Spatial-Temporal Association of Duration of Peak Period at Signalized Intersections

In the case of peak spreading, the traditional static analysis on the duration of congestion using peak 15 minutes of hour has lost its meaning. To deal with congestion, we need dynamic analysis on the onset and dissipation of congestion. This paper aims to reflect the severity of congestion, even the spatial interaction of congestion, by the relative size of peak period. Two thresholds, the minimum value in the peak hour and 95 percent of peak hour volume respectively, were chosen to define the peak using archived stop-bar detector data. The thresholds and the time-granularity of the data were cross-compared to choose appropriate threshold and data time interval, and the result is 95 percent of peak hour volume under 10min interval data. Then the measures of duration of peak period, including the length of peak period, the beginning and ending time of peak period, were calculated for different signalized intersections inlet approaches. Further, the measures of peak period of different intersections in the same direction of the same radial road were presented to find out the commute traffic patterns. Lastly, the spatial-temporal association pattern of the measures of peak period of different intersections in downtown Shanghai was performed by ArcGIS.

Analysis of work trip timing and mode choice in the Greater Toronto Area

This paper focuses on examining and analyzing observed trends in work trip making in the Greater Toronto Area (GTA). Commuter trip timing and mode choice behaviour are investigated to explain the main reasons behind peak spreading observed in cordon count data from 1975 through 2004 and to better understand the relationship between modal and temporal decisions. From analysis it becomes clear that significant differences exist in the trip timing trends of individuals choosing different modes. Multinomial logit mode choice models are developed for separate occupation groups, revealing significant differences in the mode choice preferences between occupation groups. Such differences are related to the differences in occupation-specific factors, including labour rates, work hour rules, free parking availability, and the spatial distribution of work locations. Overall, the investigations of this paper indicate that a joint analysis and modelling of trip timing and mode choice has considerable merit in travel demand models.