Smart Growth and Urban Goods Movement (2013)

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14 C H A P T E R 4 In general, no comprehensive studies have been documented that examine the relation- ship between smart growth and urban goods movement. In fact, as Woudsma found in 2001, little research is available that addresses land-use patterns and goods movement. The most comprehensive examination identified to date is the work of NCHRP Synthesis of Highway Practice 320: Integrating Freight Facilities and Operations with Community Goals (Strauss- Wieder et al. 2003). This effort was one of the first to consider the relationship of freight movement with its surroundings, but it focused primarily on long-distance freight move- ments, as opposed to the intra-city movement of goods. It also used a more traditional land- use perspective—instead of integrating land uses, it encouraged appropriate buffers (in time and space) between freight movements and residential neighborhoods. Allen and Browne (2010) have provided a more recent evaluation of the relationship between urban form and freight transportation, but they also have focused on heavier vehicles, and intra-city goods movement is only one of their focus areas. They argue that freight movements are less tied to urban form than passenger movements for three reasons: “ . . . fewer modal options exist for freight than for passengers, the demand for freight transport is more inelastic with respect to price than for passenger journeys (and therefore less likely to alter or stop than passenger journeys when prices change), and relatively little freight is transported in residential neigh- bourhoods” (Allen and Browne 2010, p. 13). However, they do argue that settlement size, density, and mixed land uses affect freight movements since larger communities will produce greater demand and higher densities will potentially reduce distance traveled between origins and destinations. While minimal research has focused on the interaction between smart growth and urban goods movement comprehensively, quite a bit of research has been conducted that looks at the relationship between specific aspects of smart growth and urban goods movement. This review will consider five areas of existing research between smart-growth-related subfields and urban goods movement: 1. Access, parking, and loading zones 2. Road channelization, bicycle, and pedestrian facilities 3. Land-use mix 4. Logistics studies 5. Network system management These five areas describe subcategories of smart growth or smart-growth-related fields that can influence or be influenced by urban goods movement. They are not a comprehensive descrip- tion of smart growth, nor are they intended to be. We have, however, identified research in these areas that informs our evaluation and modeling. Intersection of Smart Growth and Urban Goods Movement

Intersection of Smart Growth and Urban Goods Movement 15 4.1 Access, Parking, and Loading Zones The first area that has been examined with regard to smart growth and urban goods move- ment is the impact of access, parking, and loading zones. Using focus groups of truck drivers, Pivo et al. (1997) found a need for loading zones throughout the day and for improved way- finding to, and design of, existing loading spaces. Truckers in their focus groups wanted more loading zones that are larger and have longer allowable time limits. Morris et al. (1999) identi- fied inadequate docking space and insufficient curbside parking for commercial vehicles as two of four major barriers to freight mobility consistent across sectors, as identified by logistics and transportation managers. They suggested increasing off-peak deliveries, increasing the avail- able truck parking, and providing incentives for better docking facilities as solutions to these problems. Morris and Kornhauser (2000) and Morris (2004) followed up this work by survey- ing office managers of commercial office buildings, and they confirmed their earlier findings. Morris’ 2004 work also looked at loading-dock regulations nationally and found that no recent changes have been made to regulations in the six cities studied (Atlanta, Boston, Chicago, Dallas, New York City, and Seattle) and that New York’s requirements are far smaller than those in the other cities. As illustrated by the existing research in this field, a demand for adequate loading space exists and is a significant influence on driver satisfaction. However, the available research does not identify the appropriate balance between a need for adequate parking for goods move- ment and the other uses that road space can serve. It also does not consider the impact of different regulations on mobility and goods movement. 4.2 Road Channelization, Bicycle, and Pedestrian Facilities A primary aspect of smart-growth development is design that fosters non-motorized mobility and multimodal environments. These types of designs include sidewalks along roadways, a well- connected bicycle network, and narrower streets that foster slower speeds and are perceived as more pedestrian friendly (Saelens et al. 2003; Handy 2007). Although most urban freight traffic is handled via small trucks and vans, freight vehicles typically have larger turn-radius require- ments and field-of-vision limitations, which are factors that make traversing narrower roads with varied user groups more challenging. In summarizing the findings from a series of focus groups they conducted, Pivo et al. (1997) indicated that truckers were comfortable with pedes- trians and sidewalk provision but felt challenged by the automatic right of way of pedestrians at crossings, which they felt creates sudden needs to stop. Truckers were more concerned with bicy- clists, which they felt were erratic and were not held to any operational standards. Overall, what is not clear from the existing literature is the extent to which the potential for truck/non-motorized incidents is real or perceived—that is, do places with more interaction between trucks and non- motorized modes of travel have more crashes, or are these two sets of modes simply wary of their potential for collision? To date, little research has been done that focuses on these types of street designs (including sidewalks along roadways, a well-connected bicycle network, and narrower streets) and their relationships to urban goods movement. However, a significant body of literature exists that looks at the impacts of these types of changes on the roadway environment in general. For example, Huang et al. (2002) looked at crash reductions following the installation of road diets and found some evidence of a reduction in the number of crashes. Ewing and Dumbaugh (2009) found that urban environments with narrower lanes were safer than suburban environ- ments since they better communicate appropriate travel speeds. Reynolds et al. (2009) found that bicyclists had higher crash rates in pedestrian environments and were safest on dedicated infrastructure such as bike lanes or paths. These studies show that narrower street designs that

16 Smart Growth and Urban Goods Movement incorporate bicycle infrastructure and sidewalks may slow speeds and reduce crashes. So far, research has not shown that these effects extend to freight vehicles, but there is little reason to expect otherwise. 4.3 Land-Use Mix Another key component of smart-growth development is interspersing land uses of dif- ferent types. This integrated land-use design is intended to reduce travel distances and make non-motorized and multimodal travel more attractive. To some extent, proximate residential, retail, office, and industrial spaces may also reduce goods-movement travel needs following the same principles, but that effect has not been studied. Klastorin et al. (1995) found that when firms located near denser urban areas they had increased demand and revenues and that firms sometimes chose smaller vehicles to serve those types of areas. Morris and Kornhauser (2000) and Morris (2004) observed movements of freight vehicles at loading docks to determine time- of-day patterns, dwell time, and truck size. The 2000 study only looked at two buildings and did not allow for correlation between these variables and building descriptions or facility pro- visions. The 2004 study found strong correlation between the number of daily deliveries and rentable space. Other researchers and practitioners have considered ways to estimate the number of truck trips generated by land use or facility type. NCHRP Synthesis of Highway Practice 298: Truck Trip Generation Data (Fischer and Han 2001) evaluated the state of the practice for truck trip- generation collection. They found estimating trips from commodity-based measures (like the Commodity Flow Survey) is challenging since doing so requires conversion rates between ton- nage to trips and is not likely to accurately reflect movements in urban areas, which are often chained. This work found that actual truck trip-generation information was available in a lim- ited fashion, but usually only for truck-intensive uses (for example, terminals and specialized warehouse and distribution facilities). Information regarding truck trip generation is generally not available for uses in urban centers (for example, office buildings and service or retail loca- tions) or even suburban-type development (industrial parks, warehouses, and manufacturing facilities). Woudsma (2001) points out a need for standardization in data collection. The Insti- tute of Transportation Engineers, in its 2008 edition of the Trip Generation Handbook, included a section on truck trip generation. The data presented includes information from a variety of land uses but relies on limited sample sizes. To address this gap, studies for specific land uses must be completed. McCormack et al. (2010) looked at truck trip generation at grocery stores, collecting survey data and manual count infor- mation to develop an estimate of 18 trucks trips per day, with an average dwell time of 27 min- utes for the sampled grocery stores. Unlike passenger trip generation, which is usually tied to land-use size, this study did not find a correlation between the size of the facility and the number of generated trips. Regional travel demand models have incorporated truck trips on some level by including special generators for truck-intensive uses, but again these uses are frequently not in the urban core or do not reflect other uses such as office buildings or retail establishments. A number of research areas associated with land-use mix and truck travel have not yet been considered. First, little research has been done on the impacts of truck travel in mixed-use envi- ronments. The relative benefit of trip reduction from mixed-use environments should be com- pared with the benefit of allowing off-hour service by trucks. In addition, the literature is sparse in terms of the relationship between land-use patterns and truck trip generation.

Intersection of Smart Growth and Urban Goods Movement 17 4.4 Logistics Studies The research areas of logistics, operations research, and industrial engineering have a num- ber of topic areas that are related to smart growth yet consider the movement of freight vehi- cles. These areas include research into time and size restrictions, vehicle choice, and warehouse locations. 4.4.1 Time and Size Restrictions and Vehicle Choice These restrictions and decisions are either dictated or limited by policy restrictions or are deci- sions made by private-sector service providers. Restrictions imposed through public policy mea- sures are often designed to reduce externalities, including congestion, air pollution, and noise pollution (van Rooijen et al. 2008). Private market motivations to reduce costs generally yield similar results because societal desires to reduce emissions and restrictions on private behavior usually result in higher emissions (van Rooijen et al. 2008; Holguín-Veras et al. 2013; Quak and de Koster 2007; Quak and de Koster 2009; Anderson et al. 2005; Siikavirta et al. 2002; and Allen et al. 2003 have all studied or commented on this relationship). Further, since delivery providers frequently choose their timing based on customer requirements, tools such as congestion pricing have been shown to be ineffective in changing truck timing (Holguín-Veras et al. 2006). Incen- tives that encourage receivers to accept deliveries during off-peak hours have been shown to be more successful (Holguín-Veras et al. 2011). 4.4.2 Warehouse Locations Since warehouses (including storage and distribution centers) are frequently one of the end points for commercial trips, their location can significantly influence the distance traveled by goods-movement vehicles. Warehouse locations affect travel behavior, and land-use policies affect the location of warehouses. Research about the optimal location for warehouses is com- mon. Crainic et al. (2004) found that the use of “satellite” warehouses to coordinate movements of multiple shippers and carriers into smaller vehicles reduces the vehicle miles traveled of heavy trucks in the urban center but increases the total mileage and number of vehicles moving goods within the urban center. This research illustrates the closer relationship between warehouse loca- tion and the vehicle choice problem. In contrast, Allen and Brown (2010) found that locating distribution facilities closer to urban centers would reduce the average length of haul and total vehicle kilometers traveled by freight vehicles in and to urban centers, and Andreoli et al. (2010) found that mega-distribution centers, located to serve multiple regions, increase the distance traveled between the distribution center and the final outlet. While warehouse location is an important factor in the ultimate impact of urban goods move- ment on an urban area, Klastorin et al. (1995) found that the ultimate location of warehouses is determined by land costs, not transportation costs. 4.5 Network System Management A final area of research that links smart growth’s congestion-reduction goals and urban goods movement is work that looks at the management of the transportation system to improve its operation. One of the main barriers to freight mobility identified by transportation managers is network congestion (Morris et al. 1999). Addressing this concern can be done by increasing the efficiency of the network through providing real-time information or metering of access. Marquez et al. (2004) looked at a number of different policies for reducing greenhouse-gas

18 Smart Growth and Urban Goods Movement emissions, including a number of network system-management strategies. Using volume-delay functions in a traditional modeling environment, coupled with emission-modeling tools, they identified modest improvements in carbon dioxide emissions and reductions in both vehicle hours of travel and trip lengths when better traffic management or real-time traffic information is provided. 4.6 Summary While smart-growth development is a focus of today’s urban planners and all stakeholders agree that goods movement needs to be explicitly considered within the planning sphere, a sig- nificant research gap exists in understanding how these two areas relate. Despite a clear tension identified between truck drivers, who claim a need for additional parking and loading, and planners, who claim to be doing their best to balance that desire with other competing interests, no research is available that examines or develops an optimal bal- ance of parking space and time regulations. The potential for conflicts between trucks and non-motorized modes is a primary concern for urban goods movement in smart-growth envi- ronments, yet it has hardly been considered in the literature. Another area of tension identified by this work is that between the trip-reduction and associated environmental gains fostered by mixed-use development and the lifestyle conflicts of having different uses in close proximity. Indeed, some other methods of achieving these types of gains—including off-hours deliveries or larger, more efficient vehicles—have specific impacts (air quality or noise pollution) that make them undesirable in mixed-use environments. Because of the risks identified in innovative distri- bution methods, additional research is required to illustrate their benefit and to identify ways to remove some of the existing barriers. Finally, efforts to manage the transportation system through real-time information and metered access are promising solutions to reducing congestion and thus reducing costs and environmental impacts. These efforts should be expanded to the extent possible to goods-movement services.