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On Stochastic Models of Traffic Assignment, Transportation Science, 11 253-274, August 1977.
These, in turn, are used to develop probabilistic traffic relations and stochastic Lagrangian models of traffic dynamics.
The conversation veers into molecular biology or computer models of traffic flow, then just as quickly back to plans for the prom.
Physicists have devised models of traffic flow in which each vehicle is represented by a particle programmed to move according to these rules.
Abstract: Stochastic models of traffic flow are used in a variety of applications, e.g., traffic state estimation, travel time reliability, and traffic control.
Finally, the paper presents some properties which all microscopic models of traffic flow should possess and also tries to identify areas where research will bring about a qualitative jump in the understanding of how traffic flows.
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Therefore, transferability of regression models of traffic-related air pollutants reflected the extent of similarity of local sources and physical surroundings in the different neighborhoods.
Future studies using increasingly sophisticated models of traffic-related air pollutants will require an emphasis on improving geocoding accuracy and integration of time-activity data.
LUR models of traffic-related pollution have shown stronger relationships with children's respiratory outcomes than have simple distance-to-roadway measures [ 10].
Recently, a study of models of traffic-related pollution estimates that included time-activity patterns suggested that the difference between the mobility-based model and residence-only models may lead to risk estimates biased toward the null [ 11].
Other work considered how close pregnant women lived to freeways, or used monitor-based estimates of air pollutants,, or models of traffic-related exposures to study links with ASD risk.
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