Millennials,built form,and travel insights from a nationwide typology of U.S. neighborhoods

We examine the relationship between the built environment and the travel of Millennials in the United States. We develop a neighborhood typology to characterize the built environment and transportation networks in almost every U.S. census tract, allowing us to identify possible synergistic and/or threshold effects on travel. We measure travel behavior in two ways: (1) using a multi-faceted traveler typology created using latent class analysis, and (2) by measuring the vehicle miles of travel among people in each of these traveler types. This dual approach allows us to distinguish between the built environment changes needed to encourage travel by modes other than driving, and those needed to reduce vehicle miles traveled among drivers. Using a multinomial logistic regression, we find that travel patterns are relatively stable along much of the urban-rural continuum, everything else equal. Driving was substantially lower only in “Old Urban” neighborhoods, where densities, job access, and transit service are dramatically higher than in all other neighborhood types. This finding implies that dramatic changes in the built environment—doubling or even tripling development density or transit service—may do little to get young people out of their cars when initial densities or transit services are low, as they are in most of the U.S. Conversely, reducing vehicle miles traveled among drivers appears to require more modest built form changes, a finding that offers some room for optimism among those concerned with auto dependence.     

Predicting transit mode choice of New Jersey workers commuting to New York City from a stated preference survey

This study examines transit mode choice preferences of New Jersey commuters traveling to New York City (NYC) with the objective of assisting trans-Hudson ferry service planning on the basis of variables significantly affecting mode choice. A stated preference survey was conducted to collect data from a total of 2134 respondents who commute from northern New Jersey to NYC. A mixed multinomial logit model (MMLM) with random coefficients was used to analyze the data. The study considered the choice between four transit modes—ferry, PATH train, bus, and commuter rail—all of which can be used to cross the Hudson River to travel from New Jersey to NYC. Essential model results are presented for all four modes, but detailed results are discussed for only the ferry, PATH, and bus modes. Model results indicate that commuters' choices are affected not only by travel time and cost for the segment of the journey that crosses the Hudson River, but also reliability and comfort during that segment, number of access modes required by the journey, and travel time and cost of trips from home to stations/terminals before crossing the river. The results also show that commuters' attachment to the modes they currently use serves as a barrier to switching to other modes. The most important takeaway from this research for transit service planning is that there is a need to consider the attributes of both individual trip segments as well as entire journeys between commuters' home and work when exploring changes to transit service characteristics.     

Equity of transit connectivity in Tennessee cities

Federal and state agencies focus on providing captive users in mobility-vulnerable population groups with access to public transit resources. One challenge to the provision of equitable access is quantifying equity-oriented metrics for public transit service. This paper utilizes an approach that utilizes the available spatial demographic data and transit network characteristics to compute multimodal transit connectivity and equity. This method is exemplified by analyzing transit connectivity for three metropolitan cities in the state of Tennessee in the United States and overlapping that connectivity on demographic data. Results indicate that the distribution of transit services among vulnerable populations varies within and between cities. The case studies illustrate how this methodology can be used by public agencies to assess the performance of transit systems and to identify the distribution of these systems among various groups to improve the equity of transit connectivity.     

Bergen light rail – Effects on travel behaviour

Bergen is the second most populous city in Norway (280,000 inhabitants) and is situated along the west coast of the country. In 2010, the city reintroduced tram service with the opening of a new light rail line, after a gap of 45 years. This study documents the increase in public transit use in Bergen, both in terms of volume and market share, since the line was opened. Furthermore, it explores the effects of light rail transit on travel behaviour using Bergen as a case city. These goals are accomplished by combining and analysing data from different sources, including five travel surveys, and other data concerning building stock, population, business activity, commuting and traffic counts. The study identifies four potential driving forces for changes in travel behaviour: (1) the introduction of the light rail; (2) a new high-frequency bus network; (3) increased rates in the toll cordon system; and (4) changes in the urban structure. The study concluded that the introduction of light rail was the main driving force behind the growth in public transit use. The study also highlighted that transit use was highest in areas served by the light rail. The effects of the light rail investments are reinforced by an optimal location of the line with respect to potential users.     

Optimal allocation of protective resources in urban rail transit networks against intentional attacks

This paper advances the field of network interdiction analysis by introducing an application to the urban rail transit network, deploying protective resources against intentional attacks. The resource allocation problem for urban rail transit systems is considered as a game between two players, the attacker interdicting certain rail stations to generate greatest disruption impact and the system defender fortifying the network to maximize the system’s robustness to external interdictions. This paper introduces a game-theoretic approach for enhancing urban transit networks’ robustness to intentional disruptions via optimally allocating protection resources. A tri-level defender–attacker–user game-theoretic model is developed to allocate protective resources among rail stations in the rail transit network. This paper is distinguished with previous studies in that more sophisticated interdiction behaviors by the attacker, such as coordinated attack on multiple locations and various attacking intensities, are specifically considered. Besides, a more complex multi-commodity network flow model is employed to model the commuter travel pattern in the degraded rail network after interdiction. An effective nested variable neighborhood search method is devised to obtain the solution to the game in an efficient manner. A case study based on the Singapore rail transit system and actual travel demand data is finally carried out to assess the protective resources’ effectiveness against intentional attacks.     

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.     

Not minding the gap: Does ride-hailing serve transit deserts?

Transit has long connected people to opportunities but access to transit varies greatly across space. In some cases, unevenly distributed transit supply creates gaps in service that impede travelers' abilities to cross space and access jobs or other opportunities. With the advent of ride-hailing services like Uber and Lyft, however, travelers now have a new potential to gain automobility without high car purchase costs and in the absence of reliable transit service. Research remains mixed on whether ride-hailing serves as a modal complement or substitute to transit or whether ride-hailing fills transit service needs gaps. This study measures transit supply in Chicago and compares it to ride-hailing origins and destinations to examine if ride-hailing fills existing transit service gaps. Findings reveal clustering of ride-hailing pickups and drop-offs across the City of Chicago, but that the number of ride-hailing pickups and drop-offs was most strongly associated with high neighborhood median household income rather than measures of transit supply. In bivariate analyses, transit service was not associated with ride-hailing trip ends. But after controlling for neighborhood socioeconomic status, transit dependency, population density, and employment density, we found fewer ride-hailing trips in neighborhoods where bus service dominated and significantly more ride-hailing trips where rail service was prevalent. Patterns were slightly different for overnight weekend ride-hailing pick-ups, where higher transit density predicted a greater number of trips in nearby tracts. Additional research and policy is needed to ensure that ride-hailing services provide travel options to those who need them the most and fill transit gaps in low-income communities when options to increase service are limited.     

Constructing a mixed-logit model with market positioning to analyze the effects of new mode introduction

This study aims to investigate how the introduction of high-speed rail (HSR) influences traveler choice behavior and the market structure in the western corridor of Taiwan. A new mixed-logit model with factor decomposition is constructed to analyze the market positioning of the existing modes and HSR; the data is collected using the stated preference method. The empirical results show that travel cost is the major factor in market positioning. After the introduction of HSR, travelers’ mode preference did not change, whereas locations across modes on the market-positioning map as well as some coefficients of the explanatory variables changed.     

Assessing intercity multimodal choice behavior in a Touristy City: A factor analysis

This paper investigates influential factors in passengers' intercity multimodal choice behaviors in a touristy city. By collecting large individual-level data through a comprehensive field survey that was carried out at the major transportation hubs in Xi'an, China, we studied four travel modes of the surveyed travelers in this touristy city, including air, high-speed rail, traditional passenger train, and express bus. For factor analysis, 12 variables, including not only individual-related attributes but also ticketing methods and mental perceptions, were used as the independent factors after the correlation analysis and collinearity test. The regression relationships between the travel mode choice and the independent variables were studied using Bayesian multinomial logistic regression. The results indicate that those 12 factors have significant and various influences on passengers' mode choices. In particular, travel distance, fare rate, intercity travel time per hundred kilometers, quality of service, accessibility of transportation hubs, and ticketing methods have influential contributions for explaining the choice decision-makings. The findings demystify the effects of several unexplored factors in intercity multimodal travel choice behaviors and shed new light on formulating traffic management strategies for service providers and decision-makers in practice.     

城市轨道交通智慧乘客综合服务平台方案研究与设计

城市轨道交通乘客服务相关系统和设施设备是提升乘客出行满意度的关键要素。以挖掘数据潜能、释放资源价值为切入点,整合相关系统业务流程,在研究国内城市轨道交通乘客服务智能化发展的基础上,从提升服务体验、优化运营管理、挖掘商业价值3个维度分析乘客服务存在的问题,提出基于中台技术的智慧乘客综合服务平台方案。基于信息资源整合和业务能力抽取,设计乘客画像、出行支持、客流特征、场景模型4大业务中台模块,满足乘客购票、站内引导、资讯获取等方面的服务需求,实现乘客服务与车站信息的协同共享能力。通过设计智能票务、无人客服中心、智能导向、精准营销等典型场景应用,提升服务体验与运营管理水平,促进商业资源开发以满足日益增长的乘客消费需求。     

Immigrant settlement patterns,transit accessibility,and transit use

Public transit is immensely important among recent immigrants for enabling daily travel and activity participation. The objectives of this study are to examine whether immigrants settle in areas of high or low transit accessibility and how this affects transit mode share. This is analyzed via a novel comparison of two gateway cities: Sydney, Australia and Toronto, Canada. We find that in both cities, recent immigrants have greater levels of public transit accessibility to jobs, on average, than the overall population, but the geography of immigrant settlement is more suburbanized and less clustered around commuter rail in Toronto than in Sydney. Using logistic regression models with spatial filters, we find significant positive relationships between immigrant settlement patterns and transit mode share for commuting trips, after controlling for transit accessibility and other socio-economic factors, indicating an increased reliance on public transit by recent immigrants. Importantly, via a sensitivity analysis, we find that these effects are greatest in peripheral suburbs and rural areas, indicating that recent immigrants in these areas have more risks of transport-related social exclusion due to reliance on insufficient transit service.     

Walking to transit: An unexpected source of physical activity

Using data from a regional survey carried out in Montreal, this paper shows empirical evidence that modal shift from car to transit contributes to the volume of daily physical activity. First, the paper presents a method to calculate the walking distance related to transit trips, and a totally disaggregate trip assignment model. The walking distance involved in every transit trip is then associated to the individuals' characteristics to estimate the number of steps made by the population in the whole transit system.Results show that, in average, a transit trip involves 1250 steps, required to access and egress the network as well as to transfer between routes or modes. Thus, a round trip represents 2500 steps, which account for 25% of the recommended volume of physical activity per day. Hence, analysis shows that the volume of walking varies according to attributes of the traveler (general decrease with age, higher for men) and of the trip (study and work trip involve more steps, the use of train generates more steps). A regression model confirms that these variables significantly affect the number of steps involved in transit trips. Such positive outcome, for the traveler himself, is an innovative argument to promote the use of transit that is also aligned with current sustainable transportation goals.     

A study on travelers' transport mode choice behavior using the mixed logit model: A case study of the Seoul-Jeju route

This study is to analyze passengers' choice of the mode of transportation when air transportation is in competition with high speed rail (HSR). The Seoul-Jeju route analyzed as an empirical case study, in which the construction of an undersea tunnel to connect Seoul and Jeju city by HSR has been considered. The study also included two new variables, ‘safety of transportation’ and ‘availability of duty free shopping’ in addition to traditional transport choice variables such as travel time, travel costs and frequency of service to reflect special characteristics of the market. As data gathering tools, SP techniques and mixed logit model, for analytical methodology, were utilized. The authors found that the goodness of fit of the models was improved with new variables. The models also showed that the characteristics of business passengers and leisure passengers in choosing the mode of transportation were different. Business passengers were apt to choose a safety secured mode of transportation regardless of fare while leisure passengers preferred to use duty free shops more than business passengers.     

How does the propensity of living near rail transit moderate the influence of rail transit on transit trip frequency in Xi'an?

Many cities have made massive investments on rail systems to substitute transit for driving. Some studies have considered the confounding effect of attitudes in the connections between rail transit and travel behavior. However, they often focused on the average effect of rail transit and assumed that individuals' responses to transit improvements do not vary by their tastes. Using the 2014 data from Xi'an in China, this study explores the interaction effect between metro transit (heavy rail) and the propensity (i.e., predicted probability) of living in neighborhoods with metro transit on transit use. The propensity is positively associated with commute by metro transit and bus. Further, individuals with a strong propensity use transit equivalently no matter whether they live near metro transit, but metro transit tends to promote transit commute for those with a weak propensity of living near metro transit. Overall, building a rail line helps enhance transit ridership. Planners should also consider the variation in responses by individuals with different tastes when using policies to shape urban travel.     

Behavioral intentions of public transit passengers—The roles of service quality,perceived value,satisfaction and involvement

Understanding the behavioral intentions of public transit passengers is important, because customer loyalty is seen as a prime determinant of long-term financial performance. This study highlights such behavioral intentions and explores the relationships between passenger behavioral intentions and the various factors that affect them. Apart from the factors recognized by past studies, such as service quality, perceived value, and satisfaction, this study addresses the importance of the involvement of public transit services in passenger behavioral intentions. By using passenger survey data from the Kaohsiung Mass Rapid Transit (KMRT), a newly operating public transit system in Taiwan, we apply the structural equation modeling technique to analyze the conceptualized relationship model. The findings reveal that all causal relationships are statistically significant. Managerial implications are discussed.     

Exploring the impacts of land use by service coverage and station-level accessibility on rail transit ridership

In this study, we employ spatial regression analysis to empirically investigate the impacts of land use, rail service coverage, and rail station accessibility on rail transit ridership in the city of Seoul and the surrounding metropolitan region. Our analyses suggest that a rail transit service coverage boundary of 500 m provides the best fit for estimating rail transit ridership levels. With regard to land use, our results confirm that density is positively related to rail transit ridership within a 750 m radius of each station. In contrast, land use diversity is not associated with rail transit ridership. We also found that station-level accessibility is as important as land use for explaining rail transit ridership levels. Finally, we conclude that development density and station-level accessibility measures such as the number of station entrances or exits and the number of bus routes at the station are the most important and consistent factors for promoting rail transit ridership.     

Investigating users' travel behaviours and perceptions of single-corridor BRT: Lessons from Lahore

Despite the global popularity of bus rapid transit (BRT) in last couple of decades, there is limited empirical evidence in the rapidly urbanizing developing countries regarding corridor-wide users' typical travel characteristics and perceptions of the system attributes. The factors affecting BRT users' (dis)satisfaction are also often disregarded, given less priority than needed, or delayed till issues become more difficult and costlier to manage. Although on a rise, currently only ~10% of BRT systems worldwide are in lower-middle-income and low-income countries, which also supports the need to effectively address BRT passengers' mobility issues in such countries with cramped resources, contributing towards more sustainable urban mass transit systems. As major share of BRTs worldwide are single-corridors (~63%), this study investigates the above stated gaps using case of such BRT in the megacity of Lahore, Pakistan via on-site structured interview surveys using intercept method from BRT users along all stations of the corridor. Typical travel characteristics, correlations and cross-comparisons of sample demographics with mobility attributes, underlying (dis)similar themed factors ensuring internal consistency, and rankings of (dis)satisfactions regarding service attributes were evaluated using combination of statistical methods. Visual comparisons of factors in 2D and 3D rotated space were also explored. Results revealed differences in travel characteristics of BRT users for various demographics; convergence of eight factors from twenty-two service quality attributes; spectrum of highest, average and lowest ranked attributes; and inter-spatial relationship of service quality attributes based on the factors contributing relatively more variation. The overarching findings provide useful insights for transportation practitioners, policy makers and could also contribute towards updating BRT guidelines by incorporating the needs and requirements of BRT users in the developing countries.     

The Gothenburg congestion charge scheme: A pre–post analysis of commuting behavior and travel satisfaction

The article uses the Gothenburg congestion charge scheme, implemented in 2013, as a case study to analyze the effects and perceptions of a policy instrument directly aimed to change the travel behavior of individuals. For the study, a survey was conducted including measures of commuting habits, attitudes (toward the congestion charge, the environment, automobility, and public transport), and satisfaction with travel, along with socio-demographic and geographical variables. The survey was distributed to a panel of 3500 car owners in the Gothenburg region before the implementation of the scheme, with a follow-up one year later. The analysis use group comparisons and a binary logistic regression analysis and results show that the difference in accessibility of different societal functions using private versus public transport affected the propensity to reduce car travel, whereas socio-demographic variables had a low statistical significance, with the exception of women who were twice as likely to reduce their car travel than men. All studied groups reported a more positive view of the scheme at follow-up, although this effect was more pronounced among those adapting their commuting behavior. In none of the studied groups did the implementation of the congestion charge scheme correlate with any significant change in satisfaction with travel.     

Potential for reducing carbon emissions from urban traffic based on the carbon emission satisfaction: Case study in Shanghai

The transport sector has attracted much attention as one of the main sources of carbon emissions. In this study, we constructed an optimal urban traffic structure model based on the concept of carbon emission satisfaction in order to estimate the absolute carbon emission reductions that can be achieved, and to objectively analyze the relative difficulty of achieving the emissions reduction goal. By considering Shanghai as an example, we found that rail transit is the dominant mode of transportation and that the proportion of travel in private cars can be greatly reduced, but buses should be maintained at the current level, whereas the proportion of taxis may be reduced slightly. In the existing traffic environment in Shanghai, after optimizing the urban traffic structure, we found that 47.62% of the carbon emissions reduction target can be achieved. However, given the excessive attention paid to the satisfaction of individuals and the government but the lack of consideration of the ecological environment, the carbon emission satisfaction with respect to urban traffic is low at present in Shanghai. Improving the carbon emission satisfaction by reducing the satisfaction of other targets is difficult, and the potential for reducing carbon emissions is limited for transportation. Therefore, Shanghai can only achieve its carbon emission reduction targets by implementing resource allocation, transportation technology, and urban planning measures in order to improve the existing traffic conditions, thereby achieving the goal of reducing carbon emissions but without affecting the satisfaction of other targets.     

A multilevel spatial interaction model of transit flows incorporating spatial and network autocorrelation

While it is well known that ignoring spatial dependence often results in misspecification of models, travel demand models almost never account for this phenomenon. The aim of this paper is to empirically demonstrate the importance of accounting for potential spatial dependence between observations in the specification of spatial interaction models. As a case study, we analyze travel flows on the public transport system in an urban region in the Netherlands. We develop five distinct spatial interaction models (SIMs) of increasing complexity, each encompassing a lower and upper level model. At the lower level, the attractiveness of neighborhoods for boarding and alighting is modeled based on spatial and transit supply characteristics. At the upper level, spatial interactions among zones are modeled taking into account competing origins, competing destinations as well as network characteristics. We systematically compare more traditional SIM formulations with a SIM that explicitly accounts for spatial and network autocorrelation. The results show a substantial difference between the former models and the latter, in terms of the estimated total marginal impacts of the different variables and the pattern of the error terms. The results of our study underscore that the failure to incorporate autocorrelation effects in travel models is likely to influence model outcomes, which in turn may have profound implications for the very design of public transport networks in cities and regions.