**3. Microscopic Tra**ffi**c Simulation Modeling and Results**

INTEGRATION software, which has been utilized and validated for a number of traffic control applications, was used in the simulations in this study. The model provides a reasonable assessment of how the studied intersection functions.

## *3.1. Analysis of Alternative Intersection Control Strategies: Roundabout, Tra*ffi*c Signal, and Stop Sign Control*

Driving behavior and deceleration/acceleration events were modeled at a roundabout, a two-way stop sign, and a signalized intersection using INTEGRATION software. The intersection of Ariane Way and Virginia 606 in Loudoun County, Virginia—which is adjacent to the Washington Dulles Airport (Figure 1)—was used as the case study site.

The test intersection is typically used as a substitute route for airport travelers. The speed limit is 88 km/h for eastbound and westbound and 40 km/h for northbound and southbound. Northbound and southbound traffic is controlled by two-way stop signs. The average afternoon peak hour traffic volumes are shown in Figure 1. Virginia 606 is a four-lane corridor with an extra left-turn lane, and Ariane Way has two lanes. While traffic volume is low during non-peak hours, travel time and delays are significantly increased at the two-way, stop-controlled intersection during peak hours. The typical queue length at Ariane Way is from 10 to 15 vehicles and those vehicles make for unsafe gap-acceptance maneuvers through the high-speed approaching vehicles from eastbound and westbound directions.

We developed simulation models using parameters derived from field data, including speed, traffic volume, saturation flow rate, jam density, number of lanes, and lane striping data. We modeled a base saturation flow rate and a jam density of 1800 veh/h/lane and 120 veh/km/lane, respectively, for all links except the northbound approaches. Due to the aggressive driving behavior of the

northbound approaches, we used a saturation flow rate of 2000 veh/h/lane. We set the base gap between 3 and 4 s to simulate the driver gap behaviors. We calibrated and validated the simulation model against collected field data. For signalized intersection scenarios, we designed two phase movements with a 35 s cycle length, which was estimated based on the traffic demand. For roundabout scenarios, we used an entry speed of 50 km/h and a diameter of 60 m, which were recommended in *Roundabouts: An Information Guide* [20].

**Figure 1.** Map and aerial view of the modelled intersection (Source: Google Maps).

The BEVs' energy consumption was estimated using VT-CPEM from individual second-by-second profiles of vehicle speed that were generated using the INTEGRATION simulation. The ICEV fuel consumption was generated directly from the INTEGRATION software, since INTEGRATION includes the VT-Micro model. Three approach speeds, 56 km/h (35 mph), 72 km/h (45 mph), and 88 km/h (55 mph) were evaluated to identify the effects of different approach speeds.

Figure 2 compares the simulated ICEV fuel consumption and BEV energy consumption at a roundabout, a signalized intersection, and a two-way stop-sign-controlled intersection for an approach speed of 88 km/h. BEVs and ICEVs clearly had different energy/fuel consumption patterns. We converted ICEV fuel consumption to a comparable energy consumption unit, kWh based on Reference [21]. Based on the report, one liter of gasoline contains the energy equivalent to 8.9 kWh of electricity. The fuel consumption of ICEV increased by 126% and 79% when the stop-sign-controlled intersection was replaced with a roundabout and a signalized intersection, respectively. In contrast, for BEVs, the roundabout reduced energy consumption by 2.3% and 8.4% compared to the stop-sign-controlled and signalized intersections, respectively. The roundabout decreased total delay by 68% (from 18.81 to 6.07 s/veh) compared to the stop-sign-controlled intersection and by 45% (from 8.78 to 6.07 s/veh) compared to the signalized intersection. These results demonstrate that, for the modeled intersection, a roundabout would improve BEVs' energy efficiency, whereas ICEVs would have better fuel economy at a two-way stop-controlled intersection.

Figure 3 illustrates BEV and ICEV energy/fuel consumption for different intersection controls with an approach speed of 72 km/h. For ICEVs, the results were similar to those obtained at the approach speed of 88 km/h; the stop-sign-controlled intersection was the most fuel efficient, while the roundabout led to the worst fuel economy. However, for BEVs, the stop-sign-controlled intersection was slightly more energy efficient than the other two control strategies, although the energy consumption was similar for all three control types (0.15, 0.15, and 0.14 kWh/veh for the roundabout, signalized intersection, and stop-sign-controlled intersection, respectively). The roundabout considerably reduced vehicle delay by 46% and 78% compared to the signalized and stop-sign-controlled intersections, respectively.

**Figure 2.** Comparison of battery electric vehicle (BEV) and internal combustion engine vehicle (ICEV) energy/fuel consumption for different intersection control strategies (approach speed = 88 km/h).

**Figure 3.** Comparison of BEV and ICEV energy/fuel consumption for different intersection control strategies (approach speed = 72 km/h).

The BEV and ICEV energy/fuel consumption levels at the different intersections are shown in Figure 4 for an approach speed of 56 km/h. For ICEVs, the stop-sign-controlled intersection was the most fuel efficient, while the signalized intersection was the least fuel efficient. For BEVs, the energy efficiencies were nearly identical (0.12 kWh/veh) for all three control strategies. As for the other approach speeds, the roundabout was the most efficient intersection control type in terms of vehicle delay.

**Figure 4.** Comparison of BEV and ICEV energy/fuel consumption for different intersection control strategies (approach speed = 56 km/h).

The simulation results for all evaluated approach speeds show that the roundabout significantly reduced vehicle delay compared to the signalized and stop-sign-controlled intersections. For ICEVs, the stop-sign-controlled intersection significantly reduced fuel consumption compared to the other two control methods at all three approach speeds, and the roundabout resulted in the worst fuel

efficiency at approach speeds of 88 and 72 km/h. The ICEVs' higher fuel consumption in the roundabout resulted from the acceleration of vehicles leaving the roundabout. A vehicle entering a roundabout must yield or stop before entering the roundabout; thus, after negotiating the roundabout, the vehicle must accelerate to full speed upon exiting, increasing the rate of fuel consumption. Acceleration rate is one of the most important contributors to vehicle fuel consumption [19,22].

Compared to ICEVs, BEVs' energy consumption patterns were significantly different. For example, at an approach speed of 88 km/h, the roundabout was the most energy-efficient intersection, whereas the stop-sign-controlled intersection resulted in the lowest electricity usage at the approach speed of 72 km/h. Nonetheless, the differences in BEV energy consumption between the different intersection types were relatively small compared to the fuel consumption of ICEVs. These results can be explained by the energy BEVs regenerate during deceleration.

Figure 5 illustrates the average recovered energies corresponding to the three intersection controls at different approach speeds. The regenerative energy produced increased with increasing approach speed. For the roundabout, BEVs generated 193% more regenerative energy at an approach speed of 88 km/h compared to an approach speed of 56 km/h. Figure 5 also demonstrates that BEVs recovered more energy at the roundabout compared to the signalized and stop-sign-controlled intersections. Table 1 shows the percentage of regenerated energy compared to total BEV energy consumption. For example, BEVs recovered 32.9% of the total energy through regenerative energy at the roundabout with an approach speed of 88 km/h. These results indicate that regenerative energy is critical to BEVs maintaining their energy efficiency at roundabouts.

**Figure 5.** BEV's regenerative energy generated for different intersection control strategies and approach speeds.

**Table 1.** Percentage of regenerated energy compared to total BEV energy consumption.

