Zhao, Zhan; Zhao, Jinhua; Shen, Qing. (2013). Has Transportation Demand of Shanghai, China, Passed Its Peak Growth? Transportation Research Record, 2394, 85 – 92.
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Abstract
On the basis of four comprehensive transportation surveys in Shanghai, China, this study examined the latest trends in Shanghai's travel demand; investigated their social, economic, and spatial drivers; and compared the pace of travel demand growth in three periods: 1980s to early 1990s, early 1990s to mid-2000s, and mid-2000s to the present. The demand growth was relatively slow in the first period and then sped up in the second before it returned to a slower pace in the third period. As for trip purpose, Shanghai's travel is much more diversified than previously, with an increasing share of noncommuting trips (from 28% in 1995 to 46% in 2009). Spatially, travel demand is dispersed from the central district to peripheral districts because of urban expansion and decentralization and from Puxi (west of the Huangpu River) to Pudong (east of the Huangpu River) as a result of significant economic development of the Pudong New Area. Both spatial diffusion and purpose diversification favor the convenience and flexibility of private motor vehicles. Driven by rapid motorization, vehicle travel is growing at a much faster pace than person travel. Overall, the annual growth rate for travel demand in Shanghai reached its peak in 2004 for both person trips and vehicle trips. In absolute numbers, person trip growth has peaked, but vehicle trip growth has not. In response to the growing demand, especially rapid motorization, the local government has made tremendous investments in road infrastructure and public transit, and it has attempted to manage demand through vehicle ownership control.
Keywords
Urban; Impacts; Policy
Wang, Yiyuan; Moudon, Anne Vernez; Shen, Qing. (2022). How Does Ride-Hailing Influence Individual Mode Choice? An Examination Using Longitudinal Trip Data from the Seattle Region. Transportation Research Record, 2676(3), 621 – 633.
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Abstract
This study investigates the impacts of ride-hailing, which we define as mobility services consisting of both conventional taxis and app-based services offered by transportation network companies, on individual mode choice. We examine whether ride-hailing substitutes for or complements travel by driving, public transit, or walking and biking. The study overcomes some of the limitations of convenience samples or cross-sectional surveys used in past research by employing a longitudinal dataset of individual travel behavior and socio-demographic information. The data include three waves of travel log data collected between 2012 and 2018 in transit-rich areas of the Seattle region. We conducted individual-level panel data modeling, estimating independently pooled models and fixed-effect models of average daily trip count and duration for each mode, while controlling for various factors that affect travel behavior. The results provide evidence of substitution effects of ride-hailing on driving. We found that cross-sectionally, participants who used more ride-hailing tended to drive less, and that longitudinally, an increase in ride-hailing usage was associated with fewer driving trips. No significant associations were found between ride-hailing and public transit usage or walking and biking. Based on detailed travel data of a large population in a major U.S. metropolitan area, the study highlights the value of collecting and analyzing longitudinal data to understand the impacts of new mobility services.
Keywords
Shared Mobility; Ride-hailing; Longitudinal Data; Substitution Between Travel Modes; Complementarity Between Travel Modes; Services; Uber
Hong, Jinhyun; Shen, Qing; Zhang, Lei. (2014). How Do Built-Environment Factors Affect Travel Behavior? A Spatial Analysis at Different Geographic Scales. Transportation, 41(3), 419 – 440.
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Abstract
Much of the literature shows that a compact city with well-mixed land use tends to produce lower vehicle miles traveled (VMT), and consequently lower energy consumption and less emissions. However, a significant portion of the literature indicates that the built environment only generates some minor-if any-influence on travel behavior. Through the literature review, we identify four major methodological problems that may have resulted in these conflicting conclusions: self-selection, spatial autocorrelation, inter-trip dependency, and geographic scale. Various approaches have been developed to resolve each of these issues separately, but few efforts have been made to reexamine the built environment-travel behavior relationship by considering these methodological issues simultaneously. The objective of this paper is twofold: (1) to better understand the existing methodological gaps, and (2) to reexamine the effects of built-environment factors on transportation by employing a framework that incorporates recently developed methodological approaches. Using the Seattle metropolitan region as our study area, the 2006 Household Activity Survey and the 2005 parcel and building data are used in our analysis. The research employs Bayesian hierarchical models with built-environment factors measured at different geographic scales. Spatial random effects based on a conditional autoregressive specification are incorporated in the hierarchical model framework to account for spatial contiguity among Traffic Analysis Zones. Our findings indicate that land use factors have highly significant effects on VMT even after controlling for travel attitude and spatial autocorrelation. In addition, our analyses suggest that some of these effects may translate into different empirical results depending on geographic scales and tour types.
Keywords
Land-use; Urban Form; Multilevel Models; Physical-activity; Neighborhood; Choice; Impact; Specification; Accessibility; Causation; Built Environment; Travel Behavior; Self-selection; Spatial Autocorrelation; Bayesian Hierarchical Model
Wang, X.; Liu, C.; Kostyniuk, L.; Shen, Q.; Bao, S. (2014). The Influence of Street Environments on Fuel Efficiency: Insights from Naturalistic Driving. International Journal Of Environmental Science And Technology, 11(8), 2291 – 2306.
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Abstract
Fuel consumption and greenhouse gas emissions in the transportation sector are a result of a three-legged stool: fuel types, vehicle fuel efficiency, and vehicle miles travelled (VMT). While there is a substantial body of literature that examines the connection between the built environment and total VMT, few studies have focused on the impacts of the street environment on fuel consumption rate. Our research applied structural equation modeling to examine how driving behaviors and fuel efficiency respond to different street environments. We used a rich naturalistic driving dataset that recorded detailed driving patterns of 108 drivers randomly selected from the Southeast Michigan region. The results show that, some features of compact streets such as lower speed limit, higher intersection density, and higher employment density are associated with lower driving speed, more speed changes, and lower fuel efficiency; however, other features such as higher population density and higher density of pedestrian-scale retails improve fuel efficiency. The aim of our study is to gain further understanding of energy and environmental outcomes of the urban areas and the roadway infrastructure we plan, design, and build and to better inform policy decisions concerned with sustainable transportation.
Keywords
Travel; Consumption; Emissions; Cities; Energy; Street Environments; Fuel Efficiency; Structural Equation Modeling; Naturalistic Driving
Chen, Peng; Shen, Qing. (2016). Built Environment Effects on Cyclist Injury Severity in Automobile-Involved Bicycle Crashes. Accident Analysis & Prevention, 86, 239 – 246.
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Abstract
This analysis uses a generalized ordered logit model and a generalized additive model to estimate the effects of built environment factors on cyclist injury severity in automobile-involved bicycle crashes, as well as to accommodate possible spatial dependence among crash locations. The sample is drawn from the Seattle Department of Transportation bicycle collision profiles. This study classifies the cyclist injury types as property damage only, possible injury, evident injury, and severe injury or fatality. Our modeling outcomes show that: (1) injury severity is negatively associated with employment density; (2) severe injury or fatality is negatively associated with land use mixture; (3) lower likelihood of injuries is observed for bicyclists wearing reflective clothing; (4) improving street lighting can decrease the likelihood of cyclist injuries; (5) posted speed limit is positively associated with the probability of evident injury and severe injury or fatality; (6) older cyclists appear to be more vulnerable to severe injury or fatality; and (7) cyclists are more likely to be severely injured when large vehicles are involved in crashes. One implication drawn from this study is that cities should increase land use mixture and development density, optimally lower posted speed limits on streets with both bikes and motor vehicles, and improve street lighting to promote bicycle safety. In addition, cyclists should be encouraged to wear reflective clothing. (C) 2015 Elsevier Ltd. All rights reserved.
Keywords
Cycling Injuries; Traffic Accidents; Transportation Planning; Data Analysis; Employment; Built Environment; Cyclist Injury Severity; Generalized Additive Model; Generalized Ordered Logit Model; Ordered Response Model; United-states; Helmet; Frameworks; Driver; Risk
Shen, Qing; Chen, Peng; Pan, Haixiao. (2016). Factors Affecting Car Ownership and Mode Choice in Rail Transit-Supported Suburbs of a Large Chinese City. Transportation Research Part A: Policy & Practice, 94, 31 – 44.
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Abstract
As Chinese cities continue to grow rapidly and their newly developed suburbs continue to accommodate most of the enormous population increase, rail transit is seen as the key to counter automobile dependence. This paper examines the effects of rail transit-supported urban expansion using travel survey data collected from residents in four Shanghai suburban neighborhoods, including three located near metro stations. Estimated binary logit model of car ownership and nested logit model of commuting mode choice reveal that: (1) proximity to metro stations has a significant positive association with the choice of rail transit as primary commuting mode, but its association with car ownership is insignificant; (2) income, job status, and transportation subsidy are all positively associated with the probabilities of owning car and driving it to work; (3) higher population density in work location relates positively to the likelihood of commuting by the metro, but does not show a significant relationship with car ownership; (4) longer commuting distance is strongly associated with higher probabilities of riding the metro, rather than driving, to work; (5) considerations of money, time, comfort, and safety appear to exert measurable influences on car ownership and mode choice in the expected directions, and the intention to ride the metro for commuting is reflected in its actual use as primary mode for journey to work. These results strongly suggest that rail transit-supported urban expansion can produce important positive outcomes, and that this strategic approach can be effectively facilitated by transportation policies and land use plans, as well as complemented by timely provision of high quality rail transit service to suburban residents. (C) 2016 Elsevier Ltd. All rights reserved.
Keywords
Railroads; Public Transit; Choice Of Transportation; Automobile Ownership; Transportation; Suburbanization; China; Automobile Dependence; Large Chinese Cities; Rail Transit; Shanghai; Urban Expansion; Built Environment; Travel Behavior; Self-selection; Impact; Areas
Yang, Liya; Shen, Qing; Li, Zhibin. (2016). Comparing Travel Mode and Trip Chain Choices Between Holidays and Weekdays. Transportation Research Part A: Policy & Practice, 91, 273 – 285.
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Abstract
Choices of travel mode and trip chain as well as their interplays have long drawn the interests of researchers. However, few studies have examined the differences in the travel behaviors between holidays and weekdays. This paper compares the choice of travel mode and trip chain between holidays and weekdays tours using travel survey data from Beijing, China. Nested Logit (NL) models with alternative nesting structures are estimated to analyze the decision process of travelers. Results show that there are at least three differences between commuting-based tours on weekdays and non-commuting tours on holidays. First, the decision structures in weekday and holiday tours are opposite. In weekday tours people prefer to decide on trip chain pattern prior to choosing travel mode, whereas in holiday tours travel mode is chosen first. Second, holiday tours show stronger dependency on cars than weekday tours. Third, travelers on holidays are more sensitive to changes in tour time than to the changes in tour cost, while commuters on weekdays are more sensitive to tour cost. Findings are helpful for improving travel activity modeling and designing differential transportation system management strategies for weekdays and holidays. (C) 2016 Elsevier Ltd. All rights reserved.
Keywords
Choice Of Transportation; Transportation Management; Voyages & Travels; Travel Costs; Travel Time (traffic Engineering); Decision Structure; Nested Logit Model; Policy; Travel Behavior; Patterns; Behavior; Time
Pan, Haixiao; Li, Jing; Shen, Qing; Shi, Cheng. (2017). What Determines Rail Transit Passenger Volume? Implications for Transit Oriented Development Planning. Transportation Research: Part D, 57, 52 – 63.
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Abstract
Transit oriented development (TOD) has been an important topic for urban transportation planning research and practice. This paper is aimed at empirically examining the effect of rail transit station-based TOD on daily station passenger volume. Using integrated circuit (IC) card data on metro passenger volumes and cellular signaling data on the spatial distribution of human activities in Shanghai, the research identifies variations in ridership among rail transit stations. Then, regression analysis is performed using passenger volume in each station as the dependent variable. Explanatory variables include station area employment and population, residents' commuting distances, metro network accessibility, status as interchange station, and coupling with commercial activity centers. The main findings are: (1) Passenger volume is positively associated with employment density and residents' commuting distance around station; (2) stations with earlier opening dates and serving as transfer nodes tend to have positive association with passenger volumes; (3) metro stations better integrated with nearby commercial development tend to have larger passenger volumes. Several implications are drawn for TOD planning: (1) TOD planning should be integrated with rail transit network planning; (2) location of metro stations should be coupled with commercial development; (3) high employment densities should be especially encouraged as a key TOD feature; and (4) interchange stations should be more strategically positioned in the planning for rail transit network.
Keywords
Railroad Passenger Traffic; Transportation; Public Transit; Volume Measurements; Smart Cards; Mathematical Models; Accessibility; Density; Rail Transit Passenger Volume; Spatial Coupling Effect; Tod; Land-use; Built Environment; Travel-demand; Mode Choice; Impacts; Distance
Chen, Peng; Shen, Qing; Childress, Suzanne. (2018). A GPS Data-based Analysis of Built Environment Influences on Bicyclist Route Preferences. International Journal Of Sustainable Transportation, 12(3), 218 – 231.
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Abstract
This study examines the effects of built environment features, including factors of land use and road network, on bicyclists' route preferences using the data from the city of Seattle. The bicycle routes are identified using a GPS dataset collected from a smartphone application named CycleTracks. The route choice set is generated using the labeling route approach, and the cost functions of route alternatives are based on principal component analyses. Then, two mixed logit models, focusing on random parameters and alternative-specific coefficients, respectively, are estimated to examine bicyclists' route choice. The major findings of this study are as follows: (1) the bicycle route choice involves the joint consideration of convenience, safety, and leisure; (2) most bicyclists prefer to cycle on shorter, flat, and well-planned bicycle facilities with slow road traffic; (3) some bicyclists prefer routes surrounded by mixed land use; (4) some bicyclists favor routes which are planted with street trees or installed with street lights; and (5) some bicyclists prefer routes along with city features. This analysis provides valuable insights into how well-planned land use and road network can facilitate efficient, safe, and enjoyable bicycling.
Keywords
Cyclists; Mobile Apps; Multiple Correspondence Analysis (statistics); Traffic Engineering; Cycling; Bicycle Route Choice; Built Environment; Labeling Routes; Mixed Logit Model; Principal Component Analysis; Smartphone GPS Data; Choice Sets; Safe Routes; Walking; Models; Health; Infrastructure; Facilities; California; Networks
Grengs, Joe; Levine, Jonathan; Shen, Qing; Shen, Qingyun. (2010). Intermetropolitan Comparison of Transportation Accessibility: Sorting Out Mobility and Proximity in San Francisco And Washington, DC. Journal Of Planning Education And Research, 29(4), 427 – 443.
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Abstract
Both mobility and proximity influence transportation accessibility, but they exist in tension with each other. To understand the region-level trade-off between mobility and proximity requires intermetropolitan comparisons of accessibility. With a focus on the two metropolitan cases of San Francisco and Washington, D.C., we first describe a method for comparing regional accessibility and then explain a method that separates out the effects of mobility and proximity on regional accessibility. We find that the San Francisco region enjoys an accessibility advantage over Washington largely because of faster highway speeds but that central Washington offers an advantage in proximity.
Keywords
Spatial Interaction; Employment; Location; Access; Sprawl; Land Use; Methods; Nonwork Travel; Transportation; Urban Form; Regional Accessibility