innovative Research in Science, Engineering and Technology. Vol. 7, Issue 5, May 2018 [3]Nayan R. Wasekar , Asst. Prof. Feroz H. Khan, “Automated Highway System” International Journal of Advance Engineering and Research Development (IJAERD) Volume 4, Issue 1, January -2017, e-ISSN: 2348 - 4470, print-ISSN: 2348-6406 [4] Sanju Meena & Dr. Om Prakash, “The Study on Automated Highway Systems” Imperial Journal of Interdisciplinary Research (IJIR) Vol-3, Issue-4, and 2017 ISSN: 2454-1362. [5] Petros A. Ioannou, “Automated Highway Systems” Includes bibliographical references and index. ISBN 978-1- 4419-3264-8 ISBN 978-1-4757-4573-3 (eBook) DOI 10.1007/978-1-4757-4573-3 [6] “IRB OFFER DOCUMENT” Dated April 20, 2017 Book Built Issue. 0% 5% 10% 15% 20% 25% 30% 35% 40% %Accident rate per km 0 0.5 1 1.5 2 Accident rate per km Jun-15 Jan-17 Mar-18 Apr-18