would produce not only output files, but indications of the output’s performance compared to given benchmarks, such the next run would then use these indications to recalibrate the simulation’s parameters. This would allow the simulation to be represented as a Markov Chain, opening up the possibility to further mathematical analysis. The level of precision that such a synthesizer provides with regards to travel demands of individuals is one that would be vital to modeling an Advanced Transit System, which aims to rival the automobile in accessibility and mobility. More and more, the system that stands out as being closest and most likely to reaching technical and commercial viability is the automated taxi (aTaxi). Figure 30 Grid corner points. Top right: Grid pixels near Princeton, NJ Building on the idea of having stations, or in this case taxi stands, at walking distance to most residents, a suitably simple method to start such an analysis is to pixelate the area in question, hence discretizing the spatial distribution of trips. Each pixel could be a half mile on each side and a grid of such pixels could easily replace the geographic coordinate system of latitudes and longitudes. With a simple transformation that converts coordinates to suitably sized pixels, the analysis would trade the unnecessarily high level of precision for simplified analysis through the use of integers. An example of such a grid and its corner points can be seen above in Error! Reference source not found.. Modeling an aTaxi network realistically and optimizing taxi stand locations to meet travel demand could be the first step to a bright future of advanced transit in the state of New Jersey by implementing a safer, cheaper, and greener way to get around.
would produce not only output files, but indications of the output’s performance compared to given benchmarks, such the next run would then use these indications to recalibrate the simulation’s parameters. This would allow the simulation to be represented as a Markov Chain, opening up the possibility to further mathematical analysis. The level of precision that such a synthesizer provides with regards to travel demands of individuals is one that would be vital to modeling an Advanced Transit System, which aims to rival the automobile in accessibility and mobility. More and more, the system that stands out as being closest and most likely to reaching technical and commercial viability is the automated taxi (aTaxi). Figure 30 Grid corner points. Top right: Grid pixels near Princeton, NJ Building on the idea of having stations, or in this case taxi stands, at walking distance to most residents, a suitably simple method to start such an analysis is to pixelate the area in question, hence discretizing the spatial distribution of trips. Each pixel could be a half mile on each side and a grid of such pixels could easily replace the geographic coordinate system of latitudes and longitudes. With a simple transformation that converts coordinates to suitably sized pixels, the analysis would trade the unnecessarily high level of precision for simplified analysis through the use of integers. An example of such a grid and its corner points can be seen above in Error! Reference source not found.. Modeling an aTaxi network realistically and optimizing taxi stand locations to meet travel demand could be the first step to a bright future of advanced transit in the state of New Jersey by implementing a safer, cheaper, and greener way to get around.
T%20Mufti%20MSE.docx