Motivations and background

CHAPTER 1 INTRODUCTION

In this chapter, I first illustrate the importance of building pedestrian-friendly environment and the issues existing in the practice. After it, the objectives are set. Then, I present the research framework to illustrate the relationship among the study subjects and the approaches I used.

1.1 Motivations and background

Reports have shown that transportation and land use change contribute a total of nearly 31.7% of the greenhouse gas emissions. These trends are increasingly quite dramatically, especially in the countries with emerging and newly developed economies such as mainland China, India and Brazil (USEPA, 2009; WRI, 2005). Walkable environment is regarded as a solution to this problem.

Mobility and accessibility are the two key concepts when planning transportation system and land use. For a walkable environment, the estimate of walking distance serves as an accessibility indicator for evaluating whether people decide to walk or not to a planned facility. This concept was launched by Howard (1902) who used an acceptable walking distance to determinate a reasonable town size. This concept extends to urban planning.

Perry (1929) introduced the “neighborhood unit” idea (see Figure 1), with emphasis on walking accessibility, and with residences arranged around a service center within an acceptable distance.

Figure 1 The concept of the traditional walking distance.

To-date, new planning paradigms, e.g., Transit Oriented Development (TOD), New Urbanism, Compact City, continue to apply walking distance not only to create a

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pedestrian-friendly environment but also to reduce greenhouse gas emissions by encouraging transit ridership and walking frequency (Banai, 1998; Calthorpe, 1993;

Cervero and Kockelman, 1997; Cervero et al., 2009; WRI, 2005). Its application is also found in the retailing theory where it is used to estimate the number of walk-in customers and in location-allocation modeling studies where it serves as a parameter for designing the maximal covering model (Brown, 1996; Hsu and Chen, 1994; Owen and Daskin, 1998).

Although the method has been and still is applied in many fields, its measure does not reflect variability. In fact, there are various measures recorded in the literature, but few studies that explore their variation. Howard (1902) initially set it as a half mile; Perry (1929) used a quarter mile (5-minute walk) as the radius of a neighborhood unit; and in Sweden it was set as a range of about 300~500m (Lynch and Hack, 1984). The characteristics of the pedestrian, e.g., trip purpose, gender, and age, and urban context may alter the acceptable distances (Clifton and Krizek, 2004). For example, Pushkarev and Zupan(1975) compared the cumulative distribution of walking distances for a trip at two Manhattan buildings. They found that trips to eat had the shortest walking distance and that shopping trips had the longest ones among five purposes (eat, work, pleasure, business and shop). However, to-date few studies have explored the variation in walking distance and its implication for pedestrians. A useful method to express the variability of walking distance is the statistical distribution. As mentioned earlier, Pushkarev and Zupan(1975) applied this method to analyze walking distances. Seneviratne (1985) observed the distribution of walking distances by conducting a survey in the central business district of Calgary, Canada. It is worth noting that Seneviratne (1985) derived the critical distance of 243m (796 ft), at the maximum rate of change of the distribution function as the more reasonable estimate for the average walking distance of 250m (819 ft). This advanced application of statistical frequency for estimating walking distance inspired our later analysis.

However, contrary to the discussion on the variation in walking distance, there is much less concern regarding the variability across pedestrian environments. People generally agree that the higher the pedestrian environment quality (PEQ) the farther, within reason, they are willing to walk, and this finding is backed up in the literature (Untermann, 1984; Zacharias, 2001). Nevertheless, few studies have explored this issue with systematic analysis. Gehl (2001) and Untermann (1984) investigated the change of frequency based on the improvement of PEQ, but they did not include any change in walking distance. Lövemark (1972) recognized the effects of PEQ on willingness to walk and claims that a pleasant

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pedestrian environment encourages an up to 30 percent greater walking distance. To date his study is the one closest to the issue addressed here, but it still does not show any details.

In urban pedestrian environment, PEQ is associated with level of street amenities (SA), e.g., right of way, lighting, planting, pavement, street furniture, retailing, and fountains (Booth, 1983; Mitra-Sarka, 1994). Since better street space would encourage people to ride transit and to walk more frequently (or for longer), street improvement projects are broadly proposed. This could include enhancing street lighting, increasing the greenbelt area, and so forth. Even their benefits have been demonstrated in many studies with reference to the appreciation of real estate value (Cheshire and Sheppard, 1995; Correll, Lillydahl and Singell, 1978); planners have recently focused on the extent to which street improvement projects have raised WTW. However, similarly, few have conducted systematic investigations to demonstrate relationship between WTW and SA. The necessary requirements are a suitable measure of WTW, an analytical model, and adequate empirical data. Street improvement studies usually evaluate the effects of a single street amenity, such as lighting (Willis, Powe, and Garrod, 2005). They tend to either focus on economic valuation without link to users’ behavioral intentions, or perform qualitative analysis, without specifically suggesting a useful planning tool.

Additionally, arrangement of SA also affects walking mobility. This can be observed in a corridor when mobility difference is very high. A substantial difference in mobility would cause uneven pedestrian flow, particularly when it is due to elderly pedestrians. The rapidly aging population, especially in the developed countries has changed the demographic profile in Taiwan, and will continue to have a drastic impact on transportation planning in the coming decade (Meyer and Miller, 2001). It will result in temporary and local congestions in high density pedestrian corridors. Consequently, commuters must spend more travel time in these corridors to bypass slow pedestrians and to avoid a collision. This type of congestion tends to happen around elderly pedestrians walking very slowly. Figure 2 shows a photograph of a local congestion being created on a street in Taiwan.

However, designing SA to raise corridor performance is rarely discussed. Unless a pedestrian corridor is a new construction, the space available for widening the corridor is extremely limited. In that situation, the improvement program should focus on space design.

But, when planning a pedestrian corridor, planners must pay close attention to capacity design, because misallocation tends to be the major source of pedestrian congestion in high density areas (Pushkare and Zupan, 1975). Fruin(1971) characterized the quality of the

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pedestrian flow at various levels of maximum capacity as level-of-service (LOS) to aid capacity design. This method is still widely used today, and its assumptions allow us to explore any new issues that we have to face, now or in the future. It assumes that a pedestrian flow is an even or homogenous stream, but in reality it is usually uneven.

Pushkarev and Zupan found that a platoon of pedestrians causes an uneven flow, and they improved the traditional LOS method by taking the platoon effect into account.

Figure 2 A real case observed in Hsinchu City where an elderly man walks very slowly, and some of the surrounding younger pedestrians try to bypass while keeping a buffer zone in order to avoid collision. Some of them slowed down or stopped to give him the

right of way.

Mobility differences are also dangerous for the safety of the elderly on the streets. Although my observation showed that the young tend to give the right of way to the elderly, the potential risk for a collision to occur remains. Both the elderly and the younger generations require space arrangement not only to prevent possible conflict between the 2 groups, but also to maintain operation efficiency. This problem intensifies in and around downtown healthcare institutions. Although there are provisions for people with disability, many of the elderly I mentioned here can walk freely, but do so at low speed.

The reports of successful real-world cases can be of use in corridor design, but only a few of them performed systematic analyses which could benefit planners to rationally and broadly

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assess their design (Marcus and Francis, 1998). Fortunately, Helbing and his partners built agent-based models (ABMs) to study pedestrians. They found that geometric form and design elements can stabilize the flow pattern and make them more fluid (Helbing et al., 2001; Helbing et al., 2000). However, their discussions don’t cover the issue addressed in this thesis.