Researchers Quantified Energy Consumption and Travel Delay Benefits of Eco-Cooperative Adaptive Cruise Control Systems for Hybrid Electric Vehicles at Signalized Intersections Using Both Microsimulation and a Driver Simulator.
Baltimore, Maryland, United States
Developing and Testing an Advanced Hybrid Electric Vehicles Eco-Cooperative Adaptive Cruise Control System at Multiple Signalized Intersections
Summary Information
Vehicle acceleration and deceleration maneuvers and idling near signalized intersections increase vehicle energy consumption and emission levels on arterial roads. Connected and automated vehicles (CAV) can be used to develop Eco-driving strategies to provide real-time recommendations to drivers in the vicinity of intersections to improve mobility and reduce energy consumption and emissions. The objective of this study was to develop an advanced Eco-Cooperative Adaptive Cruise Control System (Eco-CACC) for hybrid electric vehicles (HEVs) to pass signalized intersections with energy-optimized speed profiles, with the consideration of impacts along multiple signalized intersections. This study extended the researchers’ previous study from 2019, in which they developed Eco-CACC-I for Internal Combustion Engine Vehicles (ICEV), by using a simple HEV energy model to compute the instantaneous energy consumption levels corresponding to each speed profile under consideration, both for single and multiple intersections. The performance of the Eco-CACC-I controller under the impact of signal timing, speed limit, and road grade was evaluated via microscopic simulation case studies, and driver simulator tests.
METHODOLOGY
In this study, in addition to the HEV energy model, a vehicle dynamics model was used to capture the relationship between speed, acceleration level and tractive and/or resistance forces on vehicles. The constraints of energy model and vehicle dynamics were then used to develop two HEV Eco-CACC-I controllers for single-intersection and multiple-intersection cases. Two case studies were analyzed using microsimulation, in which all vehicles in the network were HEVs.
- In the first case study, the performance of HEV Eco-CACC-I controller was evaluated network-wide with three signalized intersections in which each controller worked independently. Two scenarios were considered: Scenario 1 without the HEV Eco-CACC-I controller and Scenario 2 with the HEV Eco-CACC-I controller. For each scenario, various traffic demand levels (400, 800 and 1200 vehicles per hour per lane (veh/hr/ln) on the main street were tested.
- In the second case study, the performance of Eco-CACC-I for multiple intersections (Eco-CACC-I MS) was evaluated for a simulation network consisting of two signalized intersections. The Eco-CACC-I MS controller searched for the acceleration levels to minimize the energy consumption of the controlled vehicle over the entire control section. Three scenarios were considered: Scenario 1: No control, Scenario 2: controller activated per intersection independently, and Scenario 3: Controller activated for multiple intersections together. Various traffic demand levels below the saturated flow (100, 200, 400, and 800 vehicles per hour per lane (veh/hr/ln)) were used in this case study.
The developed HEV Eco-CACC-I algorithm was then implemented in a driving simulator with 48 participants to test the
participants’ performance with following the recommended speed advisories compared to a baseline scenario without the speed advisories.
FINDINGS
Results from the first microsimulation case study in which the HEV Eco-CACC-I controller was applied to single intersections individually revealed the following findings:
- The energy reductions were 9.5 percent, 6.9 percent, 5.8 percent for traffic demand levels of 400, 800 and 1200 veh/hr/ln, respectively.
- The reductions in total delay were 4.6 percent, 4.1 percent, and 8.8 percent for traffic demand levels of 400, 800 and 1200 veh/hr/ln, respectively.
- After combining all the results under the same origin-destination demand levels, the average savings for energy consumption, traffic delay, and vehicle stops were 7.4 percent, 5.8 percent, and 23 percent, respectively.
Results from the second microsimulation case study in which the HEV Eco-CACC-I controller was applied to multiple intersections revealed the following findings:
- HEV Eco-CACC-I controllers (Scenario 2 and 3) produced energy savings for all demand levels compared to the Scenario 1 (without the Eco-CACC-I controller).
- The average energy savings from Scenario 2 were 3.5 percent, 4.7 percent, 6.3 percent, and 6.1 percent for demand levels of 100, 200, 400, and 800 veh/hr/ln, respectively.
- Scenario 3 further improved the average energy savings by 8.9 percent, 9.8 percent, 10.6 percent, and 10.3 percent for demand levels of 100, 200, 400, and 800 veh/hr/ln, respectively.
- The demand of 400 veh/h/lane resulted in the maximum energy savings of 10.6 percent for the entire traffic network.
Results from the driving simulator indicated that the average fuel savings in the Eco-CACC-I scenarios was 32 percent when compared to the no guidance scenario, confirming the effectiveness of the application of the proposed controller system for HEVs.
