Journal of Urban Planning and Development

The study explores the relationship between transportation and development in the East Africa and Indian Ocean (EAIO) region. A positive link between development, defined in terms of gross national income per capita (GNI/cap), and transportation, operationalized in terms of the different major forms of transport infrastructure in the study region, is hypothesized. Multiple regression involving natural logarithms and concomitant statistics is employed to test the hypothesis. The resultant model is positive and statistically significant at the 95% level. Thus, the hypothesized relationship is confirmed. Two seemingly counterintuitive results, namely the not-statistically-significant negative association between railways and development, and the statistically significant link between dirt roads and development, are noted. Two plausible explanations are proffered for this unexpected finding. One is that dirt roads constitute a hindrance, rather than a facilitator, to development during the rainy season when they are impassable. The other is that railways in the area suffer from neglect and are not harmonized enough to maximize their utility. On account of the revelation that transportation, as a whole, is positively linked to development, and the fact that the functioning of other sectors depends largely on transportation, it is recommended that transport infrastructure and facilities be prioritized as an investment target in the EAIO region.

Accurate projection of the economic conditions in a country can enable the government to establish appropriate policies in a timely manner. This also applies to enterprises and individuals in terms of decision-making processes, such as investing and production planning and household consumption and saving. The U.S. housing market is no exception to this practice. The prompt and accurate assessment of the trends in the U.S. housing market enables consumers to make quick decisions and to come up with the corresponding measures, thus minimizing risks associated with market uncertainty. The monthly indices of the U.S. housing market indicators are released at the end of the following month, creating a month-long standstill in making a judgment regarding the housing market. Consequently, it is not possible to predict the current month’s market status. Therefore, in this study, various “U.S. housing market-related” indicators were calculated as average month-to-month changes using the composite index methodology of the National Bureau of Economic Research (NBER). The trends in the U.S. housing market were analyzed using the Markov switching models: the Markov switching random walk (MS-RW) model and the Markov switching autoregressive (MS-AR) model. Results showed that the methods can accurately determine the trends in the U.S. housing market. Findings from the forecasting performance test made it possible to predict or forecast the prospects of the U.S. housing market within the month-long standstill period.

In an era of continuous growth in mobility and demand for transportation, safety is an issue of major social concern and an area of extensive research and work by practitioners and academics. Emergency response services are very important in handling and minimizing the impacts of traffic accidents and for saving human lives. In this paper, we develop an efficient emergency response plan for responding to traffic accidents; the objective is to strategically deploy emergency response vehicles in a large urban transportation network. We combine a location model with a genetic algorithm and guide location decisions through accident metrics such as accident frequencies and severities at different parts of the network. We demonstrate the usefulness and applicability of this approach by planning for a real-world case study in the city of Thessaloniki, Greece.

Planning pedestrian environments requires assumptions about how pedestrians will respond to characteristics of the walking environment in city centers. European city centers, especially medieval ones, have been more and more pedestrianized in the last two decades. Two major groups, shopkeepers and pedestrians profit from this enlargement of public space. The perception of shopkeepers is to attract more buyers from walkways and from adjacent places in the city centers. At the same time, the perception of pedestrians is to walk on pleasant and peaceful way without confronting other pedestrians in a chaotic situation. This paper considers the perceptions of shopkeepers and pedestrians in a medium-sized Portuguese city center using the Analytical Hierarchy Process (AHP) model. A field survey was conducted in January 2010 to summarize different perceptions of using sidewalks and to know the responses of shopkeepers and pedestrians. Both were interviewed during the field survey. Results show that there are several interesting issues, such as short-term parking on walkways to buy goods from the adjacent shops or illegal encroachment of sidewalks because of goods or propaganda displayed to attract more buyers to the shops. These issues need to be considered for planning a better walkway environment in the Guimarães city center that has a long tradition of walking since medieval times.

Reliably forecasting freight demand has become essential in freight transportation management to systematically plan for future transportation facility needs. Commodity-based freight demand modeling techniques have been in the mainstream because these techniques overcome the weakness of applying a typical four-step demand forecasting modeling process to freight transportation and capture more accurately the fundamental economic mechanisms that drive freight movement. However, none of the existing models actively use commodity-flow data that have become available to public through the Internet in the past decade. The authors used such data and found good correlation between commodity-flow and aggregate land use type in a previous study. However, it was found that aggregate land-use type data were not readily available to public. Instead, data that describe characteristics of particular land-use such as employment data, business pattern data, and wage data were readily available. Hence, models that use land-use characteristics instead of aggregate land-use type data were developed in this study by using the commodity-flow data available from the 2002 Commodity Flow Survey conducted by the Bureau of Transportation Statistics and U.S. Census Bureau, and by using other data available to the public through the Internet. These models were used to estimate commodity flow in 2007, and their estimates were compared with commodity-flow values found in the 2007 Commodity Flow Survey. Results of this comparison showed that the models could produce decent estimates of commodity flow at the county level and be of practical use because the model inputs are available free through the Internet.

Given its contribution to congestion, pollution, and energy consumption and the complex and changing characteristics of delivery routes, the modeling of urban freight transport is a difficult, highly data-demanding and often unreliable task. Extending other previous works that focused only on the morning peak hour, the authors have developed a trip generation model by using the available data to their maximum extent and adding other parameters that can be found through simple surveys. This trip generation model is then included as part of a four-stage process, with the trip distribution solved through entropy maximization and resulting in the estimation of an origin-destination matrix for freight transport in a city. The application to a case study in the city of Seville and the validation with on-street vehicle counts shows reasonably robust results and provides a simple and effective tool to analyze urban freight deliveries from a macroscopic point of view.

This paper focuses on identifying important factors that determine activity-based travel distance in urban areas. Building on past research that has demonstrated the conceptual equivalence of hazard models applied to either temporal or spatial settings, the length of the distance from origin to destination is statistically modeled as longitudinal data using hazard-based modeling methods with data from Athens, Greece. Based on the data analysis, the Weibull model with gamma heterogeneity provides the best statistical fit, and a number of factors significantly affect travel distance, including socioeconomics and demographics, trip characteristics, mode choice, trip frequency, time of day for the trip, and type of activity participation. The proposed methodological approach and the research findings help to better understand travel behavior in terms of trip distance in the urban areas, an issue of significant importance for both transportation researchers and planners.

The study is based on developing a bikeway master plan by determining the utility of bicycle routes, assessing their contributions to urban transportation, their effect on individual and social leisure time activities, and the behavior and demands of the people in the City of Adana, Turkey. Sixteen routes were evaluated according to 14 criteria that include physical and environmental conditions, land use types, and user characteristics to determine level of service. The results ranged from 2.15 to 58.32 on a 90-point scale. The total length of bicycle routes included in the study (110.9 km) reached 120 km by adding 9.1 km of additional routes to provide continuity of the routes and demands of the user. Three different bikeway types were predicted for the study area, taking into account the width of the roads, the possibilities for expansion (land use type and expropriation requirements at road boundaries), and vehicle/pedestrian circulation density. Bicycle paths that were grade-separated from pedestrian and vehicular roads formed 29.8 km. Bicycle lanes designated as pedestrian roads formed 10.2 km. Bicycle lanes designated as vehicular roads formed 80 km.

The built environments of metropolitan areas are rapidly changing in response to urban development dynamics. The nature of the urban built environment continues to be influenced by the conflicting interests and expectations of various entities involved in the process of development planning and implementation. The formulation and implementation of urban development plans in Turkey is guided by the statutory provisions of the country’s planning system. This process has led to piecemeal implementation through partial plans and plan amendments in metropolitan areas. This article attempts to determine how the private sector in metropoles in Turkey shaped the built environment in Turkey after 1980. Influence of neo-liberal policies and a partial planning approach set by a free-market economy instead of a comprehensive planning approach shaped urban space. As a capital, the urban development of Ankara has mostly been shaped by partial planning approaches and implementations and uncontrolled developments, especially on the southwest axis of the city's metropolitan area. For this reason, one of the largest settlement of southwest Ankara is the Angora Settlement, which has been selected as the case study. Examining the entities who play a part in the urban development process is important to control its consequences. In this article, the case of Angora Settlement is used to question the planning process and entities in the development of urban built environments, and studies this settlement to identify and question which entities determine the components of the built environment in the urban development process. In particular, this paper captures the dominance of the structural interests of the private sector in shaping Angora’s land use pattern, which is important because it reveals the uncontrolled growth dynamics in developing countries.

The Yangtze River delta urban agglomeration of China has experienced a significant development bloom in the last 30 years. To explore the spatial structure, a series of methods have been applied in this study: a mathematical analysis to ascertain the framework of cities in this urban agglomeration, a research on the expansion of completed areas, and population density on the basis of the grid analysis. It has been identified that a single-nucleus and several-centers model could be the best model to suit the spatial structure. This model, similar in many classical cases of spatial-structure model of conurbations and urban agglomerations, can be utilized to speed up urbanization, provide reasonable modes to industry spreading, establish special functional cores, and protect the environment in both urban and rural regions.

Flex-route transit service is a promising option to serve low-density urban areas. In this paper, we investigate the feasibility and benefits of replacing feeder fixed-route transit routes in a suburban area by flex-route service. Three routes in the City of Oakville (a suburb of Toronto) that connect with the regional commuter rail (GO Transit) were chosen for the analysis. A simulation of the routes under the existing structure and under several flex-route designs was performed. The results show that assigning an appropriate slack time is essential in having an effective flex-route service and that more slack time does not necessarily translate into more ridership. The results also show that improving the performance of the transit service, in terms of passenger per vehicle revenue hours, will occur only if the ratio of the increase in ridership relative to the added slack time is more than the ratio of the existing ridership relative to the scheduled running time of the original fixed-route service.