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Pedestrians and cyclists are a vulnerable group of road users. Immigrants are disproportionally represented in pedestrian and cyclist crashes. We postulate that the mismatch in safety culture between countries of their origin and the USA contribute to their vulnerability in pedestrian and cyclist crashes. Over time, the differences may disappear and immigrants' traffic behavior gravitates toward those of native-borns. We describe this process as safety assimilation. Using the pedestrian and cyclist crash database in New York City between 2001 and 2003, we examined the effects of foreignborn population, their countries of origin, and time of entry into the USA on census tract-level pedestrian and cyclist crashes. We find that neighborhoods with a higher concentration of immigrants, especially those from Latin America, Eastern Europe, and Asia, have more crashes. Our results also exhibit a pattern of the hypothesized safety assimilation process. The study suggests a higher level of vulnerability of immigrants to pedestrian and cyclist crashes. We propose that targeted policies and programs need to be developed for immigrants of different countries of origin.KEYWORDS Pedestrian and cyclist crash, Immigrants, Safety assimilation, Safety culture INTRODUCTIONWalking and cycling are healthy and environmentally friendly modes of transportation compared to automobile usage. Yet, it is undebatable that pedestrians and cyclists are more vulnerable than motorists in traffic collisions. Nationwide, a total of 4,378 pedestrian and 716 cyclist deaths were reported in 2008, 1,2 accounting for 13.7% of motor vehicle collision fatalities. Another 69,000 pedestrians and 52,000 cyclists were injured in traffic crashes in 2008. 3 Minorities are disproportionally represented in traffic fatalities and injuries. In 2001, 69% of the nation's population were non-Hispanic whites, and yet only 60% of the pedestrian deaths for which ethnicity was known were non-Hispanic whites. 4 In contrast, African-Americans were involved in more than 20% of the total pedestrian deaths, though they represented only 12% of the population. Likewise, 13.5% of the pedestrian deaths involved one or more Latinos, while they accounted Chen is with the

We propose a decomposition of residential self-selection by understanding the process of its formation. We take a life-course perspective and postulate that locations experienced early In life can have a lasting effect on our locational preferences later in life. In other words, what was experienced spatially is a key factor contributing to our residential self-selection, and our preferences in residential locations are formed long before the onset of our self-selection. We further hypothesize that this prior-location influence is modified by the duration and recency of the prior stay. Using a dataset collected in the New York City Area, we estimated a series of multinomial logit models to test these hypotheses. The results eonfirm the prior-location influence and demonstrate that this precedes residential self-selection and is impacted by its own properties such as duration and recency. Furthermore, the analysis separating child-bearing households from non-child-bearing households shows an interaction between prior-location influence and the presence of children.

In this paper, we investigate the spatial extent of the housing search. Using the concepts of mental map and awareness space, we argue that search space is affected by households' preferences, what is available on the housing market, and the use of information channels as well as their interactions. We hypothesize that households whose members disagree with each other have a larger search spaces than those whose members agree. Furthermore, the supply in the housing market and the use of different information channels may influence the search space differently for agreeing versus disagreeing households. We collected data from face-to-face interviews with 82 households (couples with or without children) who purchased a home in the New York City area between 2004 and 2009. The results support our hypotheses, suggesting that intra-household dynamics plays an important role in housing search.

This paper presents a joint discrete-continuous model for activity-travel time allocation by employing the ordered probit model for departure time choice and the hazard model for travel time prediction. Genetic algorithm GA is employed for optimizing the parameters in the hazard model. The joint model is estimated using data collected in Beijing, 2005. With the developed model, departure and travel times for the daily commute trips are predicted and the influence of sociodemographic variables on activity-travel timing decisions is analyzed. Then the whole time allocation for the typical daily commute activities and trips is derived. The results indicate that the discrete choice model and the continuous model match well in the calculation of activity-travel schedule. The results also show that the genetic algorithm contributes to the optimization and thus the high accuracy of the hazard model. The developed joint discrete-continuous model can be used to predict the agenda of a simple daily activity-travel pattern containing only work, and it provides potential for transportation demand management policy analysis.