外文文献翻译原文及译文标题：地铁乘车需求的影响因素外文翻译 2019文献出处：ShirinNajafabadi,AliHamidi,etcJTransportPolicy,Volume 74, February 2019, Pages 201-213译文字数：3400 多字英文Does demand for subway ridership in Manhattan depend on the rainfall events?Shirin Najafabadi， Ali HamidiAbstractThe Northeast United States, particularly New York State has experienced an increase in extreme daily precipitation during the past 50 years. Recent events such as Hurricane Irene and Super storm Sandy, have revealed vulnerability to the intense precipitation within the transportation sector. In the scale of New York City, where transit system is the most dominant mode of transportation and daily mobility of millions of passengers depends on it, any disruption in the transit service would result in gridlocks and massive delays. To assess the impacts of rainfall on the subway ridership, we merged high resolution radar rainfall and subway ridership data to conduct a detailed analysis for each of the 116 subway stations at the borough of Manhattan. The analysis is carried out on both hourly and daily resolution level, where a spatial-temporal Bayesian multi-level regression model is used to capture the underlying dependency between the parameters. The estimation results are obtained through Markov Chain Monte Carlo sampling method. The results for daily analysis indicate that during weekdays, transit ridership in the stations located in commercial zones are less sensitive to the rainfallcompared to the ones in residential zones.Keywords：Bayesian multi-level regression model，Subway ridership，MCMC sampling，Radar rainfallLarge cities around the world rely on public transportation infrastructure to maintain a good level of service and to increase mobility and economic productivity. In year 2015, more than 10.7 billion transit trips were reported in the United States (Matthew Dickens, 2016). According to the American Public Transportation Association (APTA) every $1 invested in public transportation generates approximately $4 in economic returns through increased employment rate, business sales, and enhanced property values. The full return on investment for transportation systems can only be achieved when cities optimize and plan the maintenance and growth of their public transportation systems through better realization of the demand level for transportation along with the identification of other influential parameters. Transportation system performance depends on the geometry of the network, as well as other external factors such as accidents, operational tear and wear, disruptions on dependent systems (e.g. the power grid for subways), effective automobile regulation, weather, etc. (De Grange et al., 2012). The objective of the work presented here is to progress further the understanding of impacts of rainfall events on the subway ridership level in Manhattan, New York.During the past 50 years, New York State has experienced an increase in extreme daily precipitation (Horton et al., 2011) also it has been heavily affected by unusual weather patterns such as Hurricane Irene and Superstorm Sandy. In New York City, with over 4 Million daily commute trips (Moss and Qing, 2012), the evidence in the aftermath of extreme weather patterns have revealed vulnerabilities to intense precipitation within the transportation network, yielding enormous economic losses for the City (Brian Tumulty, 2012). A better analysis to quantify the effects of various weather conditions on the transportation network would result in well-informed and efficient policy- making decisions. Literature in recognition of weather influence on transportation and mobility can be classified into two groups. The first group of the literature measures the influence of weather on the performance of transport systems, while the second group studies its behavioral impacts on communities. Studies on the influence of weather over the performance of transportation networks brush over large spectrum of topics including traffic flow and road capacity (e.g. Kyte et al., 2001; Mashros et al., 2014; Maze et al., 2006), infrastructure performance (e.g. Koetse and Rietveld, 2009), traffic safety (e.g. Andreescu and Frost, 1998; Koetse and Rietveld, 2009) and changes in the quality of service (e.g. Cools et al., 2010; Khattak and De Palma, 1997). These studies have shed some light on the most important aspectsof transportation systems and service affected by weather, which are valuable information for city administrators. In general, travel demand, traffic safety, and the traffic flow are the three dominant factors impacted by adverse weather (Maze et al., 2006; Mashros et al., 2014). According to a study conducted in Manchester city by Jaroszweski and McNamara (2014), during rainfalls the rate of road accidents increases by 50%. Meanwhile, through a more comprehensive study carried