Residential segregation and commuting patterns of migrant workers in China

In China, many rural migrant workers experience residential segregation and live in urbanizing villages, due to China’s unique institutional context (e.g. land tenure system, hukou system) as well as exclusionary housing regulations. The purpose of this paper is to investigate whether these urbanizing villages provide good job accessibility for rural migrant workers. We explore this problem by investigating the commuting patterns of migrant workers. Through a survey conducted in 2009 across four mega-regions in China that are currently experiencing rapid urbanization, we collected individual level information on rural migrant workers’ commute distances and durations, demographics, household socioeconomic status, and whether the migrant worker is living in an urbanizing village or not. From residential address information collected in the survey, we constructed a group of built environment variables. Using IV Tobit models to address the endogeneity issues associated with residential location choice, our analyses show that these urbanizing villages actually provide relatively good accessibility to job opportunities. This result is different from what is suggested by the spatial mismatch literature based on U.S. data. This research helps to fill the gap in the literature on the relationship between residential segregation, built environment and travel behavior in the Chinese context. The findings have implications for policymaking, especially when many government officials are proposing to demolish urbanizing villages without fully realizing the benefits of these villages. This research could also provide useful information for other developing countries facing residential segregation of migrants or immigrants.     

The effect of crowding on public transit user travel behavior in a large-scale public transportation system through modeling daily variations

In this paper, the crowding effect in a transit vehicle is modeled in a time-expanded network that considers the daily variation in passenger flows. The study models the daily variation of in-vehicle crowding in a real large-scale transit system. A transit assignment for this real network is modeled and implemented by constructing a crowding cost function that follows the valuation of crowding and by using the reliable shortest path finding method. The direct application of the crowding model to a real network for the Utah Transit Authority indicates that crowd modeling with multi-user classes could influence public transportation system planning and affect the revenues of transit agencies. Moreover, the addition of the disutility factor, crowding, does not always appear to cause an increase in disutility for transit users.     

伦敦的公交优先政策及启示

通过对比分析的方法,将伦敦曾经面临过的与国内大中城市正面临的城市交通问题进行对比,研究了英国交通发展的历史,伦敦公交发展现状,着重研究了伦敦公交优先政策实施的主要措施.提出,公交优先是多种公共交通模式并存的优先发展,实现公交优先,需要整合各种交通基础设施,并将城市用地、交通需求管理和可持续性的公共交通三者结合起来共同考虑.最后,对提升现有常规公交的服务水平提出了5点具体建议.     

Identifying transit deserts for low-income commuters in Wuhan Metropolitan Area,China

The rapid expansion of many Chinese cities has put increasing pressure on existing urban transportation systems. Using Baidu users’ location data, this research analyzes the spatial patterns of the transit systems and commuter flows in Wuhan Metropolitan Area, China, and identifies transit deserts affecting low-income commuters. The results show that, first, most transit demand are generated by trips between neighboring communities, while large transit supply tends to occur between distant communities in the region. Second, about 11.21% of low-income commuters are affected by transit deserts in Wuhan Metropolitan Area. In detail, 61.30% of them commute within the city centers and 36.06% of them commute within the suburbs. Only about 2.64% of them actually travel between city centers and suburbs. Third, for low-income suburban commuters, transit deserts occur when they are surrounded by low-density transit infrastructure and low-frequency transit services, which makes it very difficult for them to connect to rest of the region. However, for low-income commuters residing in the city centers, transit deserts are mainly caused by the large numbers of transit-dependent people competing for limited transit supply in the areas. This research explores the relationship between transit systems and commuting demand in a major Chinese metropolitan area. The findings could help guide future transit system planning in China and beyond.     

Understanding the impacts of a combination of service improvement strategies on bus running time and passenger’s perception

Transit agencies implement many strategies in order to provide an attractive transportation service. This article aims to evaluate the impacts of implementing a combination of strategies, designed to improve the bus transit service, on running time and passenger satisfaction. These strategies include using smart card fare collection, introducing limited-stop bus service, implementing reserved bus lanes, using articulated buses, and implementing transit signal priority (TSP). This study uses stop-level data collected from the Société de transport de Montréal (STM)’s automatic vehicle location (AVL) and automatic passenger count (APC) systems, in Montréal, Canada. The combination of these strategies has lead to a 10.5% decline in running time along the limited stop service compared to the regular service. The regular route running time has increased by 1% on average compared to the initial time period. The study also shows that riders are generally satisfied with the service improvements. They tend to overestimate the savings associated with the implementation of this combination of strategies by 3.5-6.0 min and by 2.5-4.1 min for both the regular route and the limited stop service, respectively. This study helps transit planners and policy makers to better understand the effects of implementing a combination of strategies to improve running time and passenger’s perception of these changes in service.     

Aggregating mobile object trajectories: cumulative time geographic density estimation for GPS data

We present new approaches that expand upon the time geographic density estimation (TGDE) framework previously employed to estimate potential path trees. In the past, TGDE metrics have identified possible locations an individual moving object may have passed between, given known origin and destination points. This paper utilizes a new form of TGDE to investigate taxicab GPS traces over a specified time horizon with position ‘gaps’. To this end, we propose a new extension to the TGDE framework, TGDE-C, which is used to determine the cumulative TGDE values for a group of GPS traces, at a given location. These metrics are applied to multiple taxis and allow for time of day analysis. Additionally, we combine these new extensions with existing TGDE metrics that allow us to determine how accessible individual or groups of vehicles are to urban opportunities.     

Mathematically calculating the transit time of cargo through a liner shipping network with various trans-shipment policies

This paper derives the mathematical expressions for the transit time of cargo through a liner shipping network. Main efforts are devoted to deriving the calculation expressions of the connection time of cargo during trans-shipment. For the forward and many-to-one trans-shipment policies, we conduct a minor correction towards the expressions in existing studies to improve the completeness. Meanwhile, we propose an alternative but more straightforward calculation method for connection time which bypasses the complicated inductive argument in existing studies. Then we introduce two new trans-shipment policies: backward trans-shipment and one-to-many trans-shipment, and mathematically calculate the corresponding connection times. Numerical experiments also deliver some managerial insights into the effectiveness of backward trans-shipment in transit time control.     

A logit-based model for measuring the effects of transportation infrastructure on land value

Mutual interactions between transportation and land use have long been debated. Despite progress made in computational technology, the study of these interactions is not adequately developed. The most important aspect of such interactions is given by the changes in land values due to changes in transportation infrastructures. We consider the behavioural features of these interactions along with the constraints on the land and/or zoning restrictions and propose a reliable model for the first time to predict land value changes with respect to changes in transportation facilities and accessibility. The proposed model is a logit-based mathematical programming methodology where the relative price of land is predicted with respect to transportation accessibility, neighbourhood amenities, location premium, availability of land, and zoning regulations. A real-world case study is used to exhibit the applicability of the proposed methodology and demonstrate the efficacy of the algorithms and procedures.     

Drivers of transit service loyalty considering heterogeneity between user segments

Users’ loyalty to public transit service is fundamental to promote its popularity in the transportation market. A four-step analytical framework is advanced to investigate the importance of service attributes that heterogeneous transit user segments place on their public transit service loyalty, measured in terms of overall satisfaction and re-use intention. Critical service attributes perceived by transit users that are relevant for loyalty enhancement are explicitly determined, which vary between user segments. It is suggested that the design of strategies aimed to promote the use of public transit by increasing user loyalty towards transit service be targeted at specific attributes that contribute most to loyalty and specific user segments whose original loyalty level is significantly different to others.     

Using Focus and NomiNal Group Techniques for a Better Understanding of the Transit Disadvantaged Needs

The research presented in this paper explores the context, method, and value of focus group research in transit needs assessments. Group participatory research can generate data that are not easily obtained by other methods. The paper focuses on lessons from three Nebraska communities whose transit disadvantaged rely on community-based paratransit services. Because of the size of the paratransit population and the inability to control who showed up to the focus group sessions, a modified group research protocol was adopted in order to garner information from whomever attended the session. The population parameters and the number of people at the meetings were anticipated by the researchers and mitigated by incorporating nominal group techniques. Research findings from the focus group sessions are discussed paying particular attention to the candid and policy-specific comments made by the focus group participants. The paper concludes with an application of focus group research in transit planning.