Analysis of Traffic Congestion At Ettumanoor Kottayam Route and Its Solution

Analysis of Traffic Congestion At Ettumanoor Kottayam Route and Its Solution

Aparnna Binu 1

Student

Department of Civil Engineering Mangalam College of EngineeringEttumanoor, India

Alphy John Jacob 2

Student

Department of Civil Engineering Mangalam College of EngineeringEttumanoor, India

Chinchu Sabu 3

Student

Department of Civil Engineering Mangalam College of EngineeringEttumanoor, India

Dharmajith M D 4

Student

Department of Civil Engineering Mangalam College of EngineeringEttumanoor, India

Smruthy P Nair 5

Assistant Professor

Department of Civil Engineering Mangalam College of Engineering Ettumanoor, India

Abstract The spontaneous increase in number of vehicles onroad attributes the ingeneration of traffic problems like accidents, traffic congestion and delay. Traffic congestion is a condition in transportation characterized by slower speeds, long travel time and increased vehicular queueing. Nowadays it is the most complex issue of transportation due to increase in high ownership of vehicles. A substantial portion of working hours is getting wasted on the road. Poor public transportation system, rapid increase in population, unplanned transport infrastructure are the primary causes of congestion. The purpose of our study is to analyze the present condition of the area and to find out solutions for the problems using factor analysis. Etumanoor town is one of the most congested places along MC road in Kottayam district thats why we choose Ettumanoor Kottayam route for our study. There are many factors that lead to traffic congestions at different spots and by analyzing these factors we find out the solutions.

Keywords: Traffic congestion, traffic demand, transportation system.

1. INTRODUCTION

   Traffic congestion is a transport condition that occurs due to slower speeds, improper signals, less awareness about traffic rules and regulations, decrease in road capacity. Population rate of India is increasing day to day and the demand of private vehicle is also increasing. An efficient network of transport service is required to support the complex activity patterns within city, there is a strong relation between transportation and city development in our area.

   The main purpose of transportation is to provide an efficient means to satisfy human needs for a heterogeneous variety of societal groups. Therefore, the general goal is to meet this need for mobility. urban transportation planning contains several activities like analyzing present condition of the area such as the land use patterns and travel demand produced from the land development. After that development plans are prepared by forecasting the land,

   travel demand, population etc. the purpose of the process is to perform a prediction of travel demand and after that suitable alternative are implemented to reduce the traffic congestion.

   In this study we analyze the traffic flow at Ettumanoor Kottayam route by conducting transportation surveys and traffic volume, speed is calculated. we selected 5 major spots for our study which contains intersections. After the pilot survey we find out many factors which lead to congestion and among those 9 factors are taken for detailed survey. Traffic volume at 5 spots is taken during morning and evening peak hours. Traffic speed is taken manually. Questionnaire survey is conducted based on 9 factors. SPSS software is used to analysisthese factors.

2. LITERATURE REVIEW

   The studies bring about the salient points of published literatures and other works.

   1. Tanzina Afrin and Nila Yodo(7 JUNE 2020) A survey of road traffic congestion measures towards sustainable and resilient transportation system. It identified the root causes of congestion. The advantages and disadvantages of each measure are identified from data analysis.

   2. A.Vinidha Roc, P.R , Banuprakash, G.Paul Asir Ninon Raj,L. Prasad.(July 2017) SMART TRAFFIC LIGHT SYSTEM,A system of cameras are used to regulate their obtained information in their respective places and coordinates with other camera in the system to change traffic signals and suggest green signal for that route to avoid maximum traffic. Image processing unit is the central unit to maintain the traffic in normal; speech processing unit is secondary unit, the combined processing is important only in emergence.

   3. Geethu Lal, Divya L.G., Nithin K.J,Susan Mathew , Bennet Kuriakose (2016) sustainable traffic improvement for urban road intersections of developing countries; A Case study of Ettumanoor , INDIA., The

      analysis of the collected data from the direct field survey of traffic volume , land use, and pedestrian counts reveals that improper planning, unauthorised parking, lack of signal are the main causes. Junction signalization and junction improvement are the remedial measures proposed.

   4. C.H.Mohammed Koya KMGA Engineering College, Kerala. Volume 6, special issue 4 (march 2017). traffic and are improvement of baker junction, 2 intersection in Kottayam town is considered as the project stretch and relevant datas are collected. By analysing all the problems suitable improvement proposals are adopted.

   5. Shijilk, Geeva George , Dr Praveena, International Journal of Engineering, Construction Phase Road Safety Audit Of Kottayam Ettumanoor MC road, the challenges to road safety of spots are identified. Spot speed study was conducted. Factors were identified based on negative response survey and switching response survey.

3. OBJECTIVES OF WORK

   • To access the existing condition of road network andto identify the major gridlocks.

   • To identify various factors governing the trafficcongestion.

   • To collect the traffic volume and speed.

   • To identify peoples opinion and suggestions.

   • To establish proper solutions for the specificproblems.

     Identify the major junctions at Etumanoor Kottayam route

4. METHODOLOGY

   Data analysis

   • SPSS software

   Result

5. STUDY AREA

   First, we visited the study area and reduce long route into 5 major spots which contains deviation.

   Major spots are;

   • Ettumanoor bus stand

   • Adichira

   • Chavittuvari

   • Gandhinagar

   • Nagambadam

     5 major spots are taken

     ROUTE MAP FROM ETUMANOOR TO KOTTAYAM

     Conduct pilot survey and identify factors that cause

     congestion.

     1. DATA COLLECTION

        The different data required for study is collected through trafficsurveys.

        Data collection by survey

        • Traffic volume

        • Traffic speed

        • Questionnaire survey

        1. TRAFFIC VOLUME

It is defined as the procedure to determine volume of traffic moving on the roads at a particular time. It is done by counting the vehicles during morning peak hours [8 to 10am] and evening peak hours [3.30 to 5.30 pm]. The volume count at selected 5 spots was carried out and existing condition of the road stretches are analysed. The result obtained are shown below;

TRAFFIC VOLUME AT ETUMANOOR BUS JUNCTION

• MORNING PEAK HOURS

Table 1 numb of vehicles towards Adichira from Ettumanoor

VEHICLE	TIME
CAR	8:00 to 8:30	8:30 to 9:00	<>9:00 to 9:30	9:30 To 10:00
	290	324	519	483
BIKE	298	398	610	511
LORRY AND TRUCK	35	30	35	38
BUS	32	48	46	48
THREE-WHEELER	45	62	127	108

EVENING PEAK HOURS

Table 2 numb of vehicles during evening peak hours

MORNING

700

600

500

400

300

200

100

0

Bike

Bus

Lorry and Truck

Car

3 Wheeler

Fig.1. Number of vehicles versus time on 21/03/2022

VEHICLE		TIME
		3:30	4:00	4:30	5:00
		to	to	to	to
		4:00	4:30	5:00	5:30
CAR		455	495	520	539
BIKE		460	503	548	560
BUS		60	75	80	86
LORRY TRUCK	AND	38	30	29	24
THREE-WHEELER		150	165	178	189

600

500

400

300

200

100

0

Evening

Bike Bus

Lorry or Truck

Car

3 Wheeler

Fig .2.Number of vehicles versus time on 21/03/2022

Vehicle count on remaining 4 spots were taken in similarmanner and was considered for result analysis.

1. TRAFFIC SPEED

   Traffic speed count was collected from 5 spots.Formula: SPEED = DISTANCE / TIME

   Ettumanoor to Adichira, Distance = 5.9 km

   Table .3. Speed count of car

   CAR

   12

   10

   8

   6

   4

   2

   0

   0

   2

   4

   6

   No. of Vehicle

   8

   10

   12

   3PM TO 5PM 8AM TO 10AM

   Speed (m/s)

   TIME	VEHICLE TYPE	VEHICLE NUMBER	CONSUMPTION OF TIME	SPEED [M/ SEC]
   C C C C 8:00- 10:00 C AM C	AR	05 10	min	9.8
   	AR	25 12	min	8.2
   	AR	36 10	min	9.8
   	AR	45 14	min	7.0
   	AR	66 9	min	10.9
   	AR	28 12	min	8.2
   	CAR	55	9 min	10.9
   	CAR	58	14 min	7.0
   	CAR	15	9 min	10.9
   	CAR	18	12 min	8.2
   3:00- 5:00 pm	CAR	08	13 min	7.5
   	CAR	67	10 min	9.8
   	CAR	52	10 min	9.8
   	CAR	75	13 min	7.5
   	CAR	29	9 min	10.9
   	CAR	38	15 min	6.5
   	CAR	24	10 min	9.8
   	CAR	30	9 min	10.9
   	CAR	86	9 min	10.9
   	CAR	59	11 min	8.9

   Fig .3. numb of vehicle versus speed

   The vehicle speed data of bus, bike, lorry and truck and three-wheeler was estimated and analysed similarly.

2. QUESTIONNAIRE SURVEY

To identify peoples opinion regarding gridlock on the road, we conducted a well tabled questionnaire survey on a pool of 190. Each question booklet contained 12 questions fragmented to 9 factors and all the participants were enthusiastic about thesurvey.

Fig .4. Questionnaire survey format

The opinions from questionnaire survey is converted to Likert scale with 5 points. And kept for software analysis. We use Statistical Package for Social Science [SPSS] software and done factor analysis.

VI. DATA ANALYSIS

1. SOFTWARE ANALYSIS

   With the help of SPSS software, we done factor analysis and reduce 9 components to 3 variables. First of all, we have 9 factors for our analysis. The purpose of factor analysis is to reduce our number of variables into a smaller number of components. The number of variables we input in our analysis, will always be equal to the number of components. Eigenvalues are shown in fig. the number of factors or components that have eigenvalues greater than one are taken. All other components with eigenvalues less than one, we do not keep. Since only 3 components had an eigenvalue greater than one, we only have 3 components in our solution. We reduce those 9 factors to 3 components. Some of eigenvalues will be always equal to the number of components.

   FFFFF

   Table.4. Factor analysis

   Table shows KMO and Bartletts test values. the std value for KMO and Bartletts test should be more than 0.5 and less than 0.05.it actually testing whether correlation matrix are related.

   The test result shows that variable 6 contribute maximum amount of congestion in road. Roadside shops are variable 6 and it creates major traffic congestions. It reduces road width and parking spaces on road.

   1. CONCLUSION

      Traffic congestions are mainly created by traffic users by misbehaving in road and violating the rules. Congestion on Ettumanoor Kottayam route can be solved by providing proper width for road, avoid congested road side shops, provide parking area for vehicles, separate lane for heavy vehicles, proper signals, bypass roads etc. Parking should be restricted on the roads as it decreases the width of carriageway. By factor analysis we found that each factors contribute how much amount of congestion on road. Public transport should be increased to reduce gridlocks and accidents.

   2. REFERENCES

[1] R.T. KdiyaliTrafic EngineeringPAGE: 323-331

[2] S.K. Ghanna, Highway EngineeringLaxmiPublications , Chennai, India.

[3] Amudapuram Mohan Rao, Kalaga Ramachandra Rao (2012) Measuring Urban Traffic Congestion A Review International Journal for Traffic and Transportation Engineering.

[4] R. J. Smeed (1967) Traffic Studies and Urban Congestion Inaugral address by the Professor of Traffic Studies at University College London

[5] J.Michael Thomson (1946) Journal of Transport Economics and Policy Reflections on Economics of Traffic Congestion(Paper No.H-070)

[6] Bijit Kumar Banik, MD. Aktarul Islam Chowdury & MD. Shahjahan Kaisar Alam Sarkar (2006) Study of Traffic Congestion at Sylhet city Journal of Indian RoadsCongress, Vol. 1: issue 2

/Jan March 2009

[8] Takyi Harriet, Kofi Poku, Anin Kwabena Emmanuel (2013) An Assessment of Traffic Congestion and Its Effect on Productivity in Urban Ghana international Journal of business and Social Sciences (JETEAS) 2 (6) PG: 1034-1041

[9] Lum. K.M. (1998), Speed Flow Modelling of Arterial Roads in Singapore.

[10] Marwah and Buvanesh. (2000), Levelof Service Classification for Urban Heterogeneous Traffic.

[11] Chandra S. (2004), Different Sections of Urban Roads.

[12] Prasad N.V (2009), Central Road Research Institute (CRRI), New Delhi to Determine the PCU Value for different types of Vehicles.

[13] Chandra S and Sikdar. (2000), Factors Affecting PCU in Mixed Traffic Situations in Urban roads.

[14] Arkatkar. (2011), Effect of Intercity Road geometry on capacity under Heterogeneous traffic congestions.