2017
DOI: 10.1016/j.jue.2017.03.001
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The effects of driving restrictions on travel behavior evidence from Beijing

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Cited by 73 publications
(37 citation statements)
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“…It indicates that the DPR would alter the traveler's travel habit and further promote the traveler to choose public transport on restricted days, which is beneficial to easing urban congestion and reducing air pollution on restricted days. This is consistent with the research conclusions of Zhang et al [1] and Gu et al [18]. However, 27.5% of people still choose the private cars, the possible reason is that they might have more than one car or adjust their travel time to avoid the DPR.…”
Section: Changes In Travel Modes After the Implementation Of The Drpsupporting
confidence: 91%
See 1 more Smart Citation
“…It indicates that the DPR would alter the traveler's travel habit and further promote the traveler to choose public transport on restricted days, which is beneficial to easing urban congestion and reducing air pollution on restricted days. This is consistent with the research conclusions of Zhang et al [1] and Gu et al [18]. However, 27.5% of people still choose the private cars, the possible reason is that they might have more than one car or adjust their travel time to avoid the DPR.…”
Section: Changes In Travel Modes After the Implementation Of The Drpsupporting
confidence: 91%
“…Zhang et al [1] found that the DRP is very effective tool to shift people from automobile to public transit and ease traffic congestion. While analyzing the Beijing household travel survey data, Gu et al [18] found that the DRP has an impact on easing road congestion by reducing private car travel frequency and mileage. Furthermore, Wang et al [19] found that excluding electric vehicles from regulations of the DRP or the purchasing restriction policy (PRP) could earn the support from the public.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Among the quantity restriction measures, we can identify two types: policies that prohibit circulation on specific days in the city based on some form of identifier and policies that identify low-emission areas and prohibit the transit of high-emission vehicles in those metropolitan areas. These measures, however, are more usually associated with fighting pollution than congestion [77][78][79][80], but some studies also analyzed their effectiveness in reducing the flow of private transportation [81,82]. Other transportation demand management measures were less examined but are increasingly being considered by policy-makers and planners to promote sustainable transportation.…”
Section: Literature On Public Measures To Mitigate Congestionmentioning
confidence: 99%
“…This outdoor air monitoring site is located no more than 20 km from the three schools. The schools informed us that most students live within 10 km of the school, likely due in part to the state of road congestion in major Chinese cities (Viard and Fu, 2015;Gu et al, 2017). Alternative PM2.5 measurements at Chinese Ministry of Environmental Protection (CMEP) sites across the city, available only from 2013, show tight spatial correlation not only across CMEP sites but also with US embassy records in the overlapping period.…”
Section: Panel (D) Reports a Seasonal Pattern For Absenteeism With Lmentioning
confidence: 99%
“…We examine spell-adjusted absences, where an absence is the first school day of an absence spell. 24 The estimation sample consists of 2,448,516 observations. Table 2 estimates linear probability model (2) of student absences and, as alternative measures of immediate exposure to severe PM2.5, considers: (columns 1 and 2) an indicator that daily mean PM2.5 on the day before the absence decision exceeded 200 µg/m 3 (Figure 3(a)); (column 3) a count of the days in which daily mean PM2.5 exceeded 200 µg/m 3 in the three days prior to the absence decision (zero, one, two or three); (column 4) a linear spline function of daily mean PM2.5 on the day before the absence decision; and (columns 5 to 7) a quadratic function of daily mean PM2.5 on the day before the absence decision.…”
Section: Severe Air Pollution and Student Absencesmentioning
confidence: 99%