William Anderson

Modeling Private Car Ownership in China: Investigation of Urban Form Impact Across Megacities

The rising prevalence of private cars in the developing world is causing serious congestion and pollution. In China, private cars started to emerge as an important travel mode in the past decade. Prospective research on the relationship between urban form and car ownership is relatively uncommon in the developing world, and China offers a unique study opportunity, given the tremendous increases in private cars and fast-paced urbanization over the past decade. This study investigates the influence of urban form on car ownership as well as the impact of other socioeconomic and demographic factors on private car ownership across megacities in China. Analysis was conducted through the use of data from 36 megacities and two household survey data sets collected in Beijing and the city of Chengdu, China. Ordinary least squares regression and discrete choice models were employed to execute the aggregate and disaggregate analysis of the urban form impact on private car ownership across cities. The statistical model results demonstrate that urban affluence, urban scale, and road infrastructure supply factors have significant positive effects on the city level of private car ownership across cities. Population density calculated at the subdistrict level, however, had a significant negative effect on private car ownership across cities. Households with private cars were found to prefer to live close to urban centers where amenities were readily available. The results provide evidence for urban planners and policy makers.

Industrial agglomeration and transport accessibility in metropolitan Seoul

This study aims to reveal the relationship between industrial agglomeration and transport accessibility in the Seoul metropolitan area. Our study suggests that in spite of the rapid expansion of the Seoul metropolitan area, central business districts still function as centers of the industry and transportation system; the agglomeration of most industrial subsectors are occurring in central areas and only primary and manufacturing sectors’ clusters are located out of these areas; both of subway and road networks show higher level of accessibility in central Seoul and big cities. This implies a strong relationship between the industrial agglomeration and the transport accessibility, and such hypothetical relationship is tested for every industrial subsector using logit analysis. Our findings indicate that although there are industrial variations in the magnitude of impacts and the significance level, transport networks are, in general, positively associated with industrial agglomeration and this is especially true for service sectors.

Public policy in a cross‐border economic region

Purpose – The purpose of this paper is to describe an economic region straddling the Canada‐USA border between Ontario and Michigan from historical and contemporary perspectives. It aims to highlight policy challenges for federal, state, provincial and municipal governments.Design/methodology/approach – This paper provides a general review based on academic literature, government and consultant reports and data from a variety of sources. It begins with a historical review of the study regions. This is followed by a more detailed contemporary review of conditions arising since the attacks of September 11, 2001. A number of possible and ongoing policy options for various orders of government are then described.Findings – The paper finds that Ontario and Michigan comprise a highly integrated economic region with a particular focus on automotive production. Within that region the Canada‐USA border is a key transportation bottleneck whose impedance effect has gotten worse in the aftermath of September 11, 2001...

E-Commerce, Logistics and the Future of Globalized Freight

The worldwide movement of freight has emerged as one of the most critical and dynamic aspects of the transport sector. The contributors to this study examine the current state of global freight transport, with an emphasis on Europe and North America and their extra-regional linkages. These original contributions synthesize existing knowledge, highlight new developments, problems and possible solutions, and underscore the need for further research.

Toward sustainable urban mobility: Investigating nonwork travel behavior in a sprawled Canadian city

ABSTRACT The prevalence of urban sprawl, amplified levels of auto dependency, and nonwork travel during the afternoon peak hours have resulted in a steady increase in unsustainable patterns of travel in Canadian cities. Active and green modes of transportation along with smart growth have been promoted as a panacea. This article investigates the efficacy of such sustainable urban mobility strategies in Windsor, Ontario, using data records from a Household Travel Survey. Multinomial and mixed-logit models are developed to identify the factors influencing nonwork mode choice travel behavior. Next, the models are used in a scenario-building and simulation exercise to illustrate the benefits attained from jointly improving public transit, encouraging smart growth development, and lowering vehicle ownership. Based on the obtained results, embracing single-policy instruments is not an effective approach for reducing auto dependency in the study area. However, adopting a multidimensional policy approach that integrates land use and transportation policy instruments is proven more effective for achieving sustainable outcomes. It is recommended that the service and facilities for transit and nonmotorized modes be improved, and easier access to commercial and recreational activities be enhanced through progressive improvements to the built environment. Adoption of smart-growth strategies should be also pursued by planners and decision makers to create an environment conducive to reducing the levels of auto ownership. Such a goal is of paramount importance for sustainability because the level of auto ownership emerged as the most important policy instrument for reducing auto dependency in the study area.

Characterization of International Origin–Destination Truck Movements Across Two Major U.S.–Canadian Border Crossings

In 2013, 3.9 million trucks crossed between the United States and Canada at the Ambassador Bridge or the Blue Water Bridge. These trucks accounted for 43.1%, by value, of all truck trade between the two countries. GPS pings that tracked the movement of Canadian-owned trucks over a span of 1 year were used to characterize freight activities at the two Canada–United States border crossings. (A “ping” is a GPS data record that identifies the location of a subject at a given point in time. The term is commonly used in the information technology and communications industries.) A total of 172,000 and 82,000 crossing events were identified and analyzed at the Ambassador Bridge and the Blue Water Bridge, respectively. This paper describes the development of origin–destination data pertaining to truck trips that utilize the two border locations. The paper also includes an estimation of the industries involved in individual trips, on the basis of those trips’ start and end locations. The combination of origin, destination, crossing time and location, and industry provides an immense amount of information on the nature of international truck movements at the Canada–United States border. The resulting spatial patterns provide evidence that the two border crossings are used for both short- and long-range trips that include locations on the West Coast and the southern U.S. border. Although crossing times did not vary considerably by industry, they were influenced by the distance of the trip: short-distance journeys had shorter crossing durations, on average.

Location and Transportation Effects on Nonresidential Real Estate Price Regressions in Windsor, Ontario, Canada

In this paper, land prices for nonresidential real estate listings in Windsor, Ontario, Canada, are analyzed with the use of ordinary least squares regression models. Location and transportation attributes are used in the analysis to explain observed land prices. Seven models were estimated to control the heterogeneity in the land use types. The results show differences in factors explaining land prices of the models, indicating that caution should be used when land use types are aggregated together. The role of transportation carried mixed results. Rail had a positive effect for industrial properties but was negative for commercial and food services. Transit had a positive effect on vacant land. Direct proximity to highway ramps had a negative correlation for vacant land, but indirect variables such as potential (residential) accessibility and time to the central business district indicated the positive effects that roads and highways had. Testing showed that although spatial autocorrelation was present in the price data, the independent regressors used in the modeling partially mitigated that effect. Multicollinearity and heteroscedasticity were also accounted for throughout the modeling process. The results obtained provide a useful account of various spatial and transportation-related phenomena for a midsize Canadian metropolitan area. Moreover, the empirical analysis is particularly valuable given the lack of modeling done on the commercial and industrial prices when compared with that done for residential properties.

Border Crossing Choice Behavior of Trucks Along Trade Corridor Between Toronto, Ontario, Canada, and Chicago, Illinois

Canada and the United States are heavily dependent on a few border crossing locations to facilitate international trade between the two countries. These crossings cost firms extra time and uncertainty in their supply chains that reduce the effectiveness of trade. Therefore, a great need exists to study the movement of vehicles traversing these border locations and identify characteristics that make these locations attractive. To this end, this study utilizes GPS data to study trucks traveling between the transportation hubs in Toronto, Ontario, Canada, and Chicago, Illinois. Two feasible choices are available for these trucks to cross the international border: Blue Water Bridge and Ambassador Bridge. Although most route choice decisions are based primarily on reducing travel time, a unique aspect of this corridor is that the total trip time by route is relatively even. A logit model was estimated to identify other factors that may influence the route choice decisions of trucks in the Toronto–Chicago corridor. The results suggest that a higher average crossing delay for a given time of the day has a negative influence on the selection of a given border crossing. Such an effect is more pronounced for the Blue Water Bridge. Other factors influencing the choice of crossing include the type of industry served by the truck, the carriers operating the trucks, time of the day, and day of the week.

Examining the Variability of Crossing Times for Canadian Trucks at the Three Major Canada–U.S. Border Crossings

Land borders connecting Canada and the United States are vital transportation facilities for the two countries. Truck crossing times at these facilities can have a significant impact on the performance of the economy. To date, knowledge about border crossing times has been limited due to lack of detailed data on the Canadian border. This article explores and models the patterns of crossing times at the three major land crossings connecting Canada to the United States: Ambassador Bridge, Blue Water Bridge, and Peace Bridge. The analysis is based on 387,775 border crossing truck trips that were generated between Canada and the United States over a course of twelve months. Seemingly unrelated regression (SUR) models are estimated to evaluate the seasonal and hourly crossing times of Canada- and U.S.-bound trips on each border crossing, controlling for traffic intensity in the models. The SUR modeling approach is chosen to control for potential cross-model correlations. The results suggest that crossing times at the border vary by season and hour of the day. Crossing times also vary by direction of traffic and by type of day (i.e., weekday vs. weekend). Traffic intensity has a significant influence on crossing times at two of the crossings but not the Blue Water Bridge. Finally, crossing times are more variable during the summer season and tend to be higher during the late evening hours and past midnight.

Automatic license plate recognition: A comparative study

Automatic license plate recognition (ALPR) is the process of locating and extracting vehicles plate information from images or videos. The extracted information is essential for several everyday applications, ranging from automated payment services (e.g. parking and toll roads payment collection) to more critical applications, like border crossing security and traffic surveillance systems. Various solutions have been proposed for the ALPR problem, with many available commercial packages. However, amid plate variations from place to place, ALPR systems tend to be region-specific. There is no general solution that works effectively everywhere for every province/state or country. In this paper, we have reviewed a set of state-of-the-art ALPR methods and, compared their respective performances by testing them on a rich database of vehicles from Ontario (Canada).