2010•Journal of the Transportation Research ForumRequires access

The Journey to Work: 25 Years on the Jamaicaway

C D Martland

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Abstract

More than 600 observations were recorded for the author's home-to-work trip for the same route from Boston to Cambridge, Mass., over the period 1980 to 2004. With this data, it is possible to graph the pattern of travel times and travel time reliability as a function of departure times during the morning rush hour. The image of rush hour performance that emerges from this study is more complex than what is often used in network models or abstract economic analysis. For example, as rush hour progresses, variability increases even though expected travel times start to decline. There may also be lulls in rush hour, i.e. intervals of 10-15 minutes when expected trip times and reliability temporarily improve. This type of performance cannot realistically be modeled as a linear function of traffic volume, nor can it be approximated using a steady state queuing analysis. It will be far better to view rush hour performance as a steady state cyclical queuing phenomenon: every day may start afresh, but expected conditions on next Tuesday at 8:30 am are likely to be similar to conditions last Tuesday at that time.Over the 25-year period, there was surprisingly little change in rush hour performance on this congested urban route. Average travel times were mostly in the range of 25-27 minutes with a standard deviation of three to four minutes. There was some spreading of the peak, especially during periods involving major construction, but performance in the most recent period was actually equivalent to performance in the 1980s despite an increase of about 10% in traffic volume. Variability in trip times is mostly related to variability in the delays associated with the most congested

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What this paper is about

More than 600 observations were recorded for the author's home-to-work trip for the same route from Boston to Cambridge, Mass., over the period 1980 to 2004. With this data, it is possible to graph the pattern of travel times and travel time reliability as a function of departure times during the morning rush hour. The image of rush hour performance that emerges from this study is more complex than what is often used in network models or abstract economic analysis. For example, as rush hour progresses, variability increases even though expected travel times start to decline. There may also be lulls in rush hour, i.e. intervals of 10-15 minutes when expected trip times and reliability temporarily improve. This type of performance cannot realistically be modeled as a linear function of traffic volume, nor can it be approximated using a steady state queuing analysis. It will be far better to view rush hour performance as a steady state cyclical queuing phenomenon: every day may start afresh, but expected conditions on next Tuesday at 8:30 am are likely to be similar to conditions last Tuesday at that time.Over the 25-year period, there was surprisingly little change in rush hour performance on this congested urban route. Average travel times were mostly in the range of 25-27 minutes with a standard deviation of three to four minutes. There was some spreading of the peak, especially during periods involving major construction, but performance in the most recent period was actually equivalent to performance in the 1980s despite an increase of about 10% in traffic volume. Variability in trip times is mostly related to variability in the delays associated with the most congested

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Available abstract

More than 600 observations were recorded for the author's home-to-work trip for the same route from Boston to Cambridge, Mass., over the period 1980 to 2004. With this data, it is possible to graph the pattern of travel times and travel time reliability as a function of departure times during the morning rush hour. The image of rush hour performance that emerges from this study is more complex than what is often used in network models or abstract economic analysis. For example, as rush hour progresses, variability increases even though expected travel times start to decline. There may also be lulls in rush hour, i.e. intervals of 10-15 minutes when expected trip times and reliability temporarily improve. This type of performance cannot realistically be modeled as a linear function of traffic volume, nor can it be approximated using a steady state queuing analysis. It will be far better to view rush hour performance as a steady state cyclical queuing phenomenon: every day may start afresh, but expected conditions on next Tuesday at 8:30 am are likely to be similar to conditions last Tuesday at that time.Over the 25-year period, there was surprisingly little change in rush hour performance on this congested urban route. Average travel times were mostly in the range of 25-27 minutes with a standard deviation of three to four minutes. There was some spreading of the peak, especially during periods involving major construction, but performance in the most recent period was actually equivalent to performance in the 1980s despite an increase of about 10% in traffic volume. Variability in trip times is mostly related to variability in the delays associated with the most congested

Key concepts: Rush hour, Queueing theory, Morning, Standard deviation, Reliability (semiconductor), Transport engineering, Operations research, Statistics

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