Chen, Peng; Shen, Qing. (2019). Identifying High-risk Built Environments for Severe Bicycling Injuries. Journal of Safety Research, 68, 1 – 7.
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Abstract
Introduction: This study is aimed at filling part of the knowledge gap on bicycling safety in the built environment by addressing two questions. First, are built environment features and bicyclist injury severity correlated; and if so, what built environment factors most significantly relate to severe bicyclist injuries? Second, are the identified associations varied substantially among cities with different levels of bicycling and different built environments? Methods: The generalized ordered logit model is employed to examine the relationship between built environment features and bicyclist injury severity. Results: Bicyclist injury severity is coded into four types, including no injury (NI), possible injury (PI), evident injury (El), and severe injury and fatality (SIF). The findings include: (a) higher percentages of residential land and green space, and office or mixed use land are correlated with lower probabilities of El and SIF; (b) land use mixture is negatively correlated with El and SIF; (c) steep slopes are positively associated with bicyclist injury severity; (d) in areas with more transit routes, bicyclist injury is less likely to be severe; (e) a higher speed limit is more likely to correlate with SIF; and (f) wearing a helmet is negatively associated with SIF, but positively related to PI and El. Practical applications: To improve bicycle safety, urban planners and policymakers should encourage mixed land use, promote dense street networks, place new bike lanes in residential neighborhoods and green spaces, and office districts, while avoiding steep slopes. To promote bicycling, a process of evaluating the risk of bicyclists involving severe injuries in the local environment should be implemented before encouraging bicycle activities. (C) 2018 National Safety Council and Elsevier Ltd. All rights reserved.
Keywords
Motor Vehicle; Land-use; Crashes; Severities; Facilities; Frameworks; Frequency; Cyclists; Bike; Bicyclist Injury Severity; Built Environments; Generalized Ordered Logit Model; Us Cities; Bicycles; Urban Environments; Injuries; Neighborhoods; Land Use; Urban Areas; Paths; Protective Equipment; Bicycling; Fatalities; Correlation; Residential Areas; Traffic Accidents & Safety; Safety; Logit Models; Ecological Risk Assessment; Slopes; Health Risks; Urban Transportation; Studies; Environments
Zhen, Feng; Shen, Qing; Jian, Boxiu; Zheng, Jun. (2010). Regional Governance, Local Fragmentation, and Administrative Division Adjustment: Spatial Integration in Changzhou. China Review-an Interdisciplinary Journal On Greater China, 10(1), 95 – 128.
Abstract
Although the current practice of administrative division adjustment in China may help to facilitate regional governance and urbanization economies, it does not effectively resolve the fundamental conflicts between the central city and surrounding county-level cities. This paper examines the impacts of administrative division adjustment on economic development in Changzhou, Jiangsu Province, by focusing on the city's development zones. It identifies major problems in the development zones and explores the major institutional, policy, sociocultural, and spatial planning factors underlying these problems. It further proposes several approaches for the spatial integration of development zones, from the perspectives of institution, policy, and space, with broader implications that go well beyond the Changzhou case.
Keywords
River Delta; Transition
Zhang, Jinlei; Chen, Feng; Shen, Qing. (2019). Cluster-based LSTM Network for Short-term Passenger Flow Forecasting in Urban Rail Transit. Ieee Access, 7, 147653 – 147671.
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Abstract
Short-term passenger flow forecasting is an essential component for the operation of urban rail transit (URT). Therefore, it is necessary to obtain a higher prediction precision with the development of URT. As artificial intelligence becomes increasingly prevalent, many prediction methods including the long short-term memory network (LSTM) in the deep learning field have been applied in road transportation systems, which can give critical insights for URT. First, we propose a novel two-step K-Means clustering model to capture not only the passenger flow variation trends but also the ridership volume characteristics. Then, a predictability assessment model is developed to recommend a reasonable time granularity interval to aggregate passenger flows. Based on the clustering results and the recommended time granularity interval, the LSTM model, which is called CB-LSTM model, is proposed to conduct short-term passenger flow forecasting. Results show that the prediction based on subway station clusters can not only avoid the complication of developing numerous models for each of the hundreds of stations, but also improve the prediction performance, which make it possible to predict short-term passenger flow on a network scale using limited dataset. The results provide critical insights for subway operators and transportation policymakers.
Keywords
Traffic Flow; Neural-network; Prediction; Ridership; Models; Volume; Lstm; Short-term Passenger Flow Forecasting; Urban Rail Transit; K-means Clustering; Deep Learning
Liu, Chao; Shen, Qing. (2011). An Empirical Analysis of the Influence of Urban Form on Household Travel and Energy Consumption. Computers, Environment & Urban Systems, 35(5), 347 – 357.
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Abstract
Using the 2001 National Household Travel Survey (NHTS) data, this paper empirically examines the effects of urban land use characteristics on household travel and transportation energy consumption in the Baltimore metropolitan area. The results of regression analysis show that different built environment measures lead to substantially different findings regarding the importance of urban form in influencing travel behavior. Among the built environment variables used in the analysis, accessibility provides much more explanatory power than density, design and diversity measures. Moreover, this study explores approaches to modeling the connection between urban form and household transportation energy consumption. Applying Structural Equation Models (SEMs), we found that urban form does not have a direct effect either on VMT or on vehicle energy consumption. The indirect effect, however, is significant and negative, which suggests that urban form affects household travel and energy consumption through other channels. In addition, household socio-economic characteristics, such as gender and number of vehicles, and vehicle characteristics also show significant relationships between VMT and energy consumption. This empirical effort helps us understand the major data and methodology challenges. (C) 2011 Elsevier Ltd. All rights reserved.
Keywords
Urban Planning; Households; Travel; Energy Consumption; Empirical Research; Transportation; Metropolitan Areas; Climate Change; National Household Travel Survey (nhts); Usage; Environment; Behavior; Holdings; Impact
Guan, Jinping; Zhang, Kai; Shen, Qing; He, Ying. (2020). Dynamic Modal Accessibility Gap: Measurement and Application Using Travel Routes Data. Transportation Research: Part D, 81.
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Abstract
Accessibility is a key concept in transportation research and an important indicator of people's quality of life. With the development of big data analytics, dynamic accessibility that captures the temporal variations of accessibility becomes an important research focus. Few prior studies focus on comparative measures of dynamic accessibility to Points of Interest (POIs) by alternative travel modes. To fill this research gap, we propose a new index called dynamic modal accessibility gap (DMAG), which draws upon available data on residents' real travel routes using different travel modes, as well as the data on POIs. We study the DMAG in the real-travel covered area, assuming POIs are only useful if it is within someone's real-travel covered area. We then apply this DMAG methodology to Shanghai's central city and peripheral area. In both cases, we measure the accessibility for public and private travel modes. As an example, one-week taxi GPS and metro smart card data, and POIs data are used to generate the DMAG index for 30-minute and 60-minute trip durations for weekdays and holidays. Results show that DMAG can reflect the pattern of temporal variations. The proposed DMAG analytical framework, which can be applied at both the user and the system levels, can support urban and transportation planning, and promote social equity and livability.
Keywords
Air Travel; Choice Of Transportation; Urban Transportation; Transportation Planning; Urban Planning; Smart Cards; Inner Cities; Route Choice; Shanghai (china); Dynamic Accessibility; Modal Accessibility Gap (mag); Points Of Interest (pois); Public And Private Travel Modes; Temporal Variations; Scale Residential Areas; Transport; Time; Dimensions; Employment; Indicator; Choice; Boston; Car
Rowe, Daniel H.; Bae, Christine; Shen, Qing. (2011). Evaluating the Impact of Transit Service on Parking Demand and Requirements. Transportation Research Record, 2245, 56 – 62.
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Abstract
Many jurisdictions in the United States typically set minimum parking requirements for residential multifamily developments based on old data that were collected in suburban settings with little transit availability. Such parking requirements applied to urban settings with adequate transit service often result in an oversupply of parking, which in turn creates a barrier to smart growth. Not only does the oversupply of parking encourage automobile use and reduce housing affordability, but it also increases development costs, consumes land and natural resources, and increases associated air and water pollution. This research examines the relationship of parking demand and transit service in First Hill Capitol Hill (FHCH) and Redmond, two urban centers in King County, Washington. An alternative method to collect parking demand data is explored. The results show a strong relationship between transit service and parking demand. The FHCH urban center, which abuts downtown Seattle, exhibited higher levels of transit service and lower parking demand. Parking demand in FHCH was observed to be 0.52 parking space per dwelling unit, which was about 50% less than parking demand observed in Redmond, a growing mixed-use suburban center, and 50% less than data reported by the Institute of Transportation Engineers. After a review of the parking policies of each urban center, opportunities to improve regulations including adjusting minimum parking requirements and allowing for reductions in required parking when developers implement solutions to reduce demand for parking were identified.
Abu Ashour, Lamis; Dannenberg, Andrew L.; Shen, Qing; Fang, Xun; Wang, Yiyuan. (2021). Paratransit Services For People With Disabilities In The Seattle Region During The Covid-19 Pandemic: Lessons For Recovery Planning. Journal Of Transport & Health, 22.
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Abstract
Introduction: Along with all public transit services, paratransit services for people with disabilities experienced substantially reduced demand and an increased need to provide equitable services while protecting their clients and staff's safety during the COVID-19 pandemic. Paratransit services provide a lifeline for their clients' essential mobility needs, including access to medical appointments and grocery stores. In the absence of pre-existing pandemic response plans, examining transit agencies' responses to provide paratransit services during the pandemic can help inform planning for post-pandemic recovery and future disruptive events. Methods: In September 2020, we conducted semi-structured interviews with 15 decision-makers, planners, and drivers working for the primary transit agency in the Seattle region - King County Metro - and its paratransit contractors. Interview questions were designed to identify current services, policy gaps, and critical challenges for recovery planning and post-pandemic paratransit services. Interview transcripts were analyzed using NVivo software to obtain essential themes. Results: The interviewees provided insights about (1) paratransit service changes in response to the pandemic, (2) anticipated impacts of a returning demand on paratransit service efficiency, equity, and quality during the recovery period, and (3) innovative approaches for maintaining post-pandemic equitable paratransit services while balancing safety measures with available resources. Conclusions: Study findings suggest that paratransit service providers should consider (1) developing guidelines for future disruptive events, (2) examining alternative methods for food delivery to clients, (3) planning scenarios for delivering equitable services in the post-pandemic recovery period, and (4) increasing resilience possibly by establishing partnerships with transportation network companies.
Keywords
Paratransit; Mobility; Equity; Covid19 Pandemic; Scenario Planning; Recovery
Yang, Jiawen; Shen, Qing; Shen, Jinzhen; He, Canfei. (2012). Transport Impacts of Clustered Development in Beijing: Compact Development Versus Overconcentration. Urban Studies, 49(6), 1315 – 1331.
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Abstract
This research aims to inform the compact city discussion with a case study of Beijing, where urban planning has emphasised clustered suburban development in the past half-century. It uses three decades of census data to describe Beijing's spatial development trajectory and a household survey to assess its transport impacts. The research reveals an overconcentration of urban activities as a result of the featureless expansion of the central built-up area and the absorption of the suburban clusters; and, a lengthened commuting time stemming from the observed spatial development pattern. Beijing's experience adds to the existing literature by informing the search for good city forms in urban areas of high density. It is essential to differentiate compact development from overconcentration when combating sprawling development. Developing and maintaining suburban nodal characteristics around public transit can reduce travel in high-density urban areas.
Keywords
Jobs-housing Balance; Commuting Patterns; Urban; Growth; City; Towns
Shen, Qing; Wang, Yiyuan; Gifford, Casey. (2021). Exploring Partnership Between Transit Agency And Shared Mobility Company: An Incentive Program For App-based Carpooling. Transportation, 48(5), 2585 – 2603.
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Abstract
How should public transit agencies deliver mobility services in the era of shared mobility? Previous literature recommends that transit agencies actively build partnerships with mobility service companies from the private sector, yet public transit agencies are still in search of a solid empirical basis to help envision the consequences of doing so. This paper presents an effort to fill this gap by studying a recent experiment of shared mobility public-private partnership, the carpool incentive fund program launched by King County Metro in the Seattle region. This program offers monetary incentives for participants who commute using a dynamic app-based carpooling service. Through descriptive analysis and a series of logistic regression models, we find that the monetary incentive to encourage the use of app-based carpooling generates some promising outcomes while having distinctive limitations. In particular, it facilitates the growth of carpooling by making carpooling a competitive commuting option for long-distance commuters. Moreover, our evidence suggests that the newly generated carpooling trips mostly substitute single-occupancy vehicles, thus contributing to a reduction of regional VMT. The empirical results of this research will not only help King County Metro devise its future policies but also highlight an appealing alternative for other transit agencies in designing an integrated urban transportation system in the era of shared mobility.
Keywords
Shared Mobility; Public-Private Partnership; App-based Carpooling; Incentive Fund; Transit Agencies; Incentives; Commuting; Public Transportation; Mobility; Regression Analysis; Regression Models; Partnerships; Vehicles; Car Pools; Private Sector; Occupancy; Transportation Systems; Mass Transit; Transportation Planning; Empirical Analysis; Urban Transportation
Hong, Jinhyun; Shen, Qing. (2013). Residential Density and Transportation Emissions: Examining the Connection by Addressing Spatial Autocorrelation and Self-Selection. Transportation Research Part D-transport And Environment, 22, 75 – 79.
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Abstract
This paper examines the effect of residential density on CO2 equivalent from automobile using more specific emission factors based on vehicle and trip characteristics, and by addressing problems of spatial autocorrelation and self-selection. Drawing on the 2006 Puget Sound Regional Council Household Activity Survey data, the 2005 parcel and building database, the 2000 US Census data, and emission factors estimated using the Motor Vehicle Emission Simulator, we analyze the influence of residential density on road-based transportation emissions. In addition, a Bayesian multilevel model with spatial random effects and instrumental variables is employed to control for spatial autocorrelation and self-selection. The results indicate that the effect of residential density on transportation emissions is influenced by spatial correlation and self-selection. Our results still show, however, that increasing residential density leads to a significant reduction in transportation emissions. (C) 2013 Elsevier Ltd. All rights reserved.
Keywords
Urban Form; Travel; Transportation Emissions; Residential Density; Confounding By Location; Self-selection