The Third Structure of Pedestrian LOS: Quantitative and Qualitative

A mathematical model was proposed by Landis et. al (2001) based on five variables: (1) lateral separation of pedestrians from motor vehicle traffic, (2) presence of physical barriers and buffers, (3) outside lane traffic volume, (4) motor vehicle speed, and (5) vehicle mix. The model was developed through a multi variable regression analysis:

Ped LOS = - 1.2021 ln (Wol+ Wl + fp × %OSP + fb × Wb + fsw × Ws) + 0.253 ln (Vol15/L) + 0.0005 SPD² + 5.3876

19 Where:

Wol = Width of outside lane (feet)

Wl = Width of shoulder or bike lane (feet) fp = On-street parking effect coefficient (=0.20)

%OSP = Percent of segment with on-street parking

fb = Buffer barrier coefficient (=5.37 for trees spaced 20 feet on center) Wb = Buffer width (distance between edge of pavement and sidewalk, feet) fsw = Sidewalk presence coefficient = 6 – 0.3Ws

Ws = Width of sidewalk (feet)

Vol15 = average traffic during a fifteen (15) minute period L = total number of (through) lanes (for road or street) SPD = Average running speed of motor vehicle traffic (mi/hr)

Table 2-10: Pedestrian Level of Service Categories (Landis, 2001) Level of Service Model Score Description

A ≤1.5 Very pleasant

B > 1.5 and ≤ 2.5 Comfortable

C > 2.5 and ≤ 3.5 Acceptable

D > 3.5 and ≤ 4.5 Uncomfortable

E > 4.5 and ≤ 5.5 Unpleasant

F > 5.5 Very unpleasant

LOS A was considered the safest and comfortable (or least hazardous) and LOS F was considered the least safe and comfortable (or most hazardous) (refer to Table 2-10). The model seems to be a convenient and useful tool for evaluating various street side walking segments but it has following major limitations. The model does not predict LOS as a measure of ease of pedestrian movement on walkway segments. It rather predicts a motor vehicle exposure rating from a pedestrian perspective.

Muraleetharan (2005) proposed a conjoint analysis for the evaluation of pedestrian LOS. Factors for assessing the pedestrian LOS on sidewalks include: (1) lateral separation of the pedestrians, (2) width of the sidewalks, (3) obstructions, (4)

20 pedestrian flow rate and (5) number of the bicycle passing and opposing events. Total utility from the conjoint analysis represents an overall value, which specifies how much a user puts on a product or service. The maximum total utility value indicates the best case, while minimum indicates the worst case. Table 2-11 shows the attributes and level of sidewalk proposed by Muraleetharan (2005).

Table 2-11: Attributes and levels of sidewalk (Muraleetharan, 2005)

Level Attributes

Width &

Separation

Obstructions Flow Rate (ped/min/m)

Bicycle events

Level 1 More than 3m wide & excellent separation

No obstructions Less than 24 ≤ 60 events/h

Level 2 From 1.5 to 3m

& reasonable separation

From 1 to 5 obstructions per 100m

From 24 to 49 From 61 to 144 events/h

Level 3 Less than 1.5 m wide & no separation

More than 5 obstructions per 100m

More than 49 > 144 events/h

Tan (2007) developed the pedestrian LOS model by step-wise regression analyses, including (1) the bicycle flow volume, (2) the pedestrian flow volume, (3) the vehicle flow volume, (4) the driveway access frequency and (5) the distance between sidewalk and vehicle lane. He developed the following model:

PedLOS = - 1.43 + 0.006QB - 0.003QP + 0.056 QV / Wr + 11.24 (P – 1.17 P³) Where,

QB = bicycle traffic during a five-minute period QP = pedestrian traffic during a five-minute period QV = vehicle traffic during a five-minute period (pcu) P = driveway access quantity per meter

Wr = distance between sidewalk and vehicle lane (m)

21 Table 2-12 below may be used as a basis for stratifying the model’s numerical result into the rank of the pedestrian level of service when it is applied to a roadway segment.

Table 2-12: Pedestrian Level of Service Categories (Tan, 2007) Pedestrian Level of

Service

Model Score Description

A LOS < 2.0 Pleasant

B 2.0 ≤ LOS < 2.5 Reasonable

C 2.5 ≤ LOS < 3.0 Acceptable

D 3.0 ≤ LOS < 3.5 Poor

E 3.5 ≤ LOS < 4.0 Unpleasant

F LOS ≥ 4.0 Unsuitable

Hidayat (2011) proposed an alternative model for evaluating the pedestrian level of service at the sidewalk with street vendor’s activities by incorporating qualitative and quantitative variables. Along with pedestrian traffic data, regression models are estimated to find the level of service as a function of the pedestrian perceptions of comfort and problem caused by vendor activities, pedestrian volume, and the number of pedestrians who interact with street vendors. He proposed a multiple regression methods as follows:

Y = 4.774 + 0.518X1 – 0.190 X2 + 0.001X3 – 0.006X4 Where,

Y = Pedestrian LOS (score of sidewalk’s performance by pedestrian) X1 = FA-1 (Comfort, pedestrian’s perception about sidewalk comfort)

X2 = FA-3 (vendor problem, pedestrian’s perception about problem caused by street vendor)

X3 = Pedestrian volume (the number of pedestrian passing in the sidewalk per 15 minutes)

X4 = Interact with vendors (the number of pedestrian who interact with vendors per 15 minutes.

22 Table 2-13 shows the level of service categories based on the score of assessment. The range of F (LOS ≤ 2.0) to A (9.0 < LOS) can be used to assess sidewalk performance. However, this method only considers few variable and data with smaller sample size.

Table 2-13: Pedestrian Level of Service Categories (Hidayat, 2011) Pedestrian Level of Service Model Score

A 9.0 < LOS

B 7.0 < LOS ≤ 9.0

C 5.0 < LOS ≤ 7.0

D 3.0 < LOS ≤ 5.0

E 2.0 < LOS ≤ 3.0

F LOS ≤ 2.0

Over the years, PLOS models have been changed through development and application in different contexts. There have been several methods created to evaluate the quality of pedestrian LOS (Highway Capacity Manual (2000), Dixon (1996), Jaskiewicz (1999), Gallin (2001), Sarkar (2002), Asadi-Shekari (2011) and Talavera-Garcia (2015), Landis (2001), Muraleetharan (2005), Tan (2007) and Hidayat (2011).

Different researchers have developed both qualitative and quantitative methods using different attributes that they felt were important to differentiate between good and bad pedestrian environments. They consider different indicators and evaluation criteria. Therefore, there is a certain difficulty to define a standard method that can be applied everywhere because the results of these models are unsuitable for universal use. Currently, no established approach exists. Therefore, more integrated approach incorporating more walking needs is still required.

23 2.1.4 The Advantages and Disadvantages of PLOS Evaluation Structure

Based on the literature review discussed above, the following advantages and disadvantages of all types of PLOS evaluation structure are summarized in Table 2-14 as follows:

Table 2-14 Summary of Advantages and Disadvantages of PLOS Methods PLOS Evaluation

Structure

Advantages Disadvantages

First Structure (Capacity-based model)

• Selection of the indicators and weight.

• Pedestrians are equivalent to vehicles.

• Some important indicators, such as qualitative factors, and facilities, are not considered in these types of models and not investigated thoroughly.

• Not accurately describing the actual walking conditions.

• Fails to consider the quality of the human experience.

• Relatively little guidance is given in the HCM on the compilation of each factor’s LOS into a measure of overall LOS.

24 Second Structure

(Street

characteristic- based model/ Point System)

• Simple, easy to follow and easily applied.

• More accessible for non-technical staff.

• Very common.

• The system can be extended and adjusted for different contexts.

• Does not require complex data.

• Can include various factors.

• Weight of the various indicators are arbitrarily chosen.

• Strength and weight of an indicator are based on personal judgement, which increases the bias of the results.

• Very subjective and difficult to measure.

Third Structure (Regression analysis)

• Weight and strength of indicators are not on the personal decision.

• The evaluation methods are complicated and time-consuming.

• Not easy to interpret the result.

• Difficult to link the

evaluation methods to design/

decision-making process.

• Did not sufficiently consider micro level infrastructure and facility details.

• Cover only a narrow range of street conditions and may not be applicable to all situations.

25 In this study, I use the second type of evaluation structure which is a point system. The star rating system is a point system. What is the current performance and how to achieve the target to improve the management. What option can we have to change that. It is more goal oriented. It is to ease the decision for non-specialist. Easy for commoners to understand. Classification of the range. 0-20, 21-40. It is common and the most easily understandable. This is for academic rigor, but at the same time, how to present the findings easily understandable for commoners. This is for non-specialist to be able to understand or to be convinced.

This is for the ease of understanding of usual people about the criteria/classification. For example, local governors who are a non-transportation specialist. The classification of indicator values is easy. Five level is common and easy classification. There are lots of point system that are based on five level rating system.

For example, hotel rating system in tourism and airline rating system in the transport use five-star rating system. If seven level classification, it is too complicated for usual people, so, five level is enough.