Does polycentric and compact development alleviate urban traffic congestion? A case study of 98 Chinese cities

Li, Yingcheng; Wang, Xiong; Wang, Xingping

doi:10.1016/j.cities.2019.01.017

Cited by 107 publications

(63 citation statements)

References 25 publications

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“…Lee et al [17] suggested that several unobserved factors, such as road congestion, design, and materials of roads that were built in the same period and location, were spatially correlated. Also, Li et al [50] discovered that the compactness of the urban environment is positively associated with traffic congestion.…”

Section: Discussionmentioning

confidence: 99%

Factors Contributing to the Relationship between Driving Mileage and Crash Frequency of Older Drivers

2019

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As a characteristic of senior drivers aged 65 +, the low-mileage bias has been reported in previous studies. While it is thought to be a well-known phenomenon caused by aging, the characteristics of urban environments create more opportunities for crashes. This calls for investigating the low-mileage bias and scrutinizing whether it has the same impact on other age groups, such as young and middle-aged drivers. We use a crash database from the Ohio Department of Public Safety from 2006 to 2011 and adopt a macro approach using Negative Binomial models and Conditional Autoregressive (CAR) models to deal with a spatial autocorrelation issue. Aside from the low-mileage bias issue, we examine the association between the number of crashes and the built environment and socio-economic and demographic factors. We confirm that the number of crashes is associated with vehicle miles traveled, which suggests that more accumulated driving miles result in a lower likelihood of being involved in a crash. This implies that drivers in the low mileage group are involved in crashes more often, regardless of the driver’s age. The results also confirm that more complex urban environments have a higher number of crashes than rural environments.

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Section: Discussionmentioning

confidence: 99%

Factors Contributing to the Relationship between Driving Mileage and Crash Frequency of Older Drivers

2019

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“…The nonlinearity and complexity of smart grid challenges, especially climate risks, urbanization, demographic shifts, systemic environmental change, and energy infrastructure investment deficit facing many cities, can be addressed by a "polycentric" strategy that incorporates shared learning, adaptive management, civil society strategies, and creative experimentation to support existing transformative innovations and empower local energy development. Initially proposed in the 1960s and 1970s (Aligica and Tarko 2012), polycentric strategy has been applied to evaluate "solar city" economics (Byrne and Taminiau 2018), climate justice (Fischedick et al 2018;Martinez-Alier et al 2016;Ostrom 2010), urban energy planning for 100% renewability in Frankfurt and Munich cities (Radzi 2018), alleviating urban traffic congestion (Li et al 2019), assessing energy efficiency gap (Zou et al 2019), and evaluating new capacities for transformative climate governance in New York City (the United States) and Rotterdam (the Netherlands) (Hölscher et al 2019). In terms of smart energy infrastructure governance, polycentric policy underscores the elements summarized in Table 3 transparency, inclusivity, accountability, and responsive network practices.…”

Section: A Polycentric Approach To Smart City Energy Governancementioning

confidence: 99%

Smart Energy Frameworks for Smart Cities: The Need for Polycentrism

Nyangon

2020

Handbook of Smart Cities

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Rapid growth in megacities has prompted deep transformations intended to change sociotechnical systems, deep social and institutional practices, and scientific inquiries to better understand energy and material flows of cities. Typically, these processes are defined by sociotechnical experimentation and purposive reshaping of the synergies between jurisdictions, sectors, and technical solutions required to optimize resource management and improve institutional diversity

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“…A small body of literature evaluates spatial polycentricity [55][56][57]. Even the little existing literature uses only a single indicator: for example, GDP [29], land use [14], or transport/traffic [58,59]. There is a lack of systematic understanding on the changing spatial configurations of the region from a pluralistic perspective.…”

Section: The Current Researchmentioning

confidence: 99%

Polycentricity in the Yangtze River Delta Urban Agglomeration (YRDUA): More Cohesion or More Disparities?

et al. 2019

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Urban spatial structure is a critical component of urban planning and development, and among the different urban spatial structure strategies, ‘polycentric mega-city region (PMR)’ has recently received great research and public policy interest in China. However, there is a lack of systematic understanding on the spatiality of PMR from a pluralistic perspective. This study aims to fill this gap by investigating the spatiality of PMR in the Yangtze River Delta Urban Agglomeration (YRDUA) using city-level data on gross domestic product (GDP), population share, and urban income growth for the period 2000–2013. The results reveal that economically, the YRDUA is experiencing greater polycentricity, but in terms of social welfare, the region manifests growing monocentricity. We further find that the triple transition framework (marketization, urbanization, and decentralization) can greatly explain the observed patterns. Although the economic goals are accomplished with better spatial linkages and early economic development policies, inequality in spatial distribution of public services and the continuing legacy of central planning remain barriers for the YRDUA to emerge as a successful PMR. The results of this research offer meaningful insights on the impact of polycentric policies in the YRDUA and support policymakers in the implementation of appropriate urban spatial development strategies.

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Does polycentric and compact development alleviate urban traffic congestion? A case study of 98 Chinese cities

Cited by 107 publications

References 25 publications

Factors Contributing to the Relationship between Driving Mileage and Crash Frequency of Older Drivers

Factors Contributing to the Relationship between Driving Mileage and Crash Frequency of Older Drivers

Smart Energy Frameworks for Smart Cities: The Need for Polycentrism

Polycentricity in the Yangtze River Delta Urban Agglomeration (YRDUA): More Cohesion or More Disparities?

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