a) Bus delays in free-flow offsets b) Bus delays in optimised offsets c) Arterial traffic delays in free-flow offsets d) Arterial traffic delays in optimised offsets e) Side street traffic delays in free-flow offsets f) Side street traffic delays in optimised offsets Note: TSPij indicates TSP is provided at intersections i, j. Figure 6: Percentage change in delays in free-flow offsets a) Percentage changes in bus delays b) Percentage changes in arterial traffic delays c) Mean percentage changes in side street traffic delays Figure 7 presents percentage change in delays compared to base bases when offsets are optimised to minimise bus delays. Similar to observation with free-flow offsets, results indicate bus delays decrease and side street traffic delays increase with increasing numbers of intersections with TSP. The reductions in bus delays are higher than the increases in side street traffic delays, particularly in low traffic volumes. In addition, when traffic volumes increase, the increase in side street traffic delays is larger. It can be seen that the reduction in bus delays is not affected by traffic volumes. Since optimised offsets for each scenarios tend to be different, changes in arterial traffic delays are mixed. Figure 7: Percentage change in delays in optimised offsets a) Percentage changes in bus delays b) Percentage changes in arterial traffic delays c) Mean percentage changes in side street traffic delays 4.2. The multiplier effect The effects of TSP combinations and traffic volume on percentage changes in bus and mean side street traffic delays is analysed by a stepwise multiple linear regression analysis. The percentage change in bus delays (PCB) and percentage change in side street traffic delays (PCT) are considered as dependent variables. Traffic volume in 1000vph (), the number of intersections with TSP (), and its non-linear forms such as , are independent variables. It is noted that bus delay savings can be defined as the reduction in bus delays or the negative of PCB. A summary of best-fit regression models is presented in Table 3. Table 3: Regression models for PCB and PCT Regression Free-flow offset Optimised offset coefficients Model 1 Model 2 Model 3 Model 4 PCB PCT PCB PCT
a) Bus delays in free-flow offsets b) Bus delays in optimised offsets c) Arterial traffic delays in free-flow offsets d) Arterial traffic delays in optimised offsets e) Side street traffic delays in free-flow offsets f) Side street traffic delays in optimised offsets Note: TSPij indicates TSP is provided at intersections i, j. Figure 6: Percentage change in delays in free-flow offsets a) Percentage changes in bus delays b) Percentage changes in arterial traffic delays c) Mean percentage changes in side street traffic delays Figure 7 presents percentage change in delays compared to base bases when offsets are optimised to minimise bus delays. Similar to observation with free-flow offsets, results indicate bus delays decrease and side street traffic delays increase with increasing numbers of intersections with TSP. The reductions in bus delays are higher than the increases in side street traffic delays, particularly in low traffic volumes. In addition, when traffic volumes increase, the increase in side street traffic delays is larger. It can be seen that the reduction in bus delays is not affected by traffic volumes. Since optimised offsets for each scenarios tend to be different, changes in arterial traffic delays are mixed. Figure 7: Percentage change in delays in optimised offsets a) Percentage changes in bus delays b) Percentage changes in arterial traffic delays c) Mean percentage changes in side street traffic delays 4.2. The multiplier effect The effects of TSP combinations and traffic volume on percentage changes in bus and mean side street traffic delays is analysed by a stepwise multiple linear regression analysis. The percentage change in bus delays (PCB) and percentage change in side street traffic delays (PCT) are considered as dependent variables. Traffic volume in 1000vph (), the number of intersections with TSP (), and its non-linear forms such as , are independent variables. It is noted that bus delay savings can be defined as the reduction in bus delays or the negative of PCB. A summary of best-fit regression models is presented in Table 3. Table 3: Regression models for PCB and PCT Regression coefficients Free-flow offset Optimised offset Model 1 Model 2 Model 3 Model 4 PCB PCT PCB PCT
ATRF2015_Resubmission_14.docx