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Abstract
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We revisit the effectiveness of land use densification as a strategy to promote travel sustainability by investigating the nonlinearity and mediation in the effects of residential densities on home-work distance, car ownership, and driving distance. Using a 2017 travel survey dataset in Beijing, we adopt a quadratic generalized multilevel structural equation model to estimate nonlinear and mediating effects simultaneously.
RESULTS suggest that the total effects of densities on home-work distance, car ownership, and driving distance are significantly curvilinear. Over-densification may result in marginal or even countervailing travel consequences. The appropriate level of residential density should lie below a threshold at around 18,000 persons/km2. Moreover, the densification policy in low-density neighborhoods may have a trivial direct effect but a significant indirect effect on driving reduction, through the mediation of other travel decisions. These findings demonstrate the importance of incorporating nonlinearity with mediation to evaluate land use policies, particularly in high-density cities.
Cities worldwide reallocate street space from serving cars to other modes and uses as part of strategies to make their city centers attractive, vibrant, and accessible. Novel empirical knowledge may reduce uncertainties and opposition to implementation. This article contributes insights into how commuters and city center users adapted to rapid and radical street reallocations in the Oslo city center and the effects and consequences they experienced. Extensive surveys were conducted before and after realization; the results showed weak but positive results for the issues investigated, such as commute satisfaction, experienced accessibility, frequency of visits, and appreciation of the city center. Travel experiences improved for those walking and bicycling, whereas they worsened for those driving. The results showed only minor modal changes. The interventions contributed positively to factors attracting visitors, and thus, the findings might expand authorities' understanding of feasible interventions when developing more sustainable and people-friendly cities.
The study on gender disparity in service quality (SQ) interrelations of public transit can provide gender-specific improvement measures to transit officials in attracting new passengers and increase patronage. In the presence of minimal knowledge basis on gender disparity in SQ interrelations, this study fills the gap by applying an integrated Bayesian Networks (BN) and Partial Least Squares Structural Equation Modelling (PLS-SEM) on perception data of 1504 male and 745 female passengers of Delhi Metro. The study findings reveal that males consider passenger ease, whereas females consider service availability as most influential factors in explaining overall SQ. Females are less concerned about passenger ease and seamless connectivity, as compared to males. Further, gender-based importance-performance analysis has highlighted that Delhi Metro must consider 'safety and security' as most crucial factor to improve its services. Overall, this study demonstrates the necessity of gender-specific strategic measures to help transit officials in allocating resources efficiently.
Could a widespread proliferation of ridesharing services mitigate or exacerbate the carbon footprint of urban passenger transport? Despite having profound policy implications, this question has not yet been answered in the literature. This paper examines that impact ex-ante, by simulating the aggregate travel demand, the choice of transport mode and the resulting CO2 emissions in 247 cities between 2015 and 2050. We find that if ridesharing services receive substantial policy support, CO2 emissions from passenger transport in 2050 will be on average 6.3% lower than their reference level. However, we show that this finding differs widely across cities. The paper identifies the reasons for this variation and the policies that are socially desirable in a given city, conditional on its characteristics.
With the rapid growth of travel demand and massive investments in transportation infrastructure, large-scale integrated transport hubs that connect multiple transport modes are emerging in many cities. Indoor air pollution in such hubs could have significant adverse impact on passengers' health due to the high passenger volume and the pivotal role in the transport system. In this study, we examine the distribution and determinants of air pollutant concentrations in large transport hubs using Hongqiao Hub in Shanghai, China as an example. We measure air pollutant concentrations and meteorological factors on 6 days throughout a year in different areas of the hub. We explore the spatial and temporal distribution of air pollutants within the hub and apply General Addictive Models to assess the relationship between air pollution, meteorological factors, and location attributes. We find that motor vehicles including taxis and parking vehicles are a major source of air pollutants in the hub. Based on the research findings, we propose measures to mitigate indoor air pollution in the hub and discuss policy implications.
This study aims to quantify the relationship between pedestrians' walking speeds and various surface conditions typically associated with a winter environment. The purpose is to enable assessments of the effects of different winter operation and maintenance regimes on pedestrians' average travel times.
The results show that there is a significant relationship between surface conditions and average walking speeds. When comparing a bare-pavement level of service (LOS) with the practically best obtainable winter-pavement LOS it is expected that the average travel times of an average pedestrian will be approximately 1 min/km longer on the latter than the former when walking on flat ground. On clean ice, compared to a bare pavement, we can expect the average travel times to be approximately 2 min/km longer.
Data on average travel times should be implemented in cost-benefit analyses that evaluate the effects of different winter operation and maintenance regimes and measures.
Language: en |