Assessment of Pedestrian Level of Service for Mixed Lane

 

Anand Kumar Raghuwanshi1, Dr. (Mrs.) Vandana Tare2

1M. E. Student - CE and AMD S.G.S.I.T.S. Indore,

2Professor - CE and AMD S.G.S.I.T.S. Indore,

*Corresponding Author Email: andi.rag22@gmail.com, vtare@rediffmail.com

 

ABSTRACT:

The objective of the present study is to carry out the pedestrian level of service on the mixed lane urban road sections and to develop condition prediction model for mixed lane for the purpose of improving the serviceability of mixed lane and identifying factors which affect pedestrian LOS at mixed lane. The factors fall into three main categories, pedestrian factors, crosswalk factors and roadway factors. This analysis was done based on Highway Capacity Manual (HCM) 2010. The PLOS model was developed using multiple linear regression analysis. In order to determine PLOS, a set of data were collected using a video graphic survey. From this study, it is found that, pedestrian flow, pedestrian speed, pedestrian holding area, pedestrian crossing time, vehicular traffic and road side parking are significant factor in the development of the PLOS model, and therefore influence the movement of pedestrians at mixed lane.

 

KEYWORDS: Pedestrian level of service, Vehicular traffic, Road side parking, Vehicle pedestrian interaction, Multiple linear regression method.

 

 

INTRODUCTION:

The traffic on the roads of Indian cities is highly heterogeneous comprising vehicles of wide ranging static and dynamic characteristics. All categories of vehicles share the same road space without any segregation and occupy any lateral position on the road depending on the availability of road space at a given instant of time without any lane discipline. Under the said heterogeneous traffic flow conditions, the pedestrian is losing the space. The various pedestrian facilities provide segregation of the pedestrian traffic from the vehicular flow, thereby increasing the perceived safety.

 

The services delivered by these facilities needs to be evaluated for further improvement and for better design and construction of the future works. This can be effectively carried out through the evaluation of the offered level of service (LOS). Pedestrian level of service indicates the qualities of a pedestrian space and serves as a guide for development of standards for pedestrian facilities.

 

The level of service standards available was developed for the traffic conditions in the western countries. Its applicability in the Indian condition may not give true picture. The objective of this study is to identify the factors affecting pedestrian LOS in mixed lane and propose a suitable method for the estimation of pedestrian LOS.

 

LITERATURE REVIEW:

Various researchers have considered different parameters to define LOS for pedestrian facilities. Literature referred for this paper is given as under:

M. I. Nazir et al. (2014) in his article presented a statistical analysis of the data by using the statistical software SPSSv16. The collected data were used to develop the speed-flow-density-space relationship of pedestrian and this established relationship could be used as a basis for the development of more efficient, adequate, and safer facilities for the pedestrians.

 

Rajatrastogi, et al. (2014) in his paper gave a descriptive overview of the pedestrian movements along the carriageway, at its side or other pedestrian facility. The LOS criteria were developed using one approach based on the rate of change of curvature of the pedestrian flow-area module curve and another based on speed ratio-density plot.

 

Rima Sahani, et al. (2013) in her study found out PLOS criteria of urban off-streets facilities in developing countries having heterogeneous traffic flow conditions. This analysis followed the Highway Capacity Manual (HCM) 2010 methodology.

 

SambhuMohanty, et al. (2013) in his paper examined about the walk able environment for pedestrians with minimum pedestrian-vehicle interaction. In order to determine PLOS a set of qualitative data was collected by devising a questionnaire, this was used to get the real time response of people in road environment.

 

P. Vedagiri (2012) in his article described the factors which affect pedestrian level-of service (LOS) at signalized intersection crosswalks. Factors considered to develop the model were turning traffic, through traffic, number of pedestrians and pedestrian delay.

Basil David et al. (2008) in his study developed (P-LOS) model for crosswalks at signalized intersections for the purpose of improving the serviceability of crosswalks at signalized intersections and identifying factors which affect pedestrian crossing at these locations.

 

DATA COLLECTION AND METHODOLOGY:

Field survey is done to explore the condition of the traffic, the crossing facilities and the delay at the sidewalk. Video graphic technique is used to collect the field data like pedestrian volume, traffic volume, crossing time and pedestrian speed. Effective walkway width, roadway width and width occupied by street were also measured during the field survey. The survey is carried out on week days during peak hours, 6:00pm to 9:00pm for 9 sections. Data for each 15minutes interval is extracted from the video to develop the model. The survey data for typical section are shown in Table 1.

 

Based on data average pedestrian space is calculated using HCM 2010. For this following steps are involved:

      Step 1: Determination of Effective Walkway Width

      Step 2: Calculation of Pedestrian Flow Rate

      Step 3: Calculation of Average Pedestrian Space

 

The variables in the determination of PLOS are as follows:

1.    Average Pedestrian Space (Y).

2.    Volume/capacity ratio of Pedestrian (X1).

3.    Volume/capacity ratio of Vehicles (X2).

4.    Pedestrian Crossing Time (X3).

5.    Parking Factor (X4).

 

Table: 1. Pedestrian Traffic Survey Data at Section 1

 

 

For development of model multiple linear regression analysis is done. In which average pedestrian space as dependent variable and volume/capacity ratio of pedestrian, volume/capacity ratio of vehicles, crossing time (sec), parking factor (road side parking) as independent variables. The data for all the 9 sections are given in Table 2.

DEVELOPMENT OF MODEL:

From the analysis quantitative level of service model has been developed to determine the P-LOS is shown below along with statistical parameters

 

Y = 20.99  0.862X1 7.246X2 0.468X3 7.20X4

 

Table: 2. Data for Regression Analysis for all the 9 sections

S.

No.

Y (Avg. Pedestrian space)

X1 (V/C of Pedestrian)

X2 (V/C of vehicle)

X3 (Crossing time)

X4 (Parking Factor)

1

4.35

0.93

1.03

8.63

0.58

2

5.33

0.74

0.98

7.48

0.64

3

3.47

1.04

1.20

9.26

0.52

4

2.52

1.12

1.13

9.96

0.66

5

2.21

1.49

1.19

8.76

0.62

6

1.55

2.32

1.18

10.07

0.60

7

1.37

2.40

1.21

8.91

0.67

8

1.82

1.95

1.14

9.15

0.65

9

1.74

2.04

1.15

10.20

0.60

 

 

Table: 3. Statistical Parameters of Regression Equation

Variables

Coefficients

Standard Error

t Statistic

P-value

Lower 95%

Upper 95%

Intercept

20.991

2.987

7.028

0.002

12.699

29.283

X1 (V/C of Pedestrian)

-0.862

0.256

-3.372

0.028

-1.572

-0.152

X2 (V/C of vehicle)

-7.246

1.964

-3.689

0.021

-12.700

-1.793

X3 (Crossing time)

-0.468

0.157

-2.973

0.041

-0.905

-0.031

X4 (Parking Factor)

-7.200

2.557

-2.815

0.048

-14.300

-0.100

 

 

Table 4 shows the correlation matrix has been developed for dependent and independent variable.

Table: 4. Correlation Matrix

Correlation

Y

(Avg. Pedestrian space)

X1 (V/C of Pedestrian)

X2 (V/C of vehicle)

X3 (Crossing time)

X4 (Parking Factor)

Y (Avg. Pedestrian space)

1.000

-0.897

-0.830

-0.724

-0.285

X1 (V/C of Pedestrian)

-0.897

1.000

0.658

0.533

0.303

X2 (V/C of vehicle)

-0.830

0.658

1.000

0.615

-0.098

X3 (Crossing time)

-0.724

0.533

0.615

1.000

-0.131

X4 (Parking Factor)

-0.285

0.303

-0.098

-0.131

1.000

 

The normal probability plot provides information about the regression line. Figure 1 show the normal probability curve.

 

 

Fig: 1. Normal P-P plot of Regression Standardized Residual

 

 

Pedestrian space is the average area provided for each pedestrian in a walkway or queuing area. The pedestrian flow decreases with increases in average pedestrian space as shown in figure 2.

 

 

Fig: 2. Relationship between Pedestrian Flow – Average Space

 

Figure 3 illustrates the relationship between pedestrian speed and pedestrian volume. This curve shows that when there are few pedestrians on a walkway (i.e. low flow levels) there is space available to choose higher walking speed. As flow increase, speeds decline because of closer interaction among pedestrians. When a critical level of crowding occurs movement becomes more difficult and both flow and speed decline.

 

 

Fig: 3. Relationship between Pedestrian Speeds – Volume

 

Figure 4 confirm the relation of walking speed and available space, and suggest some point of demarcation for developing LOS criteria.

 

 

Fig: 4. Relationship between Pedestrian Speeds – Average Pedestrian space

 

CONCLUSIONS:

A regression line is developed between average pedestrian space and vol. /cap. ratio of pedestrian, vol. /cap. ratio of vehicle, pedestrian crossing time (sec), and parking factor. The equation has been tested for statistical parameters.From correlation matrix it is found that pedestrian traffic and vehicular traffic are the most prominent factors. The observation indicates that at an average pedestrian space greater than 1.5 m2/ped, the average speed of pedestrian is approx. constant. Development of a quantitative level of service model provides a wider domain for the planning and design of sidewalks in urban areas.

 

REFERENCES:

1.     David Basil, Choong Siew, Kamarudin Ambak, and Mohd. Ezree Abdullah. “Pedestrian level of service model for crosswalk at signalized intersections”. University Tun Hussein Onn Malaysia. (2008)

2.     Vedagiri P., Nagraj R. “Modeling pedestrian delay and level-of-service at signalized intersection crosswalks under mixed traffic condition”. Transportation Research Board, TRB, National Research Council, Washington, D.C. (2013)

3.     Raghuram B., Vedagiri P. “Modelling pedestrian road crossing behavior under mixed traffic condition”. European Transport Research paper, (2013) Issue 55, Paper no 3, ISSN 1825-3997.

4.     Bhuyan PK, and Sahani Rima. “Level of Service Criteria of Off-street Pedestrian Facilities in Indian Context using Affinity Propagation Clustering”. Journal of the Science and direct. 104 (2013) 718 – 727.

5.      Ali M., Fazil T. Najafi. “A cost effective methodology for pedestrian road crossing for developing countries”. American Society for Engineering Education, Paper ID #7673. (2013)

6.     R., Chandra S. “Development of level of service criteria for pedestrians’. Journal of Indian Roads Congress. (2014) Vol. 75-1 paper no.-611

7.     Nazir M, Razi K., Hossain QS., Khulna SK. “Pedestrian flow characteristics at walkways in Rajshahi metropolitan city of Bangladesh”. International Conference on Civil Engineering for Sustainable Development, (2014) ISBN: 978-984-33-6373-2 (CD-ROM).

8.     Singh RR, Er. Gurdeep Singh. “Study on Pedestrian and slow moving traffic”. International Journal of Research in Engineering and Technology ISSN: 2319-1163 | ISSN: 2321-7308 Volume: 03 Issue: 05 | May-2014

9.     Landis, Bruce, et al. “Modeling the Roadside Walking Environment: A Pedestrian Level of Service”, Transportation Research Board 1773, TRB, National Research Council, Washington DC, 2001.

10.   Highway Capacity Manual, Transportation Research Board, TRB, National Research Council, Washington, D.C. (2010)

11.   Highway Capacity Manual, Transportation Research Board, TRB, National Research Council, Washington, D.C. (2000)

12.   Indian Road Congress Guidelines for Pedestrian Facilities, IRC: 103-1998, New Delhi.

13.   Indian Road Congress Guidelines for capacity of urban roads in plan areas, IRC: 106-1990, New Delhi.

 

 

 

 

 

 

Received on 07.12.2015                             Accepted on 25.12.2015        

©A&V Publications all right reserved

Research J. Engineering and Tech. 7(1): Jan. -Mar., 2016 page 11-14

DOI: 10.5958/2321-581X.2016.00003.9