The factors in residents' mobility in rural towns of China: Car ownership,road infrastructure and public transport services

The improvement of rural people's mobility in developing countries has informed many policies. Still, debates remain on which policies are efficient, for instance, building more roads, providing public transport or promoting car ownership. The empirical evidence for these debates at the national level remains scarce. As a result, this paper aims to provide fresh evidence for discussions by examining residents' mobility in China using nationwide survey data with 12,524 respondents from 119 rural towns. The results of the analysis show car ownership is the most significant factor influencing rural people's mobility than other factors. Higher car ownership relates to a higher travel frequency to counties or cities. Other kinds of transport vehicles (i.e. electric cars, motorcycles and electric bikes) also have positive but relatively weaker impacts on rural mobility. For public transport, it is more accessible to access bus stops, which encourages travel to higher-order centres rather than increasing the frequency of county bus services. The accessibility of high-quality road systems tends to have a negative influence and has combined effects with levels of local services. People from towns with insufficient local services and poor access to highways travel the most frequently to higher-order centres. This study highlights the critical role of road investments and car ownership enhancement policies in improving mobility. Moreover, this study also underscores the supplemental role of public transport services given the current low car ownership rates in rural towns of China and the global consensus on sustainable green transport development. It highlights the importance of engaging eco-friendly and locally adaptive transport alternatives, such as electric cars and electric bikes. It also calls for a rational distribution of bus stops and more flexible, convenient, and physically accessible public transport and carshare modes in rural China.     

Exploring the effectiveness of bus rapid transit a prototype agent-based model of commuting behavior

The introduction of Bus Rapid Transit (BRT), typically involving the use of exclusive bus lanes and related bus priority measures, is increasingly advocated as a flexible and cost-effective way of improving the attractiveness of public transit in congested urban areas by reducing travel times and variability. These schemes typically involve the reallocation of road space for exclusive use by buses, presenting commuters with potentially competing incentives: buses on BRT routes can run faster and more efficiently than buses running in general traffic, potentially attracting commuters to public transit and reducing congestion through modal shift from cars. However, a secondary impact may also exist; remaining car users may be presented with less congested road space, improving their journey times and simultaneously acting as an incentive for some bus-users to revert to the car. To investigate the potential for these primary and secondary impacts, we develop a prototype agent-based model to investigate the nature of these interactions and how they play out into system-wide patterns of modal share and travel times. The model allows us to test the effects of multiple assumptions about the behaviors of individual agents as they respond to different incentives introduced by BRT policy changes, such as the implementation of exclusive bus lanes, increased bus frequency, pre-boarding ticket machines and express stops, separately and together. We find that, under our assumptions, these policies can result in significant improvements in terms of individual journey times, modal shift, and length of rush hour. We see that the addition of an exclusive bus lane results in significant improvements for both car users and bus riders. Informed with appropriate empirical data relating to the behavior of individual agents, the geography and the specific policy interventions, the model has the potential to aid policymakers in examining the effectiveness of different BRT schemes, applied to broader environments.     

Grocery store accessibility: Different metrics – Different modal disparity results and spatial patterns

Most accessibility studies focus on within transport mode travel performance variations. However, modal accessibility disparity analysis adds value to the single-mode analysis by assessing the interaction between different transport modes and land use. A review of modal disparity studies shows that different accessibility metrics lead to different results, and so it is unclear how this impacts modal accessibility disparity variation. Moreover, the correspondence of the disparity spatial pattern between the different metrics is unclear. This research examines how three typical accessibility metrics (closest facility, cumulative opportunity, space-time constrained) impact modal disparity of grocery store accessibility in Warsaw, Poland. Further, local indicators of spatial association are used to identify areas of similarity and difference between the metrics. This study finds that cumulative opportunities during non-rush hours indicate the best car advantage for all travel times but indicate the best transit advantage during rush hours for 15 min. Generally, the space-time metric indicates better transit accessibility than the closest facility metric which in turn shows better transit accessibility than cumulative opportunities. The city center has significant spatial similarity while peripheral, especially dense, areas have significant spatial difference. Similarity areas have higher transit stop and population densities, while difference areas have average-to-low stop, population, road and store densities.     

Longitudinal macro-analysis of car-use changes resulting from a TOD-type project: The case of Metro do Porto (Portugal)

Transit-oriented development has been widely studied in recent years as a means to reduce car trips and promote sustainable transport modes. However, longitudinal studies on the matter are still rare. This paper contributes to longitudinal research of Transit-Oriented Development (TOD) effects on travel behavior by analyzing the evolution of the number of car trips after the implementation of a light-rail metro system in the Porto region (Portugal). As Metro do Porto is a large infrastructure project (a metro network of 67 km), we relied on a macro-analysis performed at the civil parish level. Changes in the number of car trips are evaluated using a difference-in-differences model, extended to a spatial model to account for the metro's spillover effects. These effects became obvious as metro ridership is reported not only in the directly metro-served parishes but also in adjacent non-served parishes. The results highlight the importance of the metro system in reducing the number of car trips, and this effect is visible not only in metro-served parishes but also in the neighboring ones, which are not directly served by the new transport system. Furthermore, we compare the performance of parishes predominantly served with TOD stations to those with transit-adjacent (TAD) and park-and-ride (P&R) stations. We conclude that both station types can reduce the number of car trips, yet only TOD parishes generated significant spillover effects. The importance of other potentially influential factors like building density or socio-economic characteristics is also discussed.     

Choice behavior of tourism destination and travel mode: A case study of local residents in Hangzhou,China

The social and economic growth as result of promoting the rapid development of tourism in China has brought tremendous pressure on the urban transportation systems. Research of travel behavior concerning the characteristics of tourists has provided effective information for transportation planning. Due to different city plans, public transportation system design, car parking design and management, etc., the local situation in developed countries differs from the counterpart in China. However, little research has studied the factors influencing the choice of travel destinations in tourism. The research aims to study the tourism destination and mode choice behavior of tourists and provides suggestions to improve tourism transportation service system. An online questionnaire survey is used to collect data including the travel characteristics and personal attributes of local tourists in different holidays in Hangzhou, China. A multinomial logit model is constructed with the trip destination set as the dependent variable. Results show that age, residential type, car ownership, companion type and holiday length have a significant impact on destination choice. To determine what influences modal choice for such trips, a second logit model is established with travel mode set as the dependent variable with the explanatory variables of age, gender, companion type, car ownership, holiday length and travel destination found to be significant. The results demonstrated that people aged 26 to 44 prefer suburban areas, and they are the main group driving to their travel destination. Public transport use frequency decreases when the destination is located outside of the main tourist area. Finally, suggestions have been proposed to mitigate the congestion and parking problem based on model analysis from the perspective of the bus line setting, transfer improvements, and the policy to limit cars, respectively.     

Disentangling the behavioural side of the first and last mile problem: the role of modality style and the built environment

The first and last mile (FLM) problem, namely the poor connection between trip origins or destination and public transport stations, is a significant obstacle to sustainable transportation as it is likely to encourage the use of cars for FLM travel, if not for the entire trip. This study examines the role of modality style and built environment in FLM mode choice behaviour, in order to identify the key features that might invoke a travel mode shift from cars to more sustainable travel options for both mandatory and discretionary trips. More specifically, this study draws on disaggregate data from the South East Queensland household travel survey and presents a latent class choice model to unravel modality style groups. Results reveal two distinct individual-level modality style groups: (1) driving and walking oriented; (2) multimodal travellers. Individuals in the second modality style group were found to be relatively inelastic to FLM travel time for mandatory trips, while individuals in the first group were largely unaffected by built environment characteristics and highly habitual in their mode choice behaviour for both mandatory and discretionary trips. Home residence environments with high road intersection density and public transport accessibility, and home residence environments with diverse land use mix, respectively encourage individuals within the second modality style to walk for mandatory trips, and discretionary trips. To this end, when place-based policies seek to change certain built environment features, individuals in the second modality style are more likely to shift their preference from cars to more sustainable modes. Finally, our findings have practical planning implications in targeting mode shift through highlighting the importance of considering the intersection of individual modality style in a given locale and mode choice behaviour. More specifically, our findings advocate for place-based policies that seek to target particular locales with the certain modality style deemed to be more predisposed to adopting a mode shift.     

Advance transit oriented development typology: case study in Brisbane,Australia

Internationally, transit oriented development (TOD) is characterised by moderate to high density development with diverse land use patterns and well connected street networks centred around high frequency transit stops (bus and rail). Although different TOD typologies have been developed in different contexts, they are based on subjective evaluation criteria derived from the context in which they are built and typically lack a validation measure. Arguably there exist sets of TOD characteristics that perform better in certain contexts, and being able to optimise TOD effectiveness would facilitate planning and supporting policy development. This research utilises data from census collection districts (CCDs) in Brisbane with different sets of TOD attributes measured across six objectively quantified built environmental indicators: net employment density, net residential density, land use diversity, intersection density, cul-de-sac density, and public transport accessibility. Using these measures, a Two Step Cluster Analysis was conducted to identify natural groupings of the CCDs with similar profiles, resulting in four unique TOD clusters: (a) residential TODs, (b) activity centre TODs, (c) potential TODs, and (d) TOD non-suitability. The typologies are validated by estimating a multinomial logistic regression model in order to understand the mode choice behaviour of 10,013 individuals living in these areas. Results indicate that in comparison to people living in areas classified as residential TODs, people who reside in non-TOD clusters were significantly less likely to use public transport (PT) (1.4 times), and active transport (4 times) compared to the car. People living in areas classified as potential TODs were 1.3 times less likely to use PT, and 2.5 times less likely to use active transport compared to using the car. Only a little difference in mode choice behaviour was evident between people living in areas classified as residential TODs and activity centre TODs. The results suggest that: (a) two types of TODs may be suitable for classification and effect mode choice in Brisbane; (b) TOD typology should be developed based on their TOD profile and performance matrices; (c) both bus stop and train station based TODs are suitable for development in Brisbane.     

Give public transit a chance: A comparative analysis of competitive travel time in public transit modal share

Extensive research has found that people are more likely to choose the transport alternative which offers shorter travel time. But few studies approached the role of travel time across different transport alternatives and cities. This research assesses the influence of competitive travel time between car and public transit in public transit modal share for commute trips. São Paulo, New York, and Tokyo were selected to perform the analysis. A Fractional Logistic Regression in the binary form was drawn, and a competitive travel time index was calculated based on the Car/Public transit travel time ratio weighted by the number of the employed population at the origin and jobs at destinations in the absence of an Origin-Destination matrix. Findings suggest that, though car ownership was identified as the major factor, Car/Public transit travel time ratio is positively associated with the increase of public transit modal share. Furthermore, the Car/Public transit travel time ratio effect in public transit modal share consistently increases as people get increased access to cars.     

Structures of commitment in mode use: a comparison of Switzerland, Germany and Great Britain

Travellers commit themselves to particular behaviours through the ownership of cars and season tickets. They trade a large one-off payment for low or zero marginal cost at the point of use. It can be assumed that these commitments influence travel behaviour. To the knowledge of the authors there is no literature which addresses the choice between the commitment to the one or the other mode and its impacts on travel behaviour.The paper presents models using structural equation modelling to test a-priori hypotheses on the paths linking car-availability, season-ticket-ownership and modal usage. Modal usage is operationalised as the number of trips by car, public transport, or as the distances travelled by car or public transport. The models are based on three different surveys: Switzerland, Germany and Great Britain. The results confirm the dominance of car-availability, which drives the other variables, but the relationships are more complicated than generally assumed.     

Changes in car and bus usage amid the COVID-19 pandemic: Relationship with land use and land price

This study aimed to explore the impacts of COVID-19 on car and bus usage and their relationships with land use and land price. Large-scale trip data of car and bus usage in Daejeon, South Korea, were tested. We made a trip-chain-level data set to analyze travel behavior based on activity-based travel volumes. Hexagonal cells were used to capture geographical explanatory variables, and a mixed-effect regression model was adopted to determine the impacts of COVID-19. The modeling outcomes demonstrated behavioral differences associated with using cars and buses amid the pandemic. People responded to the pandemic by reducing their trips more intensively during the daytime and weekends. Moreover, they avoided crowded or shared spaces by reducing bus trips and trips toward commercial areas. In terms of social equity, trips of people living in wealthier areas decreased more than those of people living in lower-priced areas, especially trips by buses. The findings contribute to the previous literature by adding a fundamental reference for the different impacts of pandemics on two universal transportation modes.     

Urban rail systems investments: an analysis of the impacts on property values and residents’ location

Light rail, metro and other urban rail transit systems can play a significant role in improving the attractiveness and quality of urban public transport. They can influence the attractiveness of locations near the stations and improve accessibility for these locations. Furthermore urban rail can improve a location’s attractiveness by its image effect: it makes a station appear modern and dynamic, and thus raises the status of this location.This paper summarises findings on the land-use and economic impacts of the urban rail system of the city of Naples over time and space. It examines changes in residential and non-residential (offices and retail) property prices around the newly built stations between 2001 and 2008 as well as the changes in the number of residents for the same station catchment areas. Ad hoc station control areas have been specified in order to compare the results of these changes. Results show that values in station control areas are lower than those of those of the stations catchment areas.     

Determinants of transport mode choice: a comparison of Germany and the USA

Germany and the USA have among the highest motorization rates in the world. Yet Germans make a four times higher share of trips by foot, bike, and public transport and drive for a 25% lower share of trips as Americans. Using two comparable national travel surveys this paper empirically investigates determinants of transport mode choice in Germany and the USA.In both countries higher population density, a greater mix of land-uses, household proximity to public transport, and fewer cars per household are associated with a lower share of trips by automobile. However, considerable differences remain: all groups of society in America are more car-dependent than Germans. Even controlling for dissimilarities in socio-economic factors and land-use, Germans are more likely to walk, cycle, and use public transport. Moreover, Americans living in dense, mixed-use areas, and close to public transport are more likely to drive than Germans living in lower density areas, with more limited mix of land-uses, and farther from public transport. Differences in transport policy that make car travel slower, more expensive, less convenient, and alternatives to the automobile more attractive in Germany may help account for the remaining differences.     

Public bicycle as a feeder mode to rail transit in China: The role of gender,age, income,trip purpose,and bicycle theft experience

A marriage between public bicycle and rail transit presents new opportunities for sustainable transportation in Chinese cities. To examine determinants of public bicycle usage for rail transit access, an intercept survey of feeder mode choice among rail transit users was conducted near rail stations in Nanjing, China. Mode choice models were estimated with five feeder mode alternatives, including car, bus, walk, private bike, and public bike. By differentiating between public and private bicycle modes in the mode choice models, the study reveals the effects of personal demographics, trip characteristics, and station environments on public bicycle usage for rail transit access. Results show that female, older, and low-income rail commuters are less likely to use public bicycle to access rail transit. Rail commuters with bicycle theft experience and making school- or work-related trips are more likely to use public bicycle to access rail transit. Land use variables are largely insignificant in this study except that density shows a positive relationship with walking to rail transit. The results on demographic differences raise equity concerns when it comes to investing in public bicycle systems. Policy implications are discussed for Chinese cities to equitably boost public bicycle integration with rail transit.     

Exploring the impact of built environment factors on the use of public bikes at bike stations: Case study in Zhongshan,China

Many countries have implemented public bike systems to promote sustainable public transportation. Despite the rapid development of such systems, few studies have investigated how built environment factors affect the use of public bikes at station level using trip data, taking account of the spatial correlation between nearby stations. Built environment factors are strongly associated with travel demand and play an important role in the success of public bike systems. Using trip data from Zhongshan's public bike system, this paper employed a multiple linear regression model to examine the influence of built environment variables on trip demand as well as on the ratio of demand to supply (D/S) at bike stations. It also considered the spatial correlations of PBS usage between nearby stations, using the spatial weighted matrix. These built environment variables mainly refer to station attributes and accessibility, cycling infrastructure, public transport facilities, and land use characteristics. Generally, we found that both trip demand and the ratio of demand to supply at bike stations were positively influenced by population density, length of bike lanes and branch roads, and diverse land-use types near the station, and were negatively influenced by the distance to city center and the number of other nearby stations. However, public transport facilities do not show a significant impact on both demand and D/S at stations, which might be attributed to local modal split. We also found that the PBS usage at stations is positively associated with usage at nearby stations. Model results also suggest that adding a new station (with empty capacity) within a 300 m catchment of a station to share the capacity of the bike station can improve the demand-supply ratio at the station. Referring to both trip demand models and D/S models, regression fits were quite strong with larger R² for weekdays than for weekends and holidays, and for morning and evening peak hours than for off-peak hours. These quantitative analyses and findings can be beneficial to urban planners and operators to improve the demand and turnover of public bikes at bike stations, and to expand or build public bike systems in the future.     

Exploring the spatial variations of transfer distances between dockless bike-sharing systems and metros

Dockless bike-sharing is emerging as a convenient transfer mode for metros. The riding distances of bike-sharing to or from metro stations are defined as transfer distances between dockless bike-sharing systems and metros, which determine the service coverages of metro stations. However, the transfer distances have rarely been studied and they may vary from station to station. Therefore, this study aims to explore the influencing factors and spatial variations of transfer distances between dockless bike-sharing systems and metros. First, a catchment method was proposed to identify bike-sharing transfer trips. Then, the Mobike trip data, metro smartcard data, and built environment data in Shanghai were utilized to calculate the transfer distances and travel-related and built environment variables. Next, a multicollinearity test, stepwise regression, and spatial autocorrelation test were conducted to select the best explanatory variables. Finally, a geographically weighted regression model was adopted to examine the spatially varying relationships between the 85th percentile transfer distances and selected explanatory variables at different metro stations. The results show that the transfer distances are correlated with the daily metro ridership, daily bike-sharing ridership, population density, parking lot density, footway density, percentage of tourism attraction, distance from CBD, and bus stop density around metro stations. Besides, the effects of the explanatory variables on transfer distances vary across space. Generally, most variables have greater effects on transfer distances in the city suburbs. This study can help governments and operators expand the service coverage of metro stations and facilitate the integration of dockless bike-sharing and metros.     

Exploring the trip chaining behaviour of public transport users in Melbourne

This paper explores trip chaining behaviour of Melbourne residents using evidence from a household travel survey. The research literature has suggested that trip-making behaviour has grown increasingly complex as modern life has become busier and people grow time-poor. Complex trip chains have been said to require flexible travel modes, and for this reason some research has suggested that public transport is limited in this regard compared to the private car. Results of this study show that between 1994 and 1999 the complexity of trip chains was relatively stable and the complexity of chains was found to be larger for rail and tram than for car-based trips. Disaggregate analyses compare the complexity of chains based on work versus non-work chains, the purpose of stops on the chain, and whether the chain entered the central city of Melbourne or not. Overall these findings suggest a less bleak outlook for public transport ridership in a travel future which is said to be becoming more complex.     

Analysing the spatial-temporal characteristics of bus travel demand using the heat map

As the basic travel service for urban transit, bus services carry the majority of urban passengers. The characterisation of urban residents' transit trips can provide a first-hand reference for the evaluation, management and planning of public transport. Over the past two decades, data from smart cards have become a new source of travel survey data, providing more comprehensive spatial-temporal information about urban public transport trips. In this paper, a multi-step methodology for mining smart card data is developed to analyse the spatial-temporal characteristics of bus travel demand. Using the bus network in Guangzhou, China, as a case study, a smart card dataset is first processed to quantitatively estimate the travel demand at the bus stop level. The term ‘bus service coverage’ is introduced to map the bus travel demand from bus stops to regions. This dataset is used to create heat maps that visualise the regional distribution of bus travel demand. To identify the distribution patterns of bus travel demand, two-dimensional principal component analysis and principal component analysis are applied to extract the features of the heat maps, and the Gaussian mixture model is used for the feature clustering. The proposed methodology visually reveals the spatial-temporal patterns of bus travel demand and provides a practical set of visual analytics for transit trip characterisation.     

Environmental benefits of air–rail intermodality: The example of Madrid Barajas

The environmental impact of transport is a growing issue in transport infrastructure planning. The construction of a high-speed rail station at the Madrid Barajas Airport in Spain is an example of the integration of different transportation modes, with expected environmental benefits. We construct a model to assess modal choice and environmental benefits. The results show that with high-speed rail the number of people choosing air travel and the private car is reduced leading to important environmental benefits: a reduction of close to 5 kg of CO₂ per passenger, or 10% of all emissions on the corridor. Our results also show that increasing the cost of using the private car is picked up by air transport rather than high-speed rail, leading to an increase in total emissions.     

Interrelations between travel mode choice and trip distance: trends in Germany 1976–2002

In recent decades, trends in travel behaviour have been characterised by increasing trip distances and a modal shift towards the private car. This paper reports findings from longitudinal analyses of the German nation-wide travel survey KONTIV for the period 1976–2002. It focuses on travel mode choice, subdivided by distance categories, and also takes car availability and city size into account. In addition, trends in car availability itself are examined by city size categories. The results indicate that even within the same distance categories car use has considerably increased. In some cases bicycle use has increased as well. Gains in the use of the private car are mainly at the expense of trips on foot and by public transport. Accordingly, the shift in modal split towards the car is not (only) caused by increasing trip distances but took place even within distance classes. Once car availability is taken into account, the modal shifts appear to be considerably weaker. This suggests that once car availability is held constant the decision rationales of mode choice for a certain trip distance have remained relatively stable. The increase in motorisation over the study period was considerably weaker in large cities than in small towns, although the cities started from a lower level in the 1970s. Thus, the motorisation divide between cities on the one hand, and suburban and rural areas on the other hand has become ever wider. For travel mode choice, the picture is similar. What is more, the results suggest that even car owners are more inclined to walk a given distance in the cities than in small towns, even more so if they live in a central urban area. The built environment, thus, appears to have a strong impact on whether an available car is used or not.     

Impacts on travel behaviour of Greater Manchester’s light rail investment (Metrolink Phase 1): evidence from household surveys and Census data

Household survey data from 1990 and 1993 and Census data from 1991 and 2001 are used to detect some short and medium term impacts on travel of the Metrolink light rail services which opened in 1992. Particular attention is paid to research design issues to try to isolate Metrolink’s impacts from those of other influences on travel behaviour. In the short term a more marked decline in the frequency of bus use is found in the Metrolink corridor compared with conventional rail and ‘no rail’ corridors. Changes in the frequency of rail use are more prominent in the Metrolink corridor, both to the highest frequency use but also to lower frequency use. Higher frequency rail use tends to be associated with respondents who have limited or no car availability, who are in employment, who are of non-manual social class and who are aged 18–44 years. Metrolink appears to have attracted at least as many former car users as former bus users, but the former car users tend to use the light rail services less frequently. Census commuting data suggest that, in the medium term, Metrolink has increased rail’s share of trips, especially to the city centre, contributed to the declining share of bus trips and may have helped to restrain work trips by car.