a meaningful assessment process for wayfinding path ...

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A MEANINGFUL ASSESSMENT PROCESS FOR WAYFINDING PATH SHORELINES Abstract Shorelines are required to define “paths” for wayfinding and orientation. The shoreline may comprise a raised border, wall or balustrade or a contrasting textural surface that can be detected by pedestrians who are vision impaired. Research into tactile ground surface indicators shows that texture on its own cannot define detectability. Surfaces with a typical “blister” pattern established a surface profile that corresponded with the definition of “macro-texture” in road pavement assessment. It is argued that the assessment of the detectability of a surface is both subjective and objective. A “mixed-method” process is developed where a measure of “macro-texture” associated with an internationally accepted TGSI profile together with other profiles could be compared with other pavement surfaces. Static and dynamic surface profilers able to capture a measurable 3D view of the surfaces are studied. The possibility of adopting an ISO Test Method is investigated. From this a simple “mixed method” assessment process is developed from a case study. A measure known as the textural ratio based on detectability is presented for shorelines.

1.0 Introduction 1.1

Overview

The assessment of wayfinding pathway shorelines needs to reflect the real world and the needs of the user (Cheadle, 2007). This article is limited to the user with a vision impairment where wayfinding may rely on detection via the use of a cane, underfoot or a guide dog. The wayfinding strategy of shorelining is described by the Blind Citizens Australia (BAA) as; “Shorelining is a strategy adopted by white cane users; it involves the use of following contours of structures in the built environment, for example a wall, footpath edge or a trail of directional TGSIs. Shorelining assists in negotiating a clear, logical path of travel.” Section 6.2, p.7 (BCA, 2011)

This article is concerned with horizontal shorelines that define the edge of the wayfinding path. Seeing tactile surface ground indicators are now used internationally (Dowson, 2003), texture1 appears to be the surface property of materials that are used to define the path and the shoreline for the orientation and wayfinding task. The challenge is developing a measurement and assessment system that combines the physical structure or texture of the material2 (objective measure) and the perceptual detection skills of the user (subjective measure). Lamb (1983) describes the forerunner of such a system as a psychophysical experiment. Bentzen et al (1996) “built” the real world into an experimental approach they used to measure the detectability of various materials and surface profiles. MacLennan et al (2011) show the value of a real world research method as opposed to an experimental method concerned with measuring the detectability of TGSI’s taking into account visual 1

Texture on its own does not define “detectability” (Lamb, 1983 and Bentzen at al, 1996) Actual surface texture as defined, described and analysed in Song and Vorburger, National Institute of Standards and Technology. 2

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ME 064 ham 3 contrast and underfoot detection in the context of actual outdoor installations. Stahl et al (2010) addressed the challenge using a mixed methods research design method in measuring the detectability of TSGI’s in the external environment which included a measure of texture depth. This study shows the importance of “triangulating”3 any quantitative output with the equivalent subjective output (Lamb, 1983; Zao et al, 2000; and Bergmann-Tiest, 2010).

1.2

The User Perspective

The importance of “visual contrast” is accepted and the requirements set down in AS1428.2: 2009 should be utilised for shorelines. We are therefore concerned with both underfoot and cane detection. These two forms of detection need to be viewed together in terms of reliability (Bentzen et al, 1994; Dowson, 2003; O’Leary et al, 1995; and Department of Main Roads, 2008). This need is based on the uncertainty of the user in the use of the cane. Zuo et al (2000) summarise the place of perception in detecting materials in the conclusion to their article as; “Human perception to materials should be investigated systematically in a holistic environment, which would be an important aid for materials selection in product design. 2) Texture and texture perception or perceived texture are two different concepts, the former is objective, and the latter is subjective. For investigating the correlation between them, the dimensions both for objective texture identification and for subjective texture description need to be explored in parallel. 3) Subjective texture description of materials are to be classified into four dimensions: geometrical dimension, physical-chemical dimension, emotional dimension, and associative dimension. 4) Under different conditions, texture lexicons within four dimensions are slightly different in the number of lexicons, and responsive sensitiveness. 5) In the material texture perception by touch, vision can increase the response to geometrical configuration, and enrich, strengthen the emotional feelings. Blindfold can increase the responsive sensitiveness to some physical-chemical characteristics, particularly warm – cold, moist – dry, and hard – soft. “

Zuo et al (2000) clearly demonstrate that detection of different surfaces needs to be done systematically. The sense of touch, either underfoot or transmitted to the hand via a long cane is considered to be a reliable perception of a material’s shape (including surface texture). We need to be careful according to Nakatani et al (2010) as they demonstrate how surface texture can actually bias this perception with texture depths ≤1mm when the adjoining surface is similar. It is interesting to note that the surfaces shown in Figure 1 below were found by Peck and Bentzen to be undetectable when compared with an adjacent flat surface. The reason could be an extension of the finding of Nakatani et al (2010). Figure 1 – Linear flat-topped paving surface patterns

Stahl et al (2010) show that the structure of a surface of a wayfinding path does not have any impact on detecting a comparison between two surfaces, especially when one comprises a guidance path. Although their study refers mainly to guidance path systems in association with TGSI warning surfaces it could be extended to the likelihood of increased detectability when the user is comparing the surface textures of the path and the shoreline. The objective and subjective measures need to be triangulated in strict

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Making a direct comparison between quantitative and subjective output which is described in Yin (2009), Hales (2010) and Amaratunga et al (2002).

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ME 064 ham 3 accordance with any mixed methods process (Stahl et al, 2010). Such an approach would also satisfy the “parallel” measurement requirements of Zuo et al (2010). Article 20 of the United Nations Convention on the Rights of Persons with Disabilities (UNCRPD) as referenced in Section 3 of BCA (2011) refers to the importance of training in the use of the cane and the people’s access thereto. The white cane is a tool used by a person who is blind or vision impaired to navigate their environment safely. Section 7.3 of BCA (2011) stresses the importance of linking cane skills with orientation and mobility. Where the cane technique is inappropriate for the detection of the shoreline then underfoot reinforcement will be required. Cook and Polger (2008) besides demonstrating that the traditional long white cane is sufficient for orientation and wayfinding point out that; “The shaft and tip of the cane work together to sense and then relay the information to the users hand via the grip. The tip (especially a metal tip used on a hard surface such as concrete) is a major source of high frequency auditory input used by pedestrian who are blind to interface with the surfaces they walk on. There often be a change in pitch between surface materials. In the design of canes a careful balance is required between rigidity to resist unnecessary bending and flexibility which is required to transmit the auditory and tactile sense of surface texture”. Chapter 8, p.173, Essentials of assistive technologies Cook, AM, and Polger JM, (2008)

The design of the cane is relevant especially in transmitting auditory and tactile vibrational information to the user’s hand and brain. The degree and quality of this transfer of information besides relating to training and cane design relates to the textural characteristics of the path and the cane technique; “A change in surface texture or density may be picked up by the cane tip and transmitted up the shaft to the hand. This may be accompanied by a corresponding change in sound. As a result a light tapping of the cane may be useful when attempting to identify the point at which the change occurs……Sliding the cane tip along the surface to identify textural changes or to detect an edge formed by the two surfaces may be very effective” Page 12 (Lagrow, 2010)

In addition to Lagrow (2010) change in surface textures where the texture profile is similar to those shown in Figure 1 may not be detected by a cane with a curved “soft” ball tip (width ≥25mm)4. Cane design and the constant touch technique (see Figure 2) were shown by Kim et al (2009) to have a direct impact on the frequency of detection. The inclusion of underfoot detection in any user based study can therefore place the variability of outcomes in context and should be included (see Department of Main Roads, Queensland Report, 2008).

Figure 2: Illustration of the Constant Touch Technique and Sweep Dimensions shown for the 90th percentile male on an external pathway > 2m wide.

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“Blindfold” study using different cane tips with standard “marshmallow” shape carried out by author on 23rd April 2015 on external paths around the University of NSW Mid Campus on walking surfaces of varying textures. Constant touch cane technique was used by the author under expert supervision for technique compliance.

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1.3

Texture

Song and Vorburger (1990) define surface texture as; “…the fine irregularities (peaks and valleys) produced on a surface by the forming process” (p.334, Song and Vorburger, Surface Texture) The peaks and valleys are also known as the surface profile. Ye et al (2009) argue that the goal of texture measurement must include the elements required for tactile perception such as vibration sensing. Mixed methods approaches utilise a qualitative approach (MacLennan and Ormerod, 2011; O’Leary et al, 1995; and Bentzen et al, 1994) where various degrees of detectability are established for various materials. There are three types of texture;   

Micro-texture Macro-texture Mega-texture

Considering the distance between the peaks and the valleys as a measure of depth we find that the most appropriate texture profile for the surfaces associated with wayfinding paths are those associated with paving materials or profile shapes that resemble those of tactile ground surface indicators which are detectable by the pedestrian within the range of “depths” associated with “macrotexture” where the range is from 0.5mm to 50mm (Flintsch et al, 2003).

Figure 3 – Surface Profile output from the Texture Meter 2 Walking Profilometer Manufactured by WDM Limited.

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Figure 4 – Tactile Ground Surface Indicator Surface / Asphalt Pavement

The objective of the paper is therefore to develop an objective method for the measurement of the surface texture of typical pathway and shoreline materials (e.g. terra cotta slabs and asphalt pavements of the type shown in Figure 4). Following an extensive search of international standards on tactile and non-tactile methods of measuring surface texture of “pavements” where macrotexture was representative of the type of profile, ISO 13473-1: 2004 was selected as being the most appropriate standard using non tactile measurement methods. The instruments referred to were varying forms of profilometers5 suitable for dynamic (i.e. laser scanning from a device mounted on a moving vehicle) or static scanning using a device in a stationery position to “map” a section of surface6 (e.g. 700mmX700mm) in three dimensions such as shown diagrammatically in . Two surface profilometers (Walking Profilometer “TM2”7 – WDM Ltd for the dynamic scanning method and “Optimap”8 by Rhopoint for the static method) were assessed for suitability. The reference surface was taken as being that of a “warning” tactile ground surface indicator such as shown in Figure 4 above. The output of the TM2 walking profilometer is shown in the “red box” as the profile and mean profile depth. This was found to be the most appropriate measure for macrotexture5 and for triangulation with the categorical data scales developed from subjective detectability studies (Bentzen et al, 1994; O’Leary et al, 1995; Parkin and Smithies, 2012; MacLennan and Ormerod, 2011 and Stahl et al, 2010). The triangulation was intended to demonstrate that the calculation of the textural contrast between the shoreline and path materials was meaningful above a threshold value developed from the detectability studies. This was the basis of this research study.

Figure 5 – Diagrammatic Illustration of 3D Surface Profile and Texture Depth (Source: ISO 13473-1: 2004, Figure A.3, page 12)

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Flintsch et al (2003); McRobbie et al (2013); Nugent, (2008); and Binns, (2010). Hanson and Prowell (2008). 7 WDM Limited, (2013), TM2 – Texture Meter, User Manual, Version 1.3. 6

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Rhopoint, (2015) Portable objective surface quality measurement, Informative Brochure on “OPTIMAP” (PSD), Rhopoint Instruments, Visual Technologies viewed on 13 April 2015 at: http://www.rhopointinstruments.com/images/pdfs/optimap%20presentation.pdf

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2.

Method

2.1

Research question dictates the research method

Bentzen et al (1994), O’Leary et al (1995) and summarised by Dowson (2003) showed that the objective comparison of surface textures did not necessarily reflect detectability9. This is one of the underlying reasons for the development of the profile for the TGSI such as shown in Figure 4. The research question that was identified and used to develop the “Method” shown in Figure 6 is; Is an increase in textural contrast between two surfaces (path and shorelines) automatically reflected in the ease of detecting the presence of those two surfaces?

Figure 6 – Flow Chart of Research Method

Detectability has been subjectively measured in the past by survey methods which are qualitative (Bentzen et al, 1994; O’Leary et al, 1995; Parkin and Smithies, 2012; and MacLennan and Ormerod, 2011). Stahl et al (2010) used a mixed method approach and this was confirmed as being the most suitable for this project based on additional evidence provided by Amaratunga et al (2002).

2.2

Research Method (Box 3 to Box 8 - Figure 6)

2.2.1 Box 3- Method for objective measure A simple objective measure was required for texture. The materials used in the construction of wayfinding paths and shorelines vary. External wayfinding paths are normally those which would be defined by shorelines located in the same plane as the surface of the path whereas it is more likely that other elements such as walls located in the vertical plane would be used internally. A simple manual method was trialled using a contour gauge as shown in Figure 7 below. In accordance with

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According to Nakatani, M., Howe, R.B., and Tachi, S., (2010), Surface texture can bias tactile form perception. Exp. Brain Res. Springer, DOI 10.1007/s00221-010-2464-3, surface texture does impact the perception of “form”. Form here could be seen as being synonymous with profile.

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Figure 7 – The Manual Contour Gauge

“mixed method” practice (Amaratunga et al, 2002) and as further developed in the Case Study method (Yin, 2009) the Author, as an expert immersed in the study, trialled the contour gauge over a range of surfaces in external paths on a large University Campus in Sydney, Australia. The device was suitable for TGSI profiles but was impractical for others such as exposed aggregate concrete and asphalt. Its use would lead to inaccuracies in the comparison of the profiles of an exposed aggregate path and a shoreline with a profile similar to that of a TGSI. The detectability of a shoreline decreases when the “textural difference” between it and the path decreases (Bentzen et al, 1994 and O’Leary et al, 1995). MacLennan also found this in his study of TGSI’s and external stairs (MacLennan and Ormerod, 2011). Other more sophisticated contact methods were trialled using devices with a stylus type measuring device. These devices are more suited to the measurement of surface roughness in microtexture and were used in conjunction with other devices where the roughness measure dictated the slip resistance of a surface or material10. Non-contact canning methods were examined11 and ISO 13473-1: 2004 adopted because of its extensive use in the characterisation of pavement texture as demonstrated by Bitelli et al (2012). This standard was therefore adopted as the reference standard on which a standardised test method would be based seeing that the device needed to be one that was portable, manageable in terms of its mass, and one that had already been recommended by Australian Roads12. A similar apparatus, “Optimap”8 that could be used for the static test was found and tested on sample paving. The associated User Manual for “Optimap” and some test measurements taken on pavements confirmed that the device was suitable for use as a static scanning device in a similar manner as the CT Meter (Flintsch et al, 2003).

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Shaw, R., (2007), An examination of novel roughness parameters to be used in conjunction with the HSE slips assessment tool (SAT), Health and Safety Laboratory, for Health and Safety Executive, Research Report RR549 and MacLennan, HA, and Ormerod, MG, (2011), Tactile Ground Surface Indicators for outdoor steps – aid or hazard? International Conference on Stairway Usability and Safety SURFACE Inclusive Design Research Centre, University of Salford. 11

Flintsch G.W., de Leon, E., McGhee, K.K., and Al-Gadi, I.L., (2003) Pavement Surface Macrotexture Measurement and Applications, Transportation Research Record 1860, Paper No. 03-3436; Song, J.F., and Vorburger, T.V., (1990), Surface Texture, National Institute of Standards and Technology; and Vilaca, JL, Fonseca, JC, Pinho, ACM, and Freitas, E, (2010), 3D surface profile equipment for the characterization of pavement texture, Mechatronics, Vol. 20, pp.674-685.

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The Texture Meter TM2 as manufactured by WDM Limited mentioned under the definition for portable profilometers in Austroads Test Method AG:AM/T013, 2011. See also7.

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Figure 8 – Static Laser Scanning Device (Optimap) – Fully Portable

Figure 9 – TM2 Walking Profilometer – WDM Ltd

Figure 8 and Figure 9 show the two devices that were used to confirm their suitability for the derivation of the objective measure in that they are capable of measuring the MPD of a path and shoreline surfaces. Typical output values are shown for the TM2 test in Figure 4 so that it is possible to calculate the textural contrast (TC) for the path.

2.2.2 Box 4 – Detectability and Cane Sweeping Technique The method here comprised a field study by the author as an expert immersed in the study. Seeing it involved cane sweeping he was guided by an accredited wayfinding expert. The cane selected was the standard long white cane as being representative of the type used by most pedestrians with reduced or no vision (BCA, 2011; Kim et al, 2009; Rodgers and Emerson, 2005; and Roentgen et al, 2008). The continuous contact sweeping technique as shown in Figure 2 was utilised and a mushroom tip was employed. Textural differences were detected but the findings of Bentzen et al (1994) and O’Leary et al (1995) showed that underfoot detection was required as well to increase reliability. Results are provided here as Box 5 required confirmation of the additional detection method.

2.2.3 Box 5 – Investigate seminal detectability case studies The two studies selected (Bentzen et al, 1994 and O’Leary et al, 1995) pertained to the detectability of various TGSI profiles where one of the outputs was expressed as a percentile of acceptance for both cane sweeping and underfoot detection. Generic MPD data for various materials (e.g. asphalt/ TGSI; exposed aggregate concrete/TGSI and smooth concrete/TGSI) could then be triangulated with the detectability data for each of the seminal studies for the 90th percentile acceptance rate shown for the sample in each study.

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2.2.4 Box 6 – Test the output from Box 5 by calculating the textural contrast. For the purposes of this paper the textural contrast between the shoreline and the wayfinding path is: 𝑻𝑪 =

𝑴𝑷𝑫 𝒐𝒓 𝑴𝑻𝑫 𝑺𝒉𝒐𝒓𝒆𝒍𝒊𝒏𝒆 𝑴𝑷𝑫 𝒐𝒓 𝑴𝑻𝑫 𝒑𝒂𝒕𝒉

Where: TC=Textural Contrast; MPD=Mean Profile Depth; and MTD=Mean texture depth or estimated texture depth

Figure 10 – Example of Textural Contrast (TC=3.26) Source: China and James (2012), Figure 4, p. 179.

From the generic MPD values the TC was to be plotted for the data from each of the studies (Bentzen et al, 1994 and O’Leary et al, 1995). This provides a range of TC values from which a threshold TC could be established for the 90th percentile level of successful detectability for a shoreline or warning surface (e.g. exposed aggregate footpath and warning type TGSI). The approach is seen as being as robust as that of Stahl et al (2010) which quantified detectability.

2.2.5 Box 7 – Establish a textural contrast level. The detectability studies (Bentzen et al, 1994 and O’Leary et al, 1995) were concerned with finding a tactile surface that would be placed on footpaths, detected underfoot, warning of an impending hazard. The blister pattern TGSI was similar to that shown in Figure 4. The textural contrast was to be determined for a series of surface combinations using the TGSI profile as a base reference. This was compared with exposed aggregate profiles utilising data from road pavement studies (China and James, 2012; Hanson and Prowell, 2004; Akkari, A, and Izevbekhai, B, 2012; and Kim et al, 2013) as well as project trials with the TM2 and Optimap profilers. Figure 10 shows an example of the TC between a relatively smooth surface and a “exposed aggregate” surface. There was no detectability measure associated with this TC. A triangulation study was therefore required which did not utilise the TGSI profile as a base reference. A study carried by Queensland Main Roads (2008) entitled “Trial and Evaluation of Tactile Pavement Markings to Assist Vision Impaired Pedestrians” was selected to provide the detectability data for shorelines to pedestrian crossings. Data from pavement studies was to be used as a basis to estimate texture depths of the road pavement and the tactile shorelines. The tactile shorelines were white (with the appropriate reflectance value) and the aggregate mix and binding agent (epoxy) were described. Various profiles were trialled in the study including one with a 5mm high edge profile which proved to be the specimen with the highest rate of detectability. Allowance was to be made in the estimation of the texture depth for this edge effect utilising the same approach as shown in Figure 12 shown in Section 4.1. The TC was then to be calculated for each specimen and regressed against the rate of detection by the study sample of pedestrians with visual impairments.

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2.2.6 Box 8 – Modify ISO 13473-1; 2004 to suit and produce Prescriptive Matrix for candidate surfaces. The outline for the modification of ISO 13473-1 is proposed based for both static and dynamic profilometers. The procedure needed to be kept as close to the road testing sequence as possible. Special note was taken of the procedure set out in Austroads Test Method AG:AM/T013, 2011. This approach takes into account experience already gained in the measurement and characterisation of pavement surface textures. The results outline the proposed modifications to ISO 13473-1; 2004. A matrix of suitable candidate surface combinations is also proposed using data from the entire project study.

3. 3.1

RESULTS The objective measure – static and dynamic tests

The results from completion of Box 3 of the research method are: (a)

Dynamic – TM2 profiler

A test run was carried out in association with WDM Limited in the United Kingdom in May 2015. The test site is shown in Figure 4 and comprises a TGSI installation at the entry to a pedestrian Crossing with a relatively smooth asphalt footpath. The profile was measure in the transverse direction to the direction of walking and the sampling was continuous. This satisfies the 1mm interval of measurement (Flintsch et al, 2003). The results are a MPD of 3.09 for the TGSI and 0.4mm for the asphalt. A screen shot in Figure 3 confirms these calculations. The resultant Textural Contrast (TC) is 3.09/0.4 which is 7.7. (b)

Static – Optimap

Two surfaces were measured. The first was of an asphalt footpath surface where the maximum depth was recorded as 0.195mm. The second was of a concrete paving slab with a maximum depth of 0.147mm. An example of a 3D view of the asphalt surface is provided in Figure 8. The MPD can be calculated by autoscaling from the data, transferring the latter to a spread sheet and completing the calculation on an ®Excel Spread Sheet (Nigel Rose, 2015)13. The TC would then be calculated from the relevant MPD’s.

3.2

The site test – cane sweeping and detectability – Box 4

Detectability has been subjectively measured in the past by survey methods (Bentzen et al, 1994 and O’Leary et al, 1995). Stahl et al (2010) used a mixed method approach and scaled detectability. The bulk of the detectability research was associated with TGSI profiles. Following a study of “canes” it was decided to conduct a qualitative “field” test of cane vibration frequencies resulting from various surface profiles. The cane used was the long white cane with a “mushroom” plastic foot that “rolled” across the surface being “swept”. The profiles noted in Figure 1 comprised linear flat topped structures and were represented by many of the surfaces found during the test conducted on the University Campus. Multiple grooved structures comprising stainless steel grates did not increase the frequency of vibration in the cane when compared with an adjacent polished concrete finish. There was a distinct difference in the noise transmitted. The grooves were some 10mm in width and 10mm deep. The diameter of the tip of the can was > 25mm so that the cane passed over the groove (the surface of the “crown” of each groove was also quite shiny). The steel surface did not register as a shoreline. 13

As for the CT Meter scanning process (Hanson and Prowell, 2004)

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ME 064 ham 3 Shoreline planting did register because of a change in surface hardness, uneven soil profile and the stems of plants. This constituted a detectable shoreline texture. Another shoreline tested comprised rough-sawn timber sleeper where the edge of the sleeper was some 5mm above the surface of the path. The author estimates that the profile depth was greater than 8mm (contour gauge) with a marked surface texture. This shoreline was easily detectable. Also there was a marked change in the noise associated with the sweeping cane on the path and shoreline surface. The test confirmed the findings of Stahl et al (2010) to a certain extent but not across the entire range of possible texture profiles especially when associated with materials of varying resonance e.g. timber. A further review of Bentzen et al (1994) showed that detectability was impacted to a certain degree by an association between the walking surface materials and the TGSI surface profile. Further investigation was therefore required to determine the significance of this association.

3.3

Case Study Investigation

A comparison of the surfaces in Bentzen et al (1994) reveals the following: BASE SURFACE TGSI

Brushed Concrete

Wood

Coarse Aggregate

(3.09)*

(0.5)*

(0.4)*

(.85)*

No times detected

%age detected

No times detected

%age detected

No times detected

%age detected

A

24

100

24

100

21

87.5

B

24

100

24

100

21

87.5

C

24

100

24

100

22

91.7

D

24

100

24

100

24

100

E

24

100

24

100

23

95.8

F

24

100

24

100

22

91.7

G

24

100

23

95.8

24

100

H

24

100

23

95.8

23

95.8

I

24

100

24

100

21

87.5

J

24

100

24

100

16

66.7

Textural contrast

6.18

7.75

3.64

*Estimate Profile Depths with TGSI imported from Section 3.1. Table 1 – Estimates of Textural Contrast from Detectability Data from Bentzen et al (1994)

The rate of detectability is > 95% in all cases for wood and brushed concrete surfaces. As the texture depth increases the TC decreases (pale blue column). This shows qualitatively that there could be a detectability threshold that is greater than 3.5 but further clarification is required where the test site does not include TGSI units as the shorelines (warning pedestrians about the edge of the wayfinding 11

ME 064 ham 3 path). The study selected is of a pedestrian crossing carried out by the Queensland Department of Main Roads (2006).

3.4

Triangulation of Results from Section 3.3

A diagrammatic representation of the Test Site is shown below in Figure 11. The sample size and test procedure is fully described in the Stage One Report. The participant pedestrians were mainly vision impaired including a large percentage with no vision at all. There were a total of 9 treatments for the dotted shorelines which comprised many different profiles and shapes with varying texture depths. These were estimated from the description of each treatment in the QMR Report (2006).

Figure 11 – Diagrammatic View of Test Site Pedestrian Crossing

Table 2 - Reproduction of Table 3.1 – Trial and Evaluation of Tactile Pavement Markings to Assist Vision-Impaired Pedestrians (VIP), Stage 1 Report, Department of Main Roads, Queensland (2006).

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ME 064 ham 3 Table 3 – Estimated Texture Depth for each Treatment Treatment Estimated Number Texture Depth (mm) 1 1.5 2 2 3 2 4 2.3 5 2.5 6 2.6 7 2.2 8 3 9 1 Table 4 – Table showing significance of Texture to Rate of Detection Underfoot detection and visual detection were included as the luminance contrast of the treatments with the road pavement exceeded 0.3. Underfoot detection was added as not all visually impaired pedestrians would be using canes. They could be relying on guide dogs. The detection scores are shown in Table 2.

Table 3 shows the estimated texture depth for each treatment and Table 4 shows the results of a regression analysis of texture depth vs. detection score. There is a significant relationship between the two. The Report concludes; “The ability to be able to detect the line using the feet may not be the primary mode of detection and guidance for all vision impaired persons but may provide reassurance. Treatments with an edge height of at least 5mm performed the best in this regard, and while all but #1 and #9 were acceptable the trial distinguished #5, #6 and #8 above the others. In terms of acceptability, to cane users, treatments #1, #3 & #9 are all unacceptable “ Page 9, Department of Main Roads, Queensland, (2006), Trial and Evaluation of Tactile Pavement Markings to Assist VisionImpaired Pedestrians (VIP), Stage 1 Report, Queensland Government.

It is interesting to note that the participants of the study (QMR, 2006) designated treatments 5, 6 and 8 as the most detectable and 1, 3 and 9 as the worst. This corresponds with the TC and the relationship has already been shown as significant at (p