Shopping morphologies of urban transit station areas: A comparative study of central city station catchments in Toronto,San Francisco,and Melbourne

Synergies between shopping and public transit have long been noted, with main streets emerging along tram lines and shopping malls attached to train stations. The shopping-transit synergy is also at the core of transit-oriented development (TOD), a widespread planning approach to urban sustainability. However, there is a lack of morphological research investigating how shopping clusters around transit stations at a fine-geographic scale. This paper explores the shopping morphologies of three central-city subway station areas in Toronto, San Francisco, and Melbourne, mapping and measuring the extent of public and quasi-public shopfronts relative to the station. The morphological analysis of 200, 300, 400, and 500 m walking catchments shows that as the distance from the station increases, the proportion of shopfronts in the total catchment declines. Quasi-public shopping space can enhance the walkable catchment and permeability of a station area and may contribute to urbanity as long as it adds to diversity of access options. The findings highlight the role walkable shopping environments can play within urban transit station areas and show the importance of nuanced consideration being given to morphologies in the analysis and planning of TODs.     

Why we fail to reduce urban road traffic volumes: Does it matter how planners frame the problem?

If the objective of reducing urban road traffic volumes and GHG emissions from traffic is to be achieved, the way in which land use and transport systems in cities are planned and developed needs to change. Despite apparent agreement that this should be done and how it could be done, cities continue to be planned and developed in ways that cause and allow growth in urban road traffic volumes. In this paper we ask how planners frame the ‘transport problem’, and how their framing of the problem affects urban planning, the resulting plans and developments and the urban road traffic volumes. The discussions are based on findings from a case study, a survey and interviews with planning practitioners.     

Local authority and academic attitudes to urban road pricing: a UK perspective

Urban road pricing as an instrument of traffic management has generated a great deal of interest in the UK in recent years. Whilst this is the case there is still no urban road pricing scheme in operation in the UK. The reason for this is primarily one of ‘acceptability.’ This paper, through the use of a national survey, examines the attitudes of key stakeholder groups with respect to urban road pricing. How serious is traffic congestion and traffic related pollution perceived to be by Local Authority Councillors, Officials and the Academic community in the UK? How is urban road pricing viewed by this sub-group of the population in terms of its effectiveness and public acceptance when compared to other policy options? and how could the saleability of urban road pricing be improved? This raises issues in terms of how the revenue raised from urban road pricing should be utilised, the use of urban road pricing as part of a package of measures, the concerns expressed by the stakeholders with respect to urban road pricing, such as the invasion of road users’ privacy, and the type of technology which should be considered. Overall, the paper aims to further the debate among policy makers.     

Are we keeping up? Accessibility,equity and air quality in regional planning

Many US metropolitan areas have undergone dramatic shifts in socioeconomic organization.. As urban areas gentrify, many low-income residents and communities of color have transitioned towards the exurban periphery. These suburban neighborhoods tend to have fewer employment opportunities and are fairly disconnected from public transportation networks serving the urban core. Using regional transportation plans (RTPs) for three California MPOs, we show that the transportation accessibility and environmental health issues affecting these exurban communities are unique and inadequately captured by the MPOs' current equity metrics. MPOs performance evaluation is regional and achieving equity within the urban core communities will not address emerging equity, accessibility and air quality concerns for exurban communities. With a brief history and a focused case study of RTPs for the San Francisco Bay Area, San Diego, and Fresno, we examine how air pollution, equity, and transportation interact in three different types of 21st century cities. We find that when allocating limited transportation funds, California metropolitan planning organizations (MPOs) prioritize the improvement of existing public transportation in urban core areas over expansion of transit networks towards disconnected exurbs. This approach is an effective way to reduce vehicle miles traveled (and thus, air pollution) at the regional level due to high population concentrations in urban cores. However, this approach also concentrates the air quality benefits of VMT reduction in these same urban core areas. Exurban residents' on-road and near-road exposure to Traffic-Related Air Pollution (TRAP) will not be reduced by improving public transit within the urban core. We argue that although these suburban and exurban communities are a small percentage of the regional population, they have a right to share in the benefits of transportation investments, particularly given the historical and ongoing patterns of displacement and economic exclusion from urban core areas.     

Identification of land-use characteristics using bicycle sharing data: A deep learning approach

Extensive research has shown that urban land-use characteristics, including resident, work, consumption, transit, etc., are significantly interrelated with travel behaviors and travel demands. Many research efforts have been made to evaluate the impact of land use planning or policies on travel behavior, however, few studies are able to quantitatively measure the land-use characteristics based on the data of travel behaviors or travel demand. In this paper, a new hybrid model that combines time series feature extraction and deep neural network is proposed to identify regional land use characteristics and quantify land use intensity using ridership data of bicycle sharing. This method consists of four main parts: (i) A set of land-use characteristic labels are evaluated based on planning and Geographic Information System (GIS) data. (ii) An ensemble clustering method is used to determine the segmentation points of ridership time series. (iii) The statistical characteristics of the segmented time series are extracted and used as input to the neural network. (iv) A deep neural network is established and trained based on the processed ridership features and land-use labels. In terms of data collection, ridership data of the bicycle-sharing parking spots and land-use planning data are obtained from bicycle-sharing system and planning department in San Francisco Bay Area, California U.S.A., respectively. The test results show that this approach has high accuracy for identifying land-use characteristics based on several standard evaluation measures and that the identification distribution can be well explained. The extension results further prove that the model can be applied to effectively analyze the main land-use characteristics of the region although the identification results may become unstable after 3–4 months.     

Determinants of sustainable mode choice in different socio-cultural contexts: A comparison of Rome and San Francisco

This paper is a part two of a study investigating the relative importance of the built environment, socio-demographic, and attitudinal factors on mode choice. A semi-experimental approach that aims to measure causal effects of the built environment is utilized. This paper reports spatial analysis, survey and modeling results for San Francisco, CA, USA and compares the results with a previous similar study in Rome, Italy. Results reveal that the local street network's integration is important in both cities and that in both cases built environment seems to have higher impact on mode choice than attitudes and socio-demographic factors. Built environment is especially impactful when diversity, design quality, density and syntactical accessibility are combined. In San Francisco willingness to spend time walking, biking or taking transit is lower than in Rome, and residents are more sensitive to concerns about safety and security. Work travel is more affected by demographic and attitudinal factors in San Francisco than in Rome implying that in San Francisco, nonwork travel behavior may have slightly higher potential to respond positively to improvements in the built environment than work trips. In Rome, peer pressure, cost sensitivity, and probiking attitude can compensate for lack of some built environmental characteristics, but not in San Francisco, where only protransit attitude has this effect. Moreover, lack of any built environmental characteristics reduces the possibility of sustainable mode choice more dramatically in San Francisco pointing to the higher importance of investments on improving the built environment rather than marketing efforts to change attitudes.     

Can freeway traffic volume information facilitate urban accessibility assessment?: Case study of the city of St. Louis

In urban contexts, accessibility measures are often utilized to represent the interactions among land use, transport and people’s trips to services and other facilities. Accessibility is generally evaluated using conventional traffic measures such as travel time and distance, but traffic volume, which is a product of the travel trips induced by people’s needs, may also be positively related to accessibility. This study tests the hypothesis “can freeway traffic volume information facilitate urban accessibility assessment?” Traffic volume based accessibility models are proposed to investigate this relationship and test the hypothesis. The results indicate that the answer to this question is a qualified “yes”, as there is a statistically significant relationship between traffic volume differences and accessibility. The coefficients of the models can potentially be used as a reference to guide the urban planning process. The limitations of the proposed models can be addressed by deploying Intelligent Transportation Systems (ITS) traffic sensors on ramps and arterial roadways.     

Using principles of justice to assess the modal equity of regional transportation plans

While equity has been an important consideration for transportation planning agencies in the U.S. following the passage of Civil Rights Act of 1964 (Title VI specifically) and the subsequent Department of Transportation directives, there is little guidance on how to assess the distribution of benefits generated by transport investment programs. As a result, the distribution of these benefits has received relatively little attention in transportation planning, compared to transport-related burdens. Drawing on philosophies of social justice, we present an equity assessment of the distribution of accessibility in order to define the rate of “access poverty” among the population. We then apply this analysis to regional transportation plan scenarios from the San Francisco Bay Area, focusing on measures of differences between public transit and automobile access. The analysis shows that virtually all neighborhoods suffer from substantial gaps between car and public transport-based accessibility, but that the two proposed transportation investment programs reduce access poverty compared to the “no project” scenario. We also investigate how access and access poverty rates vary by demographic groups and map low-income communities within access impoverished areas, which could be the subject of further focused investments.     

Smartphone gaming is associated with pedestrians' head-turning performances: An observational study of street-crossing behaviors at uncontrolled intersection in Taipei

Pedestrians' head-turning behaviors are crucial to navigating streets safely. This research investigates the effects of phone use on pedestrians' street-crossing behaviors at an uncontrolled intersection where head-turning performances are important to identify a gap among the oncoming traffic. A field study using video cameras was conducted for evaluating pedestrians' head-turning behaviors (e.g., head-turning frequency, not looking at traffic before crossing, looking at the wrong traffic side), crossing time, and sudden movement while they were engaging in various smartphone activities (e.g., calling, texting, gaming, and listening to music). Data such as phone features, distraction types, and personal attributes of the pedestrians were obtained in the interviews conducted after pedestrians had completed crossing the street. The results indicate that the unsafe crossing behaviors (e.g., sudden movement, fewer head-turning frequencies, not looking at traffic before crossing, not looking at left side of traffic first) were more prevalent among those gaming with “Pokemon Go.” Web surfing appears to be the 2nd risky distraction event following gaming with “Pokemon Go.” Logistic regression models reveal several important correlates of unsafe crossing behaviors: being a student, large phone screen (5 in. or larger), and having un-restricted 4G Internet data allowance. The current research recommends that “Pokemon Go” gaming be prohibited while crossing the street.     

Notes on the practices and appearances of e-scooter users in public space

While the legalisation of and policies around e-scooters remain the cause of much debate worldwide, this article sheds lights on e-scooter users’ current practices and their interactions with pedestrians in the city. Taking an ethnomethodological approach to public space and mobility, we use video recordings of e-scooter riders to show, firstly, how riders dismount and then move to acquire rights to continue moving, thereby ‘playing’ with traffic rules, in order to weave rapidly through congested urban environments. Secondly, we examine how e-scooter riders and pedestrians deal with the potentially unexpected appearance of e-scooters via displays of attention, adjustments of speed, and the relative rights and obligations established via category-relevant spaces. The findings offer insights into the integration of e-scooters as one of what may be many new forms of electric powered micro-mobility in urban space.     

Who could benefit from a bus rapid transit system in cities from developing countries? A case study from Kampala,Uganda

The present rapid urban growth of cities from developing countries causes negative externalities such as lagging infrastructure development. In combination with rapidly rising motorized vehicle use this leads to severe traffic congestion affecting the mobility of the urban residents. Therefore many urban governments are planning to improve their transport and mobility situations with mass rapid transit systems of which a bus rapid transit (BRT) is a rather easy system to implement at reasonable costs. However, due to high urban inequalities the effects of urban traffic and potential improvements of the urban transport system for the diverse group of urban residents can differ significantly. In our case study Kampala (Uganda) four main groups were identified through cluster analysis of socio-economic and residential data gathered through interviews: extreme poor, poor, middle income and rich. Each group experiences a different mobility with the extreme poor being the most vulnerable group. The planned BRT system aims to decrease the average travel time but risks to exclude the lowest income class since not enough attention is paid to the affordability of the system to all residents. Therefore we argue for a policy that works from bottom up and pays attention to the internal diversity of the population.     

Road environments and bicyclist route choice: The cases of Davis and San Francisco,CA

Examining bicyclists' route choices provides valuable insights into the importance of road environments for bicycling. In this study, we examine the role of road factors, individual factors, and preference heterogeneity on route choice using two diverse and extreme cases in the U.S. The first case is bicycling to the University of California, Davis campus by students, faculty, and staff. This case represents the most bike friendly environment in the U.S. which affords a diverse bicycling population. The second case is bicycling to many destinations for many purposes in San Francisco, CA. It is more representative of a large U.S. city, but also has a relatively large bicycling mode share. It serves as an important case for examining the new innovative type of bicycling infrastructure that has been installed in North American cities over the past decade. Results suggest substantial within-city between-person heterogeneity in preference for road attributes and bicycling facilities as well as differences between contexts. Davisites show strong preferences for bike lanes and off-street paths and consistently choose routes of similar length to shortest routes indicating the need for suitable routes with minimal detours to support a large bicycling mode share. San Franciscans show strong preferences for conventional bike lanes on minor arterials, even stronger preferences for separated and protected bicycling facilities, and are willing to detour considerable distances to ride on them. Given large between-person differences within cities, we suggest usual valuations of bicycling facilities from elasticities and marginal rates of substitutions at the mean may need rethinking when applied to bike infrastructure planning.     

Investigating the impacts of built environment on traffic states incorporating spatial heterogeneity

Traffic state in the urban network is a direct reflection of the operational efficiency of the urban transportation system. As the busiest period of the day, traffic states during evening peak hours can effectively measure the capacity and efficiency of the transportation system. The primary objective of this study is to investigate how the potential factors affect traffic states during evening peak hours on weekdays. The geographically weighted regression (GWR) approach was proposed to model the spatial heterogeneity of traffic states and visualize the spatial distributions of parameter estimations. Four types of data including traffic state index (TSI) data, point of interests (POIs) data, road features data, and public transport facilities data were obtained from Shanghai in China to illustrate the procedure. According to the results, the GWR model outperformed the ordinary least square (OLS) model in the explanatory accuracy as well as the goodness of fit. The urban form was revealed to have a significant influence on traffic states and strong local variability for parameter estimations was observed. The number of public and commercial POIs, residential POIs, bus routes, bus stops, the average number of lanes, as well as average traffic volumes can significantly affect the traffic states spatially, and the estimated coefficients of each traffic analysis zone (TAZ) vary across regions. The conclusions of this study may contribute to making the planning and management strategies more efficient for alleviating traffic congestion.     

Defining and monitoring the quality of shared-use transportation facilities in parks and recreation areas

Transportation networks in parks and recreation areas provide travelers recreation opportunities and often support multiple transportation modes (e.g., hiking, walking, biking). In recreation areas, the quality of transportation service may be monitored and evaluated differently than in traditional transportation contexts. However, few studies have examined approaches for defining and monitoring the quality of transportation service and recreation experiences. This study applies traffic monitoring models to monitor (1) the quality of transportation service through the Levels of Service (LOS) framework and (2) travelers’ recreation experiences through the indicators and standards framework simultaneously on the Burlington Bike Path (BBP), a typical shared-use transportation recreation facility in Vermont. Results identify the temporal pattern of visitors use and the mode splits between cyclists and pedestrians. Moreover, study results show that the majority of travelers use the BBP for recreation or mixed purpose of recreation and commute. Study results build quantitative relationships between LOS and indicators and standards of quality that will help inform management of transportation in the context of recreation. The indicators and standards framework can help define the thresholds of acceptable levels of transportation service through the LOS framework. The relationships between LOS and the indicators and standards framework help build a robust and fully parameterized transportation planning and management framework for parks and recreation areas. Study results suggest quantitative guidelines that can be used to evaluate and monitor the quality of transportation performance for shared-use paths in parks and recreation areas.     

A new zone system to analyze the spatial relationships between the built environment and traffic safety

This study aims to investigate the impacts of the built environment on traffic safety at a zonal level using a newly developed crash-related zone system. Traffic analysis zones (TAZs) have been widely employed to analyze traffic safety at a macroscopic level. However, this zone system use may present problems. Unlike previous studies, in which new zoning systems were created from aggregating TAZs, in this study the new zone system, formed by traffic safety analysis zones (TSAZs), is created from the smallest available census units. Geographically Weighted Negative Binomial Regression (GWNBR) models are used and a comparative analysis between non-spatial global crash prediction models and spatial local GWPR (Geographically Weighted Poisson Regression) and GWNBR models using the two zonal systems is presented. We find that TSAZs based models performed better than TAZs based models, especially when combined to the GWNBR technique. Our results show that several features of the built environment are significant crash predictors, and that the relationships among these features and traffic safety vary across space. By combining a crash-related zonal system with spatial GWNBR models to understand the built environment effects on traffic safety, the results of the analysis can help urban planners to consider traffic safety proactively when planning or retrofitting urban areas.     

Auditing street walkability and associated social inequalities for planning implications

Transport planning is gradually shifting targets towards modifying the pedestrian streetscapes that favor walking and enhance urban sustainability. We cannot be optimistic about walkability on condition that walkable streets are not evenly distributed within urban settings. Auditing the street walkability and associated social inequalities in developing countries should provide critical implications for transport planning. This paper identifies the most common indicators in existing indicator classification frameworks based on word frequency; and then establishes an indicator classification system (connectivity, accessibility, suitability, serviceability, and perceptibility) through expert panel evaluation for auditing street walkability in China. Using a case of Hangzhou metropolitan area, a set of 13 indicators are first selected by referring to the established indicator classification system and then aggregated into an integrated walkability index (IWI) through the catastrophe theory (CT) model after appropriate data treatment (standardization, normalization and correlation calculation). Camera signaling data are employed to validate the developed IWI. Results show that IWI is efficient to audit street walkability. IWI presents great heterogeneity at segment level. In general, higher walkability is observed in streets across the central and western areas. Walkability profiles of the segments are further produced by the clustering approach and the categorized groups can inform more targeted planning options. Spatial regression is finally utilized to quantify the associations between community socio-demographics and neighborhood IWI at two levels. We discover that lower neighborhood walkability would be observed in socioeconomically disadvantaged communities. These results suggest that significant social inequalities in street walkability should exist across the communities within Hangzhou metropolitan area. The developed IWI not only brings a standardized measurement of street walkability in the field of transport planning, but also paves the way for addressing the social inequalities in street design across various jurisdictions.     

The trilogy of distance, speed and time

Over the recent past there has been a dramatic increase in travel, mainly driven by the desire to move faster and over ever greater distances. This growth is unsustainable, and the continued growth in levels of mobility needs to be reassessed through substantially reducing the levels of consumption (energy and carbon) in transport. This means that travel activities should be based on shorter distances and slower speeds, with a more flexible interpretation of time constraints. Transport geographers should have a strong and instrumental role to play in this debate. This paper outlines the changing patterns of movement, before concentrating on urban areas where most daily travel takes place, and it examines the trilogy of distance, speed and time. The focus of the paper is on distance, and the role that land use planning and development, and technology can play in encouraging new forms of travel in cities, but there are strong implications on the ways in which speed and time are conceptualised. The conventional transport paradigm is heavily embedded in the belief that travel time needs to be minimised and consequently speeds need to be increased. The resulting impacts on travel distances have not been part of that debate, but reducing travel distances is central to sustainable transport.     

Citizen participation for sustainable transport: the case of “Living City” in Santiago,Chile (1997–2012)

Twentieth century citizen “revolts” against urban highway projects have influenced thinking about public transport (Toronto, Vancouver, New York), governance (Portland), and cycling (The Netherlands) to this day. Less is known, however, about how these emerge in developing countries, and what they can tell us about citizens’ role in innovation to achieve more sustainable transport systems. This case study examines a social movement that emerged in opposition to the country’s first major highway concession, in Santiago, Chile (1997), challenging and changing urban planning paradigms. In 2000, the anti-highway campaign founded a citizen institution, Living City (Ciudad Viva). Twelve years later, it has become a prize-winning, citizen-led planning institution.Although the role of citizen participation in improving transport systems has become increasingly recognized in recent years, it still tends to be rather ritualistic. This experience offers insight into how strategic approaches to participation can reinforce the role of self-organizing civil society organizations in introducing innovation into existing systems. Findings suggest that traditional large movements, which are mainly useful for one-way communication of information, require support from small groups able to deliberate in a transformative sense, with more attention paid to how new consensuses can be transmitted through the relational networks of those involved. Moreover, this experience suggests that thinking about citizens as planners in their own right, rather than as mere participants at specific points in a planning process, opens the way to more effective strategies for innovating in transport, to address the social, environmental, and other challenges humanity faces today.     

Commuting and energy consumption: toward an equitable transportation policy

Like other major metropolitan areas, the urban complex that extends from Los Angeles to Orange County faces numerous transportation challenges. Daily traffic congestion, reduced productivity and loss of income, air pollution, environmental degradation and significant energy consumption are only a few outcomes of the millions of miles travelled every day on the region’s highways and streets. An important response to this significant urban challenge has been the desire for further expansion of an efficient public transportation network and increasing densities in particular areas within the larger metropolitan region. In this paper, we estimate the current energy consumption patterns in various communities, arguing that policy attempts to achieve higher density and better jobs-housing balance should fully consider the social geography of our metropolitan areas and their close relationship with energy consumption patterns.     

Spatially varying impacts of built environment factors on rail transit ridership at station level: A case study in Guangzhou,China

Understanding the relationship between the rail transit ridership and the built environment is crucial to promoting transit-oriented development and sustainable urban growth. Geographically weighted regression (GWR) models have previously been employed to reveal the spatial differences in such relationships at the station level. However, few studies characterized the built environment at a fine scale and associated them with rail transit usage. Moreover, none of the existing studies attempted to categorize the stations for policy-making considering varying impacts of the built environment. In this study, taking Guangzhou as an example, we integrated multi-source spatial big data, such as high spatial resolution remote sensing images, points of interest (POIs), social media and building footprint data to precisely quantify the characteristics of the built environment. This was combined with a GWR model to understand how the impacts of the fine-scale built environment factors on the rail transit ridership vary across the study region. The k-means clustering method was employed to identify distinct station groups based on the coefficients of the GWR model at the local stations. Policy zoning was proposed based on the results and differentiated planning guidance was suggested for different zones. These recommendations are expected to help increase rail transit usage, inform rail transit planning (to relieve the traffic burden on currently crowed lines), and re-allocate industrial and living facilities to reduce the commute for the residents. The policy and planning implications are crucial for the coordinated development of the rail transit system and land use.