Designing a Model of the Early Warning System on the Road Curvature to Prevent the Traffic Accidents

Designing a Model of the Early Warning System on the Road Curvature to Prevent the Traffic Accidents

Muhammad Nanang Prayudyanto Arief GoeritnoSafaruddin Hidayat Al Ikhsan Fadhila Muhammad Libasut Taqwa 

Civil Engineering Study Program, Faculty of Engineering and Science, Universitas Ibn Khaldun Bogor, Jalan Sholeh Iskandar km.2 Kedungbadak, Tanah Sareal, Bogor 16164, West Java Province, Indonesia

Electrical Engineering Study Program, Faculty of Engineering and Science, Universitas Ibn Khaldun Bogor, Jalan Sholeh Iskandar km.2 Kedungbadak, Tanah Sareal, Bogor 16164, West Java Province, Indonesia

Informatics Engineering Study Program, Faculty of Engineering and Science, Universitas Ibn Khaldun Bogor, Jalan Sholeh Iskandar km.2 Kedungbadak, Tanah Sareal, Bogor 16164, West Java Province, Indonesia

Corresponding Author Email: 
arief.goeritno@uika-bogor.ac.id
Page: 
291-298
|
DOI: 
https://doi.org/10.18280/ijsse.120303
Received: 
12 March 2022
|
Accepted: 
22 May 2022
|
Published: 
30 June 2022
| Citation

OPEN ACCESS

Abstract: 

Road traffic safety in developing countries is a complex problem involving many factors such as humans, vehicles, structures, and the roads' environments. This study focuses on reducing traffic accidents for passenger busses, aiming to identify the causes and create a simple computer model to warn in areas like EWS using geometric road data. The survey was conducted at accident-prone locations and simulated the travel speed, road geometric, and traffic composition data. Results can be concluded that the rate is largely influenced by the radius of curvature, visibility, road gradient, and weather conditions. The concept of the EWS computer model was developed using web-based technology that can use to record the data instantly. The model had tested in another location to validate the field parameter and geometric road improvement.

Keywords: 

model of the early warning system, road curvature, road traffic safety, traffic accidents, and the radius of curvature

1. Introduction

There are some definitions about an EWS that are used to guide a lot of actions of individuals, groups, and/or governments [1]. The EWS is a series of systems to notify the occurrence of natural events or the other forms [2, 3]. Its can be in the form of disasters or other natural signs or in the form of a number of traffic accidents [4-8]. The accidents on the traffic of highways or roads are events that have often occurred in the last decades’ era. One of them is caused by the existence of the blind zone. Detecting the blind zone on the road curvature observed [9] from inside the vehicles is an essential function of the DAS that can effectively reduce the occurrence of traffic accidents [4-7, 9-11], fatal collisions [12], and has attracted unprecedented attention [5, 13]. The accident on the Intercity Buses happened in the sharp road curvature involving many passenger injuries and fatalities [14]. On the other hand, VNs have a huge potential to increase roadway safety and traffic efficiency [15].

Indonesia National Police data shows that number of death due to traffic accident has reached 31,234 people in 2010, which means that every one hour there are about 3 to 4 people dead from road traffic accidents [16, 17]. Rolison et al. mentioned three major factors that attribute to road accidents namely human-related factors, vehicle-related factors, and roadway-related factors [18]. American Association of State Highway and Transportation (AASHTO) [19] based on the USA traffic accident data, stated that roadway factors contribute by 3% of road accidents, whereas 34% is attributed by a combination of roadway-related factors and other factors [19]. However, since that the majority of road accidents factors are interrelated, it becomes complex to identify the certain cause of road accidents as the accidents occur due to a combination of several factors [20].

The relationship between geometric elements of road and road accidents has been developed to quantify [21-26]. Assessment using linear regression models showed unsatisfactory results as the properties of linear regression are normally distributed [27, 28], which can generate negative or non-discrete values of accident rates [21]. Another model, Poisson models were suggested [29] and used by Zhang et al. [30], for their consideration of random and sporadic data, in addition to easy estimation of variables relationships, however results can be overestimated or underestimated.

Horizontal road curve radius is a primary element of roads geometric design that is associated with horizontal curve design and it is related to traffic accidents as the smaller the curve radius, the higher the possibility of accidents to occur on roads. Assessment of travel speed shows that vehicle transverse stability which includes the slippage and overturns determines the curve radius value to be selected when designing road horizontal curves [31]. Zhang computed the radius mean and curvature degree for all categories used in his research and then he regressed them against the mean of accident rates in every category, his findings supported some previous studies which found and stated that the curve sharpness has a significant impact on the accident rates [30].

Many automotive manufactures now are using some kind of the DAS in different sections of the vehicle to minimize the several collision possibilities [7]. The manufactures started to implement prevention systems for rear-end collisions, to reduce the number of accidents and the crashworthiness. The rear vehicle position is monitored with the help of radar sensors, which are located directly behind the rear bumper [6]. At least one or more radar sensors detect vehicles approaching from behind which are on direct collision course to the vehicle up to a distance of approximation to 80-100 meters and a relative speed of approximation to 60 km/h. The same radar sensors are also used for the blind spot warner on both vehicle sides too. This system is used to prevent collision of vehicles while overtaking.

The elements of geometric design play a big role to affect of the traffic accidents rates [21-26]. In Indonesia, research and assessment of road geometric was conducted in several cities, such as at Sungai Raya Kepulauan, West Borneo [32], at Magelang, Central Java [33], at Malang, East Java [34], at Tawangmangu, Central Java [35], at Luragung-Cidahu, West Java [36], and on the southern Java ring road [37]. Based on that, to improve the traffic safety on the roads, the drivers must be warn when approaching the road curvature and adjusting the travel speed to mitigate accidents occurrence and severity on roadways.

The EWS made in this first stage is a model to get the minimum radius and maximum permissible speed on an gradient (sag or step)/curvature. Many parameters are used as input to get these values, such as road curvature data, travel speed, traffic analysis, and others. This maximum permissible speed becomes a key in the future to determine whether an object that passes through the gradient/curvature is at a safe rate or needs to be warned to adjust the speed according to the permissible speed. In this built EWS model, the application will process the speed data to be simulated and compare it automatically with the maximum speed from calculations and geometry analysis results. The application will provide a safe sign or warning against the rate.

This EWS database also includes the road safety facilities for survey data. The output of the EWS system built is not only for road users but also for relevant stakeholders to monitor and determine the infrastructure feasibility of the bend/incline. To improve the road design [14, 15], the creation of software on the EWS is really important [4-7], through research objectives, i.e. (i) data validation about the road condition, traffic volume, and bus velocity at the Emen Hills (Subang District) and the Tapalkuda Curvature (Cianjur District), and (ii) the performance of EWS.

2. Materials and Methods of Research

2.1 Materials of the research

The road curvature data, travel speed, traffic analysis and road safety facilities are input for the automatic model development. This system involves many parties’ data inventory. The output of the EWS is an assessment of the severity of conditions against accident hazards. Using traffic management to give better geometric recommendations through i) improvement of road direction, ii) improvement of road safety facilities, iii) road grade improvement, iv) travel demand control, and v) progress of road curvatures and preparation of new road geometrics.

The detection distance depends on the position, the geometry and the relative speed between the two vehicles. The system's main task is the visual warning of the upstream traffic using high-frequency flashing warning lights. By law, the first visual warning level only can be activated for a TTC of less than 1.4 seconds [6]. The vehicle is preparing for an imminent crash at a second warning level. The belt systems inside the car are tensioned to keep the belt slack as small as possible. In addition, when the vehicle is at a standstill, it increases the braking pressure and thereby blocks the vehicle's brakes. This complete blocking of the brakes is intended to help prevent a movement in the positive X direction in the event of a collision and to avoid accidents with other road users. Depending on the manufacturer, the backrests are also moved into a vertical position, and windows and sunroofs are closed.

2.2 Methods of the research

The research method is an algorithm of a researcher for conducting the research that is carried out in the form of stages for achievement and accordance with the objectives of research [38-41]. The flowchart of the research methods is shown in Figure 1.

Figure 1. Flowchart of the research methods

Based on Figure 1 can be explained that for elaborating the data validation, including (a) road condition and (b) traffic measurement analysis, namely (i) results of the measurement of traffic volume and bus velocity at Emen Hills (Subang District), (ii) results of the measurement of traffic volume and bus velocity at the Tapalkuda Curvature (Cianjur District). The elaborations of the EWS performance are road condition and validation review of the EWS.

3. Results and Discussions

3.1 Validating the measurement data

Based on the data validation conducted, two assessments have obtained the road condition and analysis of the traffic measurement. Existing the data validation of the road geometric and facilities, long and cross-section, and the radius of curvatures at the Emen Hills (Subang District) and the Tapalkuda Curvature (Cianjur District) are shown in some tables and figures. The characteristics of road geometrics are shown in Table 1; the road facilities are shown in Table 2, the long section and the radius of curvatures at the Emen Hills (Subang District) are shown in Figure 2, the cross-section characteristics at the Emen Hills (Subang District) is shown in Table 3, the long section of Sta. 0+000 to Sta.0+450 and the radius of curvatures at the Tapalkuda (Cianjur District) is shown in Figure 3, and the cross-section characteristics at the Tapalkuda Curvature (Cianjur District) are shown in Table 4.

Based on Figure 4, the measurements of bus velocity at the Emen Hills (Subang District) are the average space velocity of bus-type vehicles and are also influenced by the slope of the observed road segment. It obtained the highest average speed on downhill road conditions at the Emen Hills (Subang District) toward the Ciater at Sta. 0+350 to Sta. 0+370 with speed up to 60 km/h, and the lowest average rate occurs on the road with the smallest radius, i.e., the Sta. 0+390 to Sta. 0+410 with an average speed of 15 km/h. In uphill road conditions, the average vehicle speed is 8 to 23 km/h. The space velocity at the Emen Hills is shown in Table 5.

Table 1. The characteristics of road geometric

No.

Parameter

Location

Emen Hills, Subang District, West Java

Tapalkuda Curvature, Cianjur District, West Java

1

Road Classification

Arterial, Provincial Road

Arterial, National Road

2

Length of Critical Section

200 meters (Sta. 0+300 – Sta. 500)

60 meters (Sta. 0+180 - 0+240)

3

Road Width

14 -16 meters (2 lanes two ways)

7 – 8 meters (2 lanes two ways)

4

Shoulder

1 meter on both sides, unpaved

1 meter on both sides, concrete pavement

5

Road Widening in the Curvature

4 – 6 meters

None

6

Median

Road Marking

Road island, Sta. 0+275 – Sta. 0+350

7

Vertical Gradient

10% - 12%

7% - 8%

8

Maximum Superelevation

10%

10%

Table 2. The road facilities

No.

Road Safety Facilities

Location

Emen Hills, Subang District, West Java

Tapalkuda Curvature, Cianjur District, West Java

1

Climbing Lane

Available

No

2

Emergency Stop Lane

Available

No

3

Road Marking

Available

Available

4

Drainage

Available

Available

5

Road Signs

Improper

Available

6

Street Lighting

Available

Available

7

Guard rail

Not Available

Available

8

Concrete barrier

Not Available

Available

Table 3. The cross-section characteristics at the Emen Hills (Subang District)

Sta.

Segment Length (m)

Curvature Type

Radius (m)

Gradient

Left

Right

0+000

50

SL

 

-5%

-4%

0+050

50

SL

 

-8%

-5%

0+100

50

SC

 

-8%

+10%

0+150

50

C

62.5

-2%

+8%

0+200

50

C

62.5

-8%

+4%

0+250

50

C

62.5

-14%

+4%

0+300

50

SC

 

-7%

+7%

0+350

50

SC

 

-2%

-3%

0+370

20

C

24.3

+6%

-4%

0+390

20

C

24.3

+7%

-5%

0+410

20

C

24.3

+11%

-11%

0+430

20

C

24.3

+11%

-9%

0+450

20

C

24.3

+4%

'-6%

0+475

25

C

24.3

+4%

'-5%

0+500

25

SC

 

-9%

-2%

0+525

25

C

48.1

-7%

+9%

0+550

25

SC

 

-4%

+3%

0+575

25

SL

 

-4%

-2%

0+600

25

SL

 

+3%

-6%

Abbreviations in the table: Sta. = Station; SL = Straight Line; C = Circle; SC =Spiral Circle.

Figure 2. The long section and the radius of curvatures at the Emen Hills (Subang District)

Figure 3. The long section of Sta. 0+000 to Sta.0+450 and radius of curvatures at the Tapalkuda Curvature (Cianjur District)

Table 4. The cross-section characteristics at the Tapalkuda Curvature (Cianjur District)

Sta.

Segment Length (m)

Curvature Type

Radius (m)

Gradient

Left

Right

0+000

50

SL

 

-4%

-5%

0+050

50

SC

 

-2%

-5%

0+100

50

C

164.4

-4%

-9%

0+150

50

SC

 

-4%

-8%

0+175

25

SL

 

-1%

-9%

0+200

25

C

19.9

+9%

-13%

0+225

25

C

19.9

+7%

-16%

0+250

25

C

19.9

+4%

-14%

0+275

25

S

 

-9%

-9%

0+300

25

S

 

-5%

+10%

0+325

25

C

43.4

-5%

+11%

0+350

25

S

 

-4%

+2%

0+375

25

SL

 

-4%

-4%

0+425

50

SL

 

-5%

+2%

Abbreviations in the table: Sta. = Station; SL = Straight Line; C = Circle; SC =Spiral Circle.

Table 5. The space velocity at the Emen Hills

Sta.

The segment length (m)

Toward to

the Ciater

Toward to

the Lembang

m/s

km/h

m/s

km/h

300-350

50

14.11

50.80

2.19

7.90

350-370

20

16.72

60.19

9.56

34.40

370-390

20

10.92

39.31

4.42

15.91

390-410

20

4.24

15.27

2.98

10.73

410-430

20

4.49

16.17

4.86

17.49

430-450

20

11.20

40.31

5.56

20.01

450-470

20

4.52

16.27

5.95

21.43

The results of the measurement of the traffic volume are based on the observations that have been made in the Tapalkuda Curvature (Cianjur District) and obtained 15,000 passenger cars per day so that it can cause some curves. The data curves of traffic volume at the Tapalkuda Curvature toward the Puncak to the Cianjur District and totals are shown in Figure 5.

The bus velocity measurement results at Tapalkuda Curvature (Cianjur District) are shown in Table 6.

Based on Table 6, the results of observations at the Tapalkuda Curvature (Cianjur District) show that the average space velocity of bus-type vehicles is also influenced by the slope of the observed road segment. It obtained the highest average speed on downhill road conditions towards Cianjur District at Sta. 0+000 to Sta. 0+150 with a speed of up to 58 km/h. The lowest average rate occurs on the road with the smallest radius, namely the Sta. 0+15 to Sta. 0+375, with an average speed up to 15 km/h. In uphill road conditions, the lowest vehicle speed occurred at Sta. 0+275.

Table 6. The results of measurement of bus velocity at Tapalkuda Curvature (Cianjur District)

Sta.

Segment Length (m)

Toward to

the Cianjur District

Toward to

the Puncak

m/s

km/h

m/s

km/h

0-150

150

16.10

57.95

11.82

42.55

150-225

50

8.02

28.87

6.51

23.44

225-275

50

10.14

36.48

6.00

21.60

275-325

50

10.97

39.50

8.94

32.18

325-375

50

10.45

37.63

7.53

27.09

375-475

100

14.21

51.16

9.80

35.27

Figure 4. The data curves of traffic volume at the Emen Hills toward the Ciater, to the Lembang, and the total traffic volume

Figure 5. The data curves of traffic volume at the Emen Hills toward the Puncak, toward the Cianjur District, and the total traffic volume

Table 7. The characteristics of geometric data

No.

Parameter

Lembah Koi Curvature, Cianjur District, (West Java)

1.

Road Classification

Arterial Road, National

2.

Length of Critical Section

100 meters (STA 0+150 – 0+250)

3.

Road Width

7 – 8 meters (2 lanes two ways)

4.

Shoulder

1 meter on both sides, concrete pavement

5.

Road Widening in the Curvature

None

6.

Median

None

7.

Vertical Gradient

5% - 7%

8.

Maximum Superelevation

14%

9.

Road radii

37 meters

3.2 Performance of the EWS

The display of geometric tracing at Lembah Koi, Cipanas Regency, Cianjur District is shown in Figure 6, the characteristics of geometric data are shown in Table 7, and the display of the initial EWS modeling application is shown in Figure 7.

Based on Figure 6, Table 7, and Figure 7, it can be explained that during the validation of the EWS program, the system obtained the following note that the EWS program that has been developed can still be improved, both in terms of appearance, the UI, ease of use (user-friendly system), as well as in the data processing process. Based on the note and findings above, several recommendations that can submit included the following, namely i) filling and presenting traffic data based on traffic counting results, ii) weighting of AEK, iii) geometric calculations on long incline/descending, iv) hotline service, v) adding a new account online (for the general public), and vi) the general public (users) are allowed to add new location data, equipped with existing photos in real-time.

Figure 6. The geometric tracing at Lembah Koi, Cipanas Regency, Cianjur District

Figure 7. The display of the initial EWS modeling application

4. Conclusion

The effort to reduce traffic accidents in road curvature in this research is dedicated to passenger busses, aiming to identify the causes and create a simple computer model to warn called EWS. The survey was conducted at accident-prone locations on the arterial roads and simulated travel speed data, geometric and traffic composition data. One site has an extremely sharp horizontal alignment, and another has a critical horizontal and vertical alignment. Based on the results, the speed is largely influenced by the radius of curvature, visibility and road gradient, and weather conditions. The traffic is estimated at 15,000 cars/day with traffic speeds ranging from 7.90 to 60.19 km/h; however, bus speed can run to 57.69 km/h, assuming that it cannot control the speed when entering the sharp curvature. The EWS program developed can be used to model to warn the bus driver since the first time can use the web-based technology to record the data instantly. The improved model should be proven and tested in other locations to validate the field parameter and geometric road improvement.

Nomenclature

EWS

Early Warning System

DAS

Driving Assistance System

VNs

Vehicular Networks

TTC

Time To Collision

Sta.

Station

m

meter

m/s

meter per second

km/h

kilometers per hour

SL

Straight Line

C

Circle

SC

Spiral Circle

PCE/h

Passengers Car Equivalent per hour

2/2 UD

Two ways/Two Lines, Undivided

UI

User Interface

AEK

Accident Equivalence Figures

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