TRAFFIC SIGNAL OPTIMIZATION.docx

TRAFFIC SIGNALOPTIMIZATION A project report submitted in partial fulfilment of the requirements for the award of the degree of

BACHELOR OF TECHNOLOGY IN CIVIL ENGINEERING Submitted by

K.MOUNIKA REDDY (1210212241) D.SAI GOWTHAM(1210212219) B.NAVEEN(1210212211) K.KOTISIVA REDDY(1210212234) G.SATHVIK(1210212257) Under the esteemed guidance of DR.DANGETI MUKUND RAO(Associate Professor) Civil Department, GITAM UNIVERSITY

Department of Civil Engineering GITAM Institute of Technology, GITAM University Visakhapatnam – 530045 Batch:2012-2016

DEPARTMENT OF CIVIL ENGINEERING GITAM INSTITUTE OF TECHNOLOGY GITAM UNIVERSITY

CERTIFICATE This is to certify that the project report entitled TRAFFIC SIGNALOPTIMIZATION IN VISAKHAPATNAM REGION, a work done by K.Mounika (1210212241), D.SaiGowtham (1210212219), B.Naveen (1210212211), K.KotiSiva Reddy (1210212234) and G.Sathvik (1210212257) students of 4/4 B.TECH CIVIL ENGINEERING is carried out at GITAM UNIVERSITY,VISAKHAPATNAM in partial fulfilment of the requirements for the award of degree in B.Tech and it has been found worthy of acceptance according to the requirement of the university.

Dr.DangetiMukundRao Associate Professor

Professor M.Ramesh Head of the Department

Dept. of Civil Engineering

Dept. of Civil Engineering

Gitam University

Gitam University

S.NO 1 2 3 4 5 6

TITLE ACKNOWLEDGEMENT ABSTRACT INTRODUCTION SCOPE AND PURPOSE REVIEW OF LITERATURE 5.1 5.2 5.3 5.4 5.5

PAGE NUMBER 1

ACKNOWLEDGEMENT

We have taken efforts in the project and gained valuable knowledge and our sincere gratitude to our Associate Professor Dr. D. MukundRao, Department of Civil Engineering for his excellent support, encouragement and valuable guidance throughout the project and his personal involvement in the partial completion of the project. We express our sincere thanks to professorDr. M. Ramesh, and Head of the Department, Civil Engineering, GIT, GITAM UNIVERSITY for providing necessary initiation and valuable support. We are also thankful to teaching and non-teaching staff of department , Civil Engineering and all other people involved in completion of the project.

K.MOUNIKA REDDY D.SAI GOWTHAM B.NAVEEN K.KOTISIVA REDDY G.SATHVIK

(1210212241) (1210212219) (1210212211) (1210212234) (1210212257)

TABLE OF CONTENTS

ABSTRACT

Traffic signal timing optimization has been recognized as one of the most costeffective methods for improving mobility within the urban transportation system. Inappropriate signal timing plans can cause not only discomfort (extra delay) to drivers but also increased emissions and fuel consumption. Thus, it is important to investigate the practice of signal optimization methodology to ensure that newly developed timing plans will improve the system performance. At complex intersections, traffic congestion causes pollution and leads to accidents, high commute times and many other problems. Correct traffic signal timing helps to reduce the congestion and it improves the traffic flow. The primary objective of this study is to develop an optimization traffic signal cycle length model for signalized intersections. Traffic data were collected from 15 signalized intersections in Visakhapatnam city. To evaluate the effects of the optimization cycle length model, major intersections were selected.

INTRODUCTION

Urbanization has its own merits and demerits, the merit part is it increase the standards of living of the people residing in the city, the demerit part of it being it brings increased traffic flow which leads to traffic congestion if the roads are not been developed on par with the increased traffic flow the traffic congestion worsens and leads to serious problems in the day to day activities of people. In most cases the extension of the roads in the city core has the existing buildings can’t be demolished and land acquisition and compensation to be paid are too high and hence the existing routes are to be used with full efficiency for this traffic signals are used. This signals are to be optimized to regulate the traffic with highest efficiency for which where traffic surveys and studies has to be done as signal optimization is one of the most economic step that can be taken and which highly effects traffic regulation. In Visakhapatnam the national highway runs through the entire length of the city and most of city is developed on either sides of the highway. To access the various parts of the city, the city traffic enters the highway and combines with the highway traffic. The NH5 connects major cities on south east coast and hence experiences heavy commercial traffic. The Visakhapatnam being a developing city itself has a high traffic, intersection both of this traffic is the major cause for the various traffic problems of the city. Hence optimization of the signals on this route has to be highest extent for the efficient traffic regulation and it’s flow.

Factors that influence signal coordination:

         

Increased traffic Balanced traffic flow Traffic signal spacing Common cycle length Transit signal priority Updated signal coordination studies Reliable communication systems In-pavement vehicle detection Pedestrian timings Lane reductions

These above factors help in studying the nature of the traffic and help in the co-ordination and optimization of the signals.

What is signal coordination and optimization? This involves the implementation of the best possible timing settings to govern the operation of a traffic signal. The objective is to respond to the demands of motor vehicles, bicycles, and pedestrians in a safe and optimum manner. Signal optimization leads to the minimization of stops and delays, fuel consumption and air pollution emissions and maximizing the progression along an arterial.

Why is it necessary to optimize signals? Traffic signal optimization is one of the most cost-effective ways to improve traffic movement and make our streets safer and efficient. Signal optimization is performed for any or all of the following reasons:  To adjust signal timing to account for changes in traffic patterns due to new developments and traffic growth  To reduce motorist frustration and unsafe driving by reducing stops and delay

 To improve traffic flow through a group of signals, thereby reducing emissions and fuel consumption  To postpone the need for costly long-term road capacity improvement by improving traffic flow with existing resources

Benefits of the signal optimization:           

Decrease in the travelling time Reduction in travel delays Reduction of fuel consumption Reduce the vehicle wear Reduction of the road accidents Improving accessibility Reduction of motorist frustration and road rage Elimination of street widening needs Control on the travel speeds Reduction in the pollution Improved emergency response time

Multi-Objective Optimization of Traffic Signal Timing for Oversaturated Intersection By Yan Li, Lijie Yu,

Siran Tao, Kuanmin Chen Current traffic signal control technologies usually have lower efficiency when the saturation degree is high. Many methods were proposed to improve the efficiency of traffic signal under traffic conditions with high saturation degree. However, very little of those methods can be widely utilized for the reason of the requirements or limitations of those methods. In order to establish one specific traffic control method with the capability of dealing with oversaturated condition, the nature of traffic signal control should be discovered. Traffic signal control methods try to establish the connection between observed traffic parameters, like counts, delay and queue length, with traffic signal parameters, such as phase sequence, cycle length, and split. In this way, various traffic signal optimization algorithms can seek for the values of traffic signal parameters to obtain the optimal values of one or several traffic parameters by considering traffic signal parameters as independent variables under specific traffic condition. This principle is followed by almost all the commonly used traffic control optimization methods, which include TRRL (Transport and Road Research Laboratory) method , HCM (Highway Capacity Manual) method and adaptive traffic control software like SCATS (Sydney Coordinated Adaptive Traffic System) and SCOOT (Split Cycle Offset Optimizing Technique). Then, it can be indicated that the descriptions of traffic flow characteristics are the most critical factor in traffic signal timing optimization. However, the traffic flow becomes unstable when the traffic demand approaches or exceeds the capacity. The detrimental effects, such as spillback, residual queue, or Defacto red, make it hard to describe traffic flow characteristics accurately. Thus, traffic signal optimization methods established by traffic flow formulas under normal traffic condition are no longer suitable for oversaturated conditions. The data-driven based heuristic algorithms could be an ideal method to obtain optimized traffic signal timing plan under oversaturated conditions. The heuristic algorithms do not rely

on the traffic flow formulas but to seek for optimization scenarios based on real time traffic data. For the reason that various factors can affect the effects of traffic signal control under oversaturated condition, it will be better to consider more impact factors in the process of traffic signal optimization. The focus of this paper is to present a multi-objective optimization method to obtain a relatively better signal timing plan for oversaturated intersection. Before we design the algorithm, the characteristics of oversaturated traffic flow are analyzed to acquire the optimized objectives of the algorithm. Then, we present the details of the algorithm, which include coding scheme, optimization objectives, and algorithm selection. At last the convergence and simulation results of the algorithm under different conditions are summarized and analyzed.

Critical Review and Analysis of Traditional Approach for Pre-Timed Traffic Signal Coordination and Proposed Novel Approach By Pranay M. Shah Dr. H. R. Varia Khushboo M Patel Dipesh K. Kadiya Traffic congestion in urban areas has become a global phenomenon now a day. Speedy urbanization and industrialization have caused radically growth of vehicles all over the world. Particularly in India, a developing country the problem of rapid urbanization and increase in growth of vehicle is much more severe than other part of the world considering the speedy increase in population of the country. In view of the increasing traffic congestion and lack of possibilities for infrastructure expansion in urban road networks, the importance of efficient signal control strategies, particularly under saturated traffic conditions, can hardly be overemphasized. The difficulty like congestion, delay, energy consumption, environmental pollution, etc which ultimately leads to increase in vehicle operation cost (VOC) still remain in question if the traffic signals are not coordinated. Coordination of signals is achieved when the flow of traffic on a given phase of movement at one intersection will receive green phase on its arrival at the next signalized intersection. It enhances progressive movement of traffic streams at some specific speed without enforced halts and reduced overall delay. It reduces the speed variations and provides smooth traffic operation, which increases capacity, decreases energy consumption and reduces air and noise pollution, thus reducing overall Vehicle Operation Cost. Goal of signal coordination is to get the maximum number of vehicles through the system with the smallest amount of stops in a comfortable manner. In urban areas, traffic volumes

are higher during peak hours in all the approaches of the signalized intersections, i.e. on the major and minor streets. Therefore, it is necessary to coordinate the signals of the network in all the directions, rather than to coordinate on a single corridor. It is quite difficult to improve the performance of urban traffic signal control system efficiently by using traditional methods of modeling and control because of timevariability, non-linearity, fuzziness and non determinacy in the system. It becomes the research hotspot in this area to apply artificial intelligence methods to urban traffic signal control system. In fact, urban traffic signal control is the product of vehicle modernization: in order to separate the traffic flows that may result in traffic conflict, it is necessary to guide and schedule it effectively by using traffic signals. The problem of urban traffic is more and more serious, and many people are trying hard to solve it. On one hand, people are ceaselessly presenting new theories and new methods, and on the other hand, many area coordinated traffic control systems based on computers are developed one after the other. Generally, traffic control methods include fixed-time control, time-of-day control, vehicle actuated control, semi-actuated control, green wave control, area static control and area dynamic control. In order to solve some of the previously mentioned problems it is necessary to design an optimum signal timing plan. The signal timing plans seek to optimize (i) the cycle length of a signal, that is defined as the duration time from the center of the red phase to the center of the next red phase (ii) green splits, the percentage of time devoted to each phase during a cycle and (iii) offsets, the phase difference between signal transitions at consecutive intersections regulated by traffic signals.

Traffic Signal Optimization for Important Routes By Kishor Bambode Vishal Gajghate

In India number of vehicles are increasing day by day hence major cities in India like Nagpur facing to so many problems such as loss of time, increased in fuel consumption, increase in noise pollution and it caused long queues which produce inconvenience , frustration to drivers or road users. The city Nagpur have too many intersections and too many traffic signals. It rely on pre timed control signal system or fixed cycle control signal system hence it is beneficial to optimize traffic signal and coordinated it by means of Intelligent transportation system. It is not yet adopted on Indian roads. This paper presents an intelligent transportation system for traffic flow prediction and control it through traffic signal optimization and coordination. An important factor that affects the development and restricts the economic construction of cities. It’s a complex system in a random way so it was necessary to optimize traffic control signals to cope with so much urban traffic problems. Inappropriate signal timing. Plans can cause not only discomfort (extra delay) to drivers but also increased emissions and fuel consumption. Thus, it is important to investigate the practice of signal optimization methodology to ensure that newly developed timing plans will improve the system performance. Cross intersection is an important part of the urban road system. Signal timing optimization is most important method that improves the intersection level.

Intersection is an important part of the urban road system. It is very easy to cause the low efficiency in vehicle operating that vehicle have diverging, merging or intersecting repeatedly on the grade crossing. This case will cause the decline of the ability in traffic capacity, the increasing of vehicle delay, and thus the noise pollution and exhaust emission will increase. On the other hand, once the intersection is blocked, it is not only the roads near the intersection but also the roads which are far away will be affected. Therefore, organizational optimization is needed for traffic operating on the intersection. Nowadays, traffic simulation techniques are increasingly being used to optimize the intersection condition. It becomes an essential tool in researching and solving the traffic problem. Traffic simulation investigates the characteristic of reappearing practical traffic system through modern computer technique for pursuing an optimum solution for practical traffic problem. Traffic simulation describes the complicated traffic property accurately and directly through reappear the order of traffic flow. Currently, according to the level of detail traffic model can be divided into micro-model, meso model and macro-model. Among them, micro-simulation model can be at a high level of detail to describe the whole system and its internal relationship. In congested traffic conditions, the study of individual behavior and individual characteristics of the vehicle is often the factor of traffic congestion and traffic congestion analysis for those data to determine the rush hour flow. Moreover, researchers can make analysis and calculations for the rush hour traffic characteristic, the remaining capacity and the saturation through determining the nature and the quantity, and then investigate the vehicle correlation non-vehicle correlation and mixing problem by observing the video recording and surveying. Collection, problem analysis, program optimization, and program evaluation). Synchro system specially engages in signal timing. It sets the time delay, number of stop and queue length these three indices as the target function, and consider the maximum period, minimum period and phase minimum green light time as the limitation. Synchro is an easily and

excellent signal timing optimization software to make up for the trouble of manual calculations. James Mulandi and some other researchers make comparative experiments on various simulation software’s under the same geometry and traffic conditions and carried out that in many simulation software’s, VISSIM based genetic algorithm optimization of signal timing and Synchro programs produce signal timing of the highest quality and provide extremely similar performance.

Review of Road Traffic Control Strategies By MARKOS PAPAGEORGIOU, CHRISTINA DIAKAKI, VAYA DINOPOULOU, APOSTOLOS KOTSIALOS, AND YIBING WANG Traffic congestion in urban road and freeway networks leads to a strong degradation of the network infrastructure and accordingly reduced throughput, which can be countered via suitable control measures and strategies. After illustrating the main reasons for infrastructure deterioration due to traffic congestion, a comprehensive overview of proposed and implemented control strategies is provided for three areas: urban road networks, freeway networks, and route guidance. Selected application results, obtained from either simulation studies or field implementations, are briefly outlined to illustrate the impact of various control actions and strategies. The paper concludes with a brief discussion of future needs in this important technical area. A Traffic Congestion and the Need for Traffic Control Transportation has always been a crucial aspect of human civilization, but it is only in the second half of the last century that the phenomenon of traffic congestion has become predominant due to the rapid increase in the number of vehicles and in the transportation demand in virtually all transportation modes. Traffic congestion appears when too many vehicles attempt to use a common transportation infrastructure with limited capacity. In the best case, traffic congestion leads to queueing phenomena (and corresponding delays) while the infrastructure capacity (“the server”) is fully utilized. In the worst (and far more typical) case, traffic congestion leads to a degraded use of the available infrastructure (reduced throughput), thus contributing to an accelerated congestion increase, which leads to further

infrastructure degradation, and so forth. Traffic congestion results in excess delays, reduced safety, and increased environmental pollution. The following Manuscript received December 6, 2002; revised July 18, 2003. The authors are with the Technical University of Crete, Dynamic Systems and Simulation Laboratory, GR-73100 Chania, Greece (e-mail: [email protected]). Digital Object Identifier 10.1109/JPROC.2003.819610 impressive statement is included in the European Commission’s “White Paper—European Transport Policy for 2010”: “Because of congestion, there is a serious risk that Europe will lose economic competitiveness. The most recent study on the subject showed that the external costs of road traffic congestion alone amount to 0.5% of Community GDP. Traffic forecasts for the next 10 years show that if nothing is done, road congestion will increase significantly by 2010. The costs attributable to congestion will also increase by 142% to reach 80 billion a year, which is approximately 1% of Community GDP.” The emergence of traffic (i.e., many interacting vehicles using a common infrastructure) and subsequently traffic congestion (whereby demand temporarily exceeds the infrastructure capacity) have opened new innovation needs in the transportation area. The energy crisis in the 1970s, the increased importance of environmental concerns, and the limited economic and physical resources are among the most important reasons why a brute force approach (i.e., the continuous expansion of the available transportation infrastructure) cannot continue to be the only answer to the ever increasing transportation and mobility needs of modern societies. The efficient, safe, and less polluting transportation of persons and goods calls for an optimal utilization of the available infrastructure via suitable application of a variety of traffic control measures. This trend is enabled by the rapid developments in the areas of communications and computing (telematics), but it is quite evident that the efficiency of traffic control directly depends on the efficiency and relevance of the employed control methodologies. This paper provides an overview of advanced

traffic control strategies for three particular areas: urban road networks, freeway networks, and route guidance and information systems.

TRAFFIC SIGNAL COORDINATION PLANNING EFFORT By Traffic Engineering Division Colorado Springs, Colorado This report sets forth a flexible plan that will guide us in our efforts to improve traffic signal coordination along our heaviest traveled arterial streets. Over the years, traffic flow along these streets has grown rapidly due to community growth and dependence on the automobile. To address this growth, we need to continually examine our plans, practices and policies to improve our performance. With this plan, we are focusing on efforts to improve traffic signal coordination. Such signal coordination ranks as one of the most cost effective and successful strategies to reduce congestion problems. Each dollar spent optimizing signal timing and implementing system improvements can yield up to $40 in fuel savings. Additionally, signal coordination can also have a dramatic impact on the drivers themselves. As most of us realize, delays and frustrations caused by the operation of traffic signals can lead to accidents and road rage. By bettering our equipment, maintenance practices, and signal programming methods, we can improve the lives of our motoring public by shortening their travel times and providing easier drives. This report provides a brief discussion on the benefits of coordinating traffic signals, signal timing efforts, influencing factors, complementary system operations, and short-range improvements.

We coordinate traffic signals to insure optimum travel speeds, reduced delays, and minimal stops. As national studies indicate, coordinating previously uncoordinated signals can result in a reduction in travel time ranging from 10% to 20%. According to our own recent studies conducted along Academy in February, there is a 10% to 30% improvement in travel times resulting from coordinated signals. These studies coincided with the traffic signal upgrade project, which shut down signal coordination along the Academy corridor for equipment upgrades.

METHODOLOGY

Visakhapatnam is the largest city, both in terms of area and population in the Indian state of Andhra Pradesh. Visakhapatnam is the principal commercial hub of the state, and contributes to its economy in many sectors such as heavy industries, tourism, industrial minerals, fishing, information technology, busiest port and headquarters of Eastern Naval Command of Indian Navy and therefore NH 5 passes through the city which in turn is a part of Golden Quadrilateral. As a result, the city witnesses tremendous growth in traffic over the past decade. A total of fifteen traffic junctions in the stretch of 12 kilometers starting from Venkojipalem junction to NAD junction on NH5 have been identified. These include Venkojipalem Junction, Isakathota Junction, Automotive Junction, Maddilapalem Junction, Satyam Junction, Gurudwara Junction, NGGOs Junction, Akkayapalem Junction, Port Stadium Junction, Thatichetlapalem Junction, Urvasi Junction, Birla Junction, Punjab hotel Junction, R and B Junction and NAD Junction

Based on the studies conducted several inferences are drawn regarding the number of traffic signals and their working condition with signal timings, pedestrian crossings, etc. In the identified fifteen signals 11 are in good working condition and 12 are manned signals but the traffic congestion increases during the peak hours. In the places without traffic signals the flow on the highway and the junctions is comparatively low and hence the traffic flows smoothly but congestion is unavoidable during the peak hours. This necessitates the need to control the traffic during peak hours in order to avoid delay and accidents.

The junctions at which the study is conducted include one of the three types of junctions among Y,T and 4 cross junctions with maximum being 4 cross junctions and controlling traffic along the 4 roads is the most difficult. Though, many of these roads have pedestrian crossings to facilitate the pedestrians several of the pedestrian crossings are weathered out and improvement is needed. Most of the regions on the highway are found to be highly commercial with the already heavy traffic on the highways. The hourly variation in the traffic occurs with the roads being busiest in the morning and the evening. The average speed was computed along these routes by travelling at the common public speed and noting the distance and time of travel. The average of all the speeds calculated at different junctions is found to be 30.38kmph and the range is between 22.15kmph the lowest and 38.02kmph the highest. The reasons for the driver delays and manual delays are identified. The data thus collected was analyzed and critical inferences are drawn.

ISAKATHOTA JUNCTION APPROACH DIRECTION RED YELLOW GREEN CYCLE LENGTH

1 FromMaddilapal em 1:42 0:03 0:51 2:36

2 FromVenkojipal em 1:42 0:03 0:51 2:36

3 From Isakathota 2:17 0:03 0:16 2:36

4 From Mvp 2:07 0:03 0:26 2.:36

MADDILAPALEM JUNCTION APPROACH DIRECTION

1 From Satyam

2 From Mvp

3 From RTC Complex

RED YELLOW GREEN CYCLE LENGTH

1:36 0:03 0:36 2:15

1:31 0:04 0:40 2:15

1:37 0:05 0:33 2:15

2 From Gurudwara 2:10 0:05 0:45 3:00

3 From Rama talkies 2:25 0:05 0:30 3:00

2 From NAD

3 From RTC Complex 1:20 0:04 0:27 1:51

4 From Maddilapalem Depot 2:01 0:04 0:10 2:15

SATYAM JUNCTION APPROACH DIRECTION RED YELLOW GREEN CYCLE LENGTH

1 From Maddilapalem 2:10 0:05 0:45 3:00

GURUDWARA JUNCTION APPROACH DIRECTION

1 From Satyam

RED 1:10 YELLOW 0:05 GREEN 0:36 CYCLE 1:51 LENGTH AKKAYAPALEM JUNCTION

1:10 0:05 0:36 1:51

APPROACH DIRECTION

2 From NAD

1 From Gurudwara

3 FromAkkayapa lem

4 From Eenadu 2:15 0:10 0:35 3:00

RED YELLOW GREEN CYCLE LENGTH

1:00 0:04 0:41 1:45

1:10 0:03 0:32 1:45

1:17 0:03 0:25 1:45

2 From NAD

3 FromPortStadi um 1:55 0:05 0:20 2:20

NGGO’s JUNCTION APPROACH DIRECTION

1 From Gurudwara 1:35 0:05 0:40 2:20

RED 1:35 YELLOW 0:05 GREEN 0:40 CYCLE 2:20 LENGTH THATICHETLAPALEM JUNCTION APPROACH DIRECTION

1 From NAD

RED 1:19 YELLOW 0:04 GREEN 0:54 CYCLE 2:17 LENGTH URVASI JUNCTION APPROACH DIRECTION

1 From NAD

RED 1:30 YELLOW 0:05 GREEN 0:50 CYCLE 2:25 LENGTH BIRLA JUNCTION APPROACH DIRECTION

1 From NAD

RED 1:20 YELLOW 0:04 GREEN 0:51 CYCLE 2:15 LENGTH R&B JUNCTION APPROACH DIRECTION

1 From NAD

2 From Gurudwara 1:40 0:03 0:35 2:17

2 From Gurudwara 1:35 0:04 0:46 2:25

2 From Gurudwara 1:26 0:03 0:46 2:15

2 From Gurudwara

3 From RLY CLNY 1:54 0:03 0:20 2:17

3 From Urvasi 2:05 0:04 0:16 2:25

3 From Birla

4 FromDiamondp ark 1:55 0:05 0:20 2:20

4 FromSanthoshn agar 1:59 0:03 0:15 2:17

4 From Police CLNY 2:05 0:04 0:16 2:25

4

1:59 0:03 0:13 2:15

From JyothiNagar 1:59 0:03 0:13 2:15

3 From Madhavdara

4 From Marripalem

RED YELLOW GREEN CYCLE LENGTH

1:21 0:03 0:51 2:15

1:27 0:03 0:45 2:15

1:59 0:03 0:13 2:15

1:59 0:03 0:13 2:15

2 From Gurudwara 2:33 0:05 0:55 3:33

3 FromGopalpat nam 2:43 0:05 0:45 3:33

4 From 104 area

NAD ‘X’ ROADS APPROACH DIRECTION

1 From Airport

RED YELLOW GREEN CYCLE LENGTH

2:23 0:05 1:05 3:33

3:00 0:03 0:30 3:33

TIME AND DISTANCE BETWEEN THE JUNCTIONS: SEGMENT S

DISTANCE (KM)

TRAVEL TIME (MINUTES )

AVG SPEED (KMPH)

1 2 3 4 5 6 7 8 9 10 11 12 13 14

0.68 0.7 0.51 0.72 0.59 0.32 0.61 0.64 0.85 1.77 1.4 0.7 0.8 1.38

1:38 1:53 1:19 1:21 1:28 0:50 1:23 1:12 1:39 2:53 2:13 1:06 1:19 2:13

25.01 22.15 23.10 31.66 25.85 23.01 26.32 31.97 31.67 36.75 38.02 37.84 35.79 37.20

DESIGN SPEED or SPEED LIMIT (KMPH) 40 40 40 40 40 40 40 40 40 40 40 40 40 40

REMARKS

NOT OK NOT OK NOT OK OK NOT OK NOT OK NOTOK OK OK OK OK OK OK OK

SEGMENTS: SEGMENTS SEGMENT : SEGMENT : SEGMENT : SEGMENT : SEGMENT : SEGMENT : SEGMENT : SEGMENT : SEGMENT : SEGMENT : SEGMENT : SEGMENT : SEGMENT : SEGMENT :

1 2 3 4 5 6 7 8 9 10 11 12 13 14

NAME OF JUNCTIONS VENKOJIPALEM TO ISAKATHOTA ISAKATHOTA TO AUTOMOTIVE AUTOMOTIVE TO MADDILAPALEM MADILLAPALEM TO SATYAM SATYAM TO GURUDWARA GURUDWARA TO NGGO’s NGGO’s TO AKKAYAPALEM AKKAYAPALEM TO PORT STADIUM PORT STADIUM TO THATICHETLAPALEM THATICHETLAPALEM TO URVASI URVASI TO BIRLA BIRLA TO PUNJAB HOTEL PUNJAB HOTEL TO R&B R&B TO NAD ‘X’ ROADS

Complete Route: Venkojipalem to NAD ‘X’ Roads Number of intersections: Fifteen(15) 1. Venkojipalem Junction 2. Isakathota Junction 3. Automotive Junction 4. Maddilapalem Junction 5. Satyam Junction 6. Gurudwara Junction 7. NGGO’s Junction 8. Akkayapalem Junction 9. Port Stadium Junction 10. Thatichetlapalem Junction 11. Urvasi Junction 12. Birla Junction 13. Punjab Hotel Junction 14. R&B Junction 15. NAD Junction DISTANCE : Venkojipalem to NAD ‘x’ Roads --- 11.84km NAD ‘x’ Roads to Venkojipalem --- 11.95km The distance varies as the road from Venkojipalem to NAD falls in the inner curvature, but NAD to Venkojipalem falls in the outer curvature.

VENKOJIPALEM JUNCTION TRAFFIC SIGNAL: YES CONDITION: NOT WORKING MANNED SIGNAL: YES TYPE OF JUNCTION: Y TYPE OF LOCATION: COMMERCIAL PEDESTRIAN CROSSING: AVAILABLE BUT WEATHERED OUT REASONS FOR TRAFFIC:    

Busy highway being intersected by a commercial road. Passing by traffic in highway and heavy traffic from MVP. Sudden increase in traffic during morning and evening hours. A busy road merging into the highway just before the junction.

ISAKATHOTA JUNCTION TRAFFIC SIGNAL: YES CONDITION: WORKING MANNED SIGNAL: YES TYPE OF JUNCTION: ‘T’ JUNCTION TYPE OF LOCATION: COMMERCIAL CUM RESIDENTIAL PEDESTRIAN CROSSING: YES (Available only on Double road) REASONS FOR TRAFFIC:    

Heavy traffic from the residential areas of MVP and presence of many commercial buildings. Heavy traffic on highway. Important location. Presence of the bus stop right before the junction which makes buses and autos to stagnate there.

AUTOMOTIVE JUNCTION TRAFFIC SIGNAL: YES CONDITION: NOT WORKING MANNED SIGNAL: NO, BUT PRESENT AT THE TIME OF PEAK HOUR TYPE OF JUNCTION: ‘Y’JUNCTION TYPE OF LOCATION: COMMERCIAL PEDESTRIAN CROSSING: NO REASONS FOR TRAFFIC:    

Presence of fuel filling station which is used by the majority of the highway traffic this causes obstruction to the traffic. Minor traffic from the HB colony road this causes jam at the junction while crossing. Improper crossing. Insufficient turning radius for heavy automotive.

MADDILAPALEM JUNCTION TRAFFIC SIGNAL: YES CONDITION: WORKING MANNED SIGNAL: YES AND PRESENCE OF A CONTROL ROOM TYPE OF JUNCTION: FOUR ROAD (IMPROPER) TYPE OF LOCATION: PURELY COMMERCIAL PEDESTRIAN CROSSING: YES REASONS FOR TRAFFIC:      

Pretty much well aligned but heavy traffic passing over the junction. Poor visibility of signal for traffic coming out of maddilapalem depot. Major junction of the city. Presence of major bus stop right at the junction. Crucial junction for various important routes to in & out of the city. Heavy traffic due to the presence of the multiplex.

SATYAM JUNCTION TRAFFIC SIGNAL: YES CONDITION: WORKING MANNED SIGNAL: YES TYPE OF JUNCTION: FOUR ROAD TYPE OF LOCATION:COMMERCIAL PEDESTRIAN CROSSING: YES REASONS FOR TRAFFIC:  

Channelized junction but presence of IT companies causes traffic. Major working place and companies like EENADU, MAHINDRA SATYAM, WIPRO…e.t.c., and presence of super market.

GURUDWARA JUNCTION TRAFFIC SIGNAL: YES CONDITION: WORKING MANNED SIGNAL: YES TYPE OF JUNCTION: ‘Y’ JUNCTION TYPE OF LOCATION: COMMERCIAL PEDESTRIAN CROSSING: YES REASONS FOR TRAFFIC:  

Traffic coming from R.T.C complex merges with the highway traffic causing a delay due to turning of buses. Presence of hospital and fuel filling station and residential complexes.

NGGO’S JUNCTION TRAFFIC SIGNAL: YES CONDITION: WORKING MANNED SIGNAL: YES TYPE OF JUNCTION:FOUR ROAD TYPE OF LOCATION: COMMERCIAL CUM RESIDENTIAL PEDESTRIAN CROSSING: YES REASONS FOR TRAFFIC:

VENKOJIPALEM JUNCTION TRAFFIC SIGNAL: CONDITION: MANNED SIGNAL: TYPE OF JUNCTION: TYPE OF LOCATION: PEDESTRIAN CROSSING: REASONS FOR TRAFFIC:

VENKOJIPALEM JUNCTION TRAFFIC SIGNAL: CONDITION: MANNED SIGNAL: TYPE OF JUNCTION: TYPE OF LOCATION: PEDESTRIAN CROSSING: REASONS FOR TRAFFIC:

VENKOJIPALEM JUNCTION TRAFFIC SIGNAL: CONDITION: MANNED SIGNAL: TYPE OF JUNCTION: TYPE OF LOCATION: PEDESTRIAN CROSSING: REASONS FOR TRAFFIC:

VENKOJIPALEM JUNCTION TRAFFIC SIGNAL: CONDITION: MANNED SIGNAL: TYPE OF JUNCTION: TYPE OF LOCATION: PEDESTRIAN CROSSING: REASONS FOR TRAFFIC:

VENKOJIPALEM JUNCTION TRAFFIC SIGNAL: CONDITION: MANNED SIGNAL: TYPE OF JUNCTION: TYPE OF LOCATION: PEDESTRIAN CROSSING: REASONS FOR TRAFFIC:

VENKOJIPALEM JUNCTION TRAFFIC SIGNAL: CONDITION: MANNED SIGNAL: TYPE OF JUNCTION: TYPE OF LOCATION: PEDESTRIAN CROSSING: REASONS FOR TRAFFIC:

VENKOJIPALEM JUNCTION TRAFFIC SIGNAL: CONDITION: MANNED SIGNAL: TYPE OF JUNCTION: TYPE OF LOCATION: PEDESTRIAN CROSSING: REASONS FOR TRAFFIC:

VENKOJIPALEM JUNCTION TRAFFIC SIGNAL: CONDITION: MANNED SIGNAL: TYPE OF JUNCTION: TYPE OF LOCATION: PEDESTRIAN CROSSING: REASONS FOR TRAFFIC:

VENKOJIPALEM JUNCTION TRAFFIC SIGNAL: CONDITION: MANNED SIGNAL: TYPE OF JUNCTION: TYPE OF LOCATION: PEDESTRIAN CROSSING: REASONS FOR TRAFFIC: