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In recent decades, transit equity has become a recurrent topic within the domain of sustainable transportation, where accessibility is a crucial indicator. However, the measurement of accessibility and equity in existing studies is usually based on the route with the shortest travel time, whereas multiple travel routes and corresponding travel costs remain unexamined. Taking the ground access to Hong Kong International Airport (HKIA) as an example, this study aims to fill the previous research gaps by examining the equity of accessibility by public transport simultaneously considering different sets of route options and corresponding total travel costs. These routes have either the shortest travel time or the maximum time-saving benefit–monetary cost ratio. Results reveal spatial variation in the total travel cost, which reflects considerable horizontal inequity. The results, however, indicate that vertical equity exists because the total travel cost is positively correlated with median income level across different locations. In addition, the route that provides a reasonable benefit–cost ratio further improves the equity in accessibility to HKIA. The study illustrates the significance of simultaneous consideration of total travel costs and multiple routes in the assessment of accessibility equity. It also provides transferrable methods for evaluating transit equity. [ABSTRACT FROM AUTHOR]

This manuscript summarizes/reviews the current trends of ride-sharing services, which can be a supplement to or replacement of conventional transit services. It argues that smartcard data can be utilized to identify low-demand transit routes, where emerging ride-sharing services such as Uber and Lyft can play a role as a supplement to, or replacement of transit services along those routes. It outlines transferrable procedures and methods that can be used to process smartcard data and to define, identify and visualize low-demand transit routes. In an empirical study, it shows that some low-demand transit routes can probably be replaced by Uber at a lower level of overall costs. But the empirical study also indicates that the replacement can be challenging in reality given issues such as unwillingness or difficulties of local transit agencies and ride-sharing service providers in sharing financial information regarding their services, latent demand for private ride-sharing services, social equity and political/legal concerns over the introduction of private ride-sharing services into the transit-service market and usage of public funding for residents/riders to use private ride-sharing services. • It summarizes/reviews the current trends of ride-sharing services. • It outlines procedures and methods to identify low-demand transit services. • It shows how Uber can replace low-demand transit services with fewer overall costs. [ABSTRACT FROM AUTHOR]

Universities are where innovations, face-to-face interactions and social capital are commonplace. Nevertheless, often regarded as ‘the ivory tower’, universities cannot be separated from the social and economic transformations outside of them. Traffic, information and financial flows between universities and other locations can be used to reveal connections between the ivory tower and other locales. Therefore, this paper uses the weekday public transit smartcard records from 6 to 9 April 2010 (158,262 transit trips in total, including bus-only, bus plus subway and subway-only trips) to identify and profile the most popular destinations of student riders from the ‘985 universities’ (a short list of top universities designated by the Chinese Central Government in 1999) and associated transit trip flows in Beijing. It identifies destination hotspots for the 985 universities’ students in Beijing, allocates traffic volume to major roads and delineates the transit trips of students from each campus. The results indicate that there exist only weak ties and little movement between the top universities and the most disadvantaged areas. [ABSTRACT FROM PUBLISHER]

In 2011, the Ministry of Transport (MoT) of China announced to competitively select and fund at least 30 cities in their respective efforts of building a transit metropolis. Incentivized by MoT, many Chinese cities have started planning for a transit metropolis and even implementing related measures. This signifies some larger-than-ever government-led efforts towards the transit metropolis that we have heard of. Why did China/MoT initiate the transit metropolis program? Is the transit metropolis idea of MoT similar to what Robert Cervero defines in his book, which introduces the concept of transit metropolis and illustrates it using 12 exemplars? If not, why? Have Chinese cities followed the same principles or taken comparable measures proposed or identified by Cervero? Or, have they produced brand new principles or measures? If so, what is the implication? This article answers the above questions through literature review, interviews, surveys and case studies. It shows that MoT's idea of the transit metropolis differs notably from that of Cervero. Even though MoT proposes more universal and quantitative performance measures for a transit metropolis than Cervero, its perspectives and policies are still parochial. Local governments, nevertheless, have comparable principles or measures like Cervero. But compared to a transit metropolis exemplar such as Curitiba, they overlook issues such as the match between regional commuter sheds and the services/administrative boundaries of local transit-related entities, coordinated, regionalized transit services and fares, pedestrian-friendly streets and parking pricing strategies. The above indicate that more work is needed to better define, plan and implement a transit metropolis in China. [ABSTRACT FROM AUTHOR]

Using Beijing as an example, this research demonstrates that smartcard data can be used to (a) assemble the required data for excess commuting studies, and (b) visualise related results. Based on both smartcard and household travel survey data, we find that the theoretical minimum commute is considerably lower for bus users than for car users in Beijing. This suggests that there is a greater inter-mixing of jobs–housing functions (i.e., a better jobs–housing balance) associated with users of that mode compared to the corresponding land-use arrangement for car users, who locate further from the central area (Tian’anmen) than bus users. The commuting range for car users is 9.4 km greater than for bus users. Excess commuting is slightly higher for bus users (69.5%) than for car users (68.8%). Commuting capacity values are slightly lower for car users than for bus users, implying that car users consume less of their available commuting resources overall than bus users, albeit only marginally. [ABSTRACT FROM AUTHOR]

Abrupt socioeconomic changes have become increasingly commonplace. In face of these, both institutions and individuals must adapt. Against the backdrop of the COVID-19 pandemic, suddenness, scale, and impacts of which are unprecedented as compared to its counterparts in history, we first propose transferable measures and methods that can be used to quantify and geovisualize COVID-19 and subsequent events' impacts on metro riders' travel behaviors. Then we operationalize and implement those measures and methods with empirical data from Hong Kong, a metropolis heavily reliant on transit/metro services. We map out where those impacts were the largest and explores its correlates. We exploit the best publicly available data to assemble probable explanatory variables and to examine quantitatively whether those variables are correlated to the impacts and if so, to what degree. We find that both macro- and meso-level external/internal events following the COVID-19 outbreak significantly influenced of metro riders' behaviors. The numbers of public rental housing residents, public and medical facilities, students' school locations, residents' occupation, and household income significantly predict the impacts. Also, the impacts differ across social groups and locales with different built-environment attributes. This means that to effectively manage those impacts, locale- and group-sensitive interventions are warranted. • Propose measures and methods that can be used to quantify COVID-19 and subsequent events' impacts. • Operationalize and implement those measures and methods with empirical data from Hong Kong. • Examine quantitatively which variables are correlated to those impacts and if so, to what degree. [ABSTRACT FROM AUTHOR]

Equity and justice have long been central in transport policy. The emphasise on the importance of individuals' access to social and economic opportunities stresses the link between accessibility and concepts like agency and freedom of choice. It calls for a nuanced and comprehensive understanding of accessibility that considers specific contextual factors that limit people's transport choices, such as the design of public transport networks and services, government interventions, and competition between public transport companies. To promote people's potential mobility and freedom of choice, it is crucial to initially assess the spatial distribution of transport options. In this article, we synthesise the findings from existing scholarship on transport choice, reinforcing the need for (re)considering choice in transport equity. We propose a metric to evaluate the availability of transport choices by considering the trade-off between time and money. By analysing household survey responses on transport choices and transit service datasets, we investigate the spatial disparities in the availability of transport choices within a multimodal public transportation system in Hong Kong and explore how adjusting unappealing choices can potentially enhance transport equity. • Discuss transport equity issues with a relative understudied angle – transport choice. • Propose a metric to assess spatial equity of transport choices. • A realistic case study based on a multi-modal public transport network in Hong Kong. • Implications to transit choice provision and fare adjustment tactics. [ABSTRACT FROM AUTHOR]

This paper seeks to understand extreme public transit riders in Beijing using both traditional household surveys and emerging new data sources such as Smart Card Data (SCD). We focus on four types of extreme transit behaviors: public transit riders who (1) travel significantly earlier than average riders (‘early birds’); (2) ride in unusual late hours (‘night owls’); (3) commute in excessively long distance (‘tireless itinerants’); and (4) make significantly more trips per day (‘recurring itinerants’). SCD are used to identify the spatiotemporal patterns of these four extreme transit behaviors. In addition, household surveys are employed to supplement the socioeconomic background and tentatively profile extreme travelers. While the research findings are useful to guide urban governance and planning in Beijing, our methodology and procedures can be extended to understand travel patterns elsewhere. [ABSTRACT FROM AUTHOR]

Public transport with high levels of patronage is the cornerstone of a sustainable city. Passengers' feelings of safety shapes an individuals' decision to utilise public transport that are informed in large part by the other people with which the transit stations and public transit trips are shared. Some of these people are unknown to us but considered – familiar strangers – in that we visually recognise the individuals but have never spoken to them. Our empirical understanding of this subtle yet important social phenomena known to impact sense of community, place attachment and feelings of safety remain in their infancy but with emergence of disaggregate sources of big data bourne from smart card technologies there exists new opportunities to measure and visualise potential familiar strangers in transit networks. The aim of the current study is to develop a new measurement framework that moves beyond existing work that measures familiar strangers via a single volumetric measure and introduce a suite of metrics capturing the full scope of the social phenomena within a transit network. Our measurement framework and associated metrics are operationalised using smart card data from Brisbane, Australia. Results hold implications for policy and planning, and it is hoped that the framework will be redeployed across other situational and cultural contexts forming a growing set of comparative studies. • A new measurement framework for familiar stranger encounters in transit networks. • Measure and visualise spatial-temporal dynamics of familiar stranger encounters. • Explore patterns of familiar stranger encounters across both weekdays and weekends. • Explore patterns of familiar stranger encounters by transit passenger type. [ABSTRACT FROM AUTHOR]

Transit accessibility should take transit timetable into account and be time-dependent. The reason is that the maximum passenger carrying capacity of a transit station is determined by the scheduled timetable. In addition, passengers always choose departure time according to their own need, which varies with time. Based on the traditional two-step floating catchment area (2SFCA) and gravity method, this paper proposes two new methods to evaluate transit accessibility. The proposed methods are implemented to evaluate the bus accessibility of Xiamen City, China. According to the local bus timetable, a typical workday is divided into three periods. Within each time period, bus travel supply-to-demand ratios by station are calculated and then aggregated into the traffic analysis zone (TAZ). The empirical findings show that fluctuations in travel demand and the passenger carrying capacity of bus stations in different time periods make the bus accessibility significantly differ throughout the city. They also show that bus accessibility based on the extended 2SFCA model are equivalent to that based on the extended gravity model, when the total demand is relatively lower than the total passenger carrying capacity of a bus station. [ABSTRACT FROM AUTHOR]