Pan, Haixiao; Shen, Qing; Xue, Song. (2010). Intermodal Transfer Between Bicycles and Rail Transit in Shanghai, China. Transportation Research Record, 2144, 181 – 188.
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Abstract
Large cities in China are building rail transit systems as part of a key strategy to address their pressing urban transportation problems. Because the high construction cost of subways and light rail limits the network density of rail transit, urban transport planners must seek effective intermodal connections between rail and other modes. This research examines the challenges and opportunities for improving the bicycle rail connection by using Shanghai as a case study. On the basis of two questionnaire surveys of rail transit riders, the research analyzes the existing mode shares of rail station access and egress trips, the underlying mechanisms for choosing among alternative modes, and the comparative advantages of the bicycle for trips that have certain distance and location characteristics. Empirical results suggest that the potential for travel improvement for rail transit riders lies primarily in the collection and distribution phases. Results point to several promising approaches to improving the bicycle rail connection and utilizing the bicycle more fully as an efficient supplement mode for the rapidly expanding urban rail transportation in China. In addition, the work can be a useful reference for cities in other countries in which rail transit development is accompanied by the continued importance of bicycles in residents' travel.
Chen, Peng; Hu, Songhua; Shen, Qing; Lin, Hangfei; Xie, Chi. (2019). Estimating Traffic Volume for Local Streets with Imbalanced Data. Transportation Research Record, 2673(3), 598 – 610.
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Abstract
Annual average daily traffic (AADT) is an important measurement used in traffic engineering. Local streets are major components of a road network. However, automatic traffic recorders (ATRs) used to collect AADT are often limited to arterial roads, and such information is, therefore, often unavailable for local streets. Estimating AADT on local streets becomes a necessity as local street traffic continues to grow and the capacity of arterial roads becomes insufficient. A challenge is that an under-represented sample of local street AADT may result in biased estimation. A synthetic minority oversampling technique (SMOTE) is applied to oversample local streets to correct the imbalanced sampling among different road types. A generalized linear mixed model (GLMM) is employed to estimate AADT incorporating various independent variables, including factors of roadway design, socio-demographics, and land use. The model is examined with an AADT dataset from Seattle, WA. Results show that: (1) SMOTE helps to correct imbalanced sampling proportions and improve model performance significantly; (2) the number of lanes and the number of crosswalks are both positively associated with AADT; (3) road segments located in areas with a higher population density or more mixed land use have a higher AADT; (4) distance to the nearest arterial road is negatively correlated with AADT; and (5) AADT creates spatial spillover effects on neighboring road segments. The combination of SMOTE and GLMM improves the estimation accuracy on AADT, which contributes to better data for transportation planning and traffic monitoring, and to cost saving on data collection.
Keywords
Average; Prediction; Network; County
Rowe, Daniel H.; Bae, Chang-hee Christine; Shen, Qing. (2010). Assessing Multifamily Residential Parking Demand and Transit Service. Ite Journal-institute Of Transportation Engineers, 80(12), 20 – 24.
Abstract
This study examined the relationship of multifamily residential parking demand and transit level of service in Two King County, WA, USA, Urban Centers: First Hill/Capitol Hill (FHCH) and redmond. In addition, current parking policies were assessed for their ability to meet the observed parking demand, and an alternative method to collect parking demand data was explored.
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