Effects on Traffic Flow

Table 6.7 and Table 6.8 show results of simulations according to the explanations in Section 6.2. First, we have a look at the differences between real-world traffic evaluated in the former section and RACC-traffic with an equipment rate of 100 %.

At first glance, we can assess an improvement in travel time and waiting time for all combinations of network and switching schemes. The traffic in scenarios with the shorter cycle time benefits more from the RACC, in particular with a decrease of up to 28 % regarding the waiting time. This result corresponds to the intuition that scenarios with a shorter cycle time benefit more as the RACC mainly optimizes the starting maneuvers. Once the traffic flows more or less constantly, the RACC has no impact. Besides the fact that in the four-intersections network possibly more starting maneuvers occur, the gain in traffic flow is higher in the single-intersection network. This is possibly due to the higher density of cars in the smaller network. The values of the environmental parameters show a similar behavior.

Table 6.7: Obtained values for traffic induced by the RACC on the single-intersection network with different switching schemes for the traffic-lights and percentage of equipped cars.

1s|9s|3s|2s¹ 1s|24s|3s|2s¹

10 %² 50 %² 100 %² 10 %² 50 %² 100 %²

travel time [s] 95.23 87.90 78.95 69.49 68.44 66.96

waiting time [s] 63.23 55.85 46.91 37.44 36.39 34.88

fuel consumption [ml] 66.69 61.78 55.01 52.77 50.23 48.11

CO2emissions [g] 152.27 141.07 125.61 120.49 114.70 109.86

Annotations. Values are geometric means per vehicle of five testing instances.

1duration red-amber phase|duration green phase|duration amber phase|duration red phase,

2percentage of cars which are equipped with the RACC

6 Numerical Results 92

Figure 6.8: Visualization of the RACC using SUMO. The green car performs the pole-start-regime while the traffic-light is still red. Yellow cars follow according to the car-following-regime. White cars model real-world traffic.

6 Numerical Results 93

Figure 6.9: Visualization of the RACC using SUMO. The green car performed the pole-start-regime. Because of its acceleration during the red phase, it passed the stopping line with a higher velocity after the traffic-light switched to green. Hence, the green phase might be used more efficiently in terms of traffic flow. Yellow cars follow according to the car-following-regime. White cars model real-world traffic.

The difference between the traveled distances of equipped and non-equipped cars is visible.

6 Numerical Results 94

Figure 6.10: Visualization of the RACC using SUMO. The blue car performs the deferred-transit-regime. The yellow car follows according to the car-following-regime. White cars model real-world traffic.

6 Numerical Results 95

Figure 6.11: Visualization of the RACC using SUMO. The blue car performs the deferred-transit-regime and passes the intersection with the minimum value of desired velocity and 40 kilometers per hour. Hence, the green phase might be used more efficiently in terms of traffic flow. The yellow cars follow according to the car-following-regime. White cars model real-world traffic. The difference between the traveled distances of equipped and non-equipped cars is visible.

6 Numerical Results 96

Figure 6.12: Visualization of the RACC using SUMO. The cyan car performs the free-transit-regime and passes the intersection with the desired velocity. White cars model real-world traffic. Due to the unawareness of an imminent switch to green, the non-equipped car going from right to left decelerates in front of the traffic-light.

6 Numerical Results 97

Figure 6.13: Visualization of the RACC using SUMO. The cyan car performed the free-transit-regime and passed the intersection with its desired velocity. In contrast, the non-equipped car going from right to left had to decelerate and accelerate in front of the traffic-light. The resulting difference in traveled distances is visible.

6 Numerical Results 98 Table 6.8: Obtained values for traffic induced by the RACC on the four-intersections network with different switching schemes for the traffic-lights and percentage of equipped cars.

1s|9s|3s|2s¹ 1s|24s|3s|2s¹

10 %² 50 %² 100 %² 10 %² 50 %² 100 %²

travel time [s] 79.37 78.63 70.91 65.18 64.44 63.13

waiting time [s] 39.73 39.06 31.26 25.55 24.82 24.50

fuel consumption [ml] 65.06 63.60 57.18 54.67 53.66 51.73

CO2emissions [g] 148.58 145.23 130.58 124.85 122.55 118.14

Annotations. Values are geometric means per vehicle of five testing instances.

1duration red-amber phase|duration green phase|duration amber phase|duration red phase,

2percentage of cars which are equipped with the RACC

Focusing solely on the RACC, we recognize the same development of the values between the different switching schemes as in the real-world traffic: in both networks, traffic flow is higher for the longer cycle times of the traffic-lights. Better values for CO2-emissions and fuel consumption can be assessed accordingly.

At this point, we want to investigate the impact of the equipment rate. For a fixed equipment rate, the differences between the scenarios with different cycle times reveal analogous trends for all measured parameters. When the network and switching scheme is fixed, all parameters improve when the equipment rate is increased. We can assess a decrease in travel time of up to 17 % for the short-cycled single-intersection network when increasing the equipment rate from 10 % to 100 %. A sightly lower gain can be determined for the short cycle time in the four-intersections network. We discussed reasons for a higher gain when introducing the RACC for shorter traffic-light cycles above. Worth noticing is the fact that in none of the analyzed scenarios, the RACC leads to a decrease in traffic flow – even for low equipment rates. There is a small increase in CO2-emissions and fuel consumption for the short-cycled four-intersections network with an equipment rate of 10 %. However, the overall effect of the RACC seems to be rather negligible for this scenario when regarding the differences in travel and waiting time.