Developing and Field Implementing an Ecocruise Control System in the Vicinity of Traffic Signalized Intersections
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Developing and Field Implementing an Ecocruise Control System in the Vicinity of Traffic Signalized Intersections

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  • English

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    • Abstract:
      The research develops Eco-CACC algorithms by considering a single intersection, multiple intersections, and field implementation for human drivers and automated vehicles. The INTEGRATION microscopic traffic assignment and simulation software is used to evaluate the performance of the proposed Eco-CACC algorithm by considering isolated intersection to assess its network-wide energy and environmental impacts. The analysis also demonstrates that the length of control segments, the SPaT plan, and the traffic demand levels significantly affect the algorithm performance. This research also develops Eco-CACC-MS algorithms to minimize fuel consumption for vehicles to pass multiple intersections. Simulation of the single-lane intersections proved that fuel consumption savings were greater at higher MPRs. The reductions in fuel consumption reached 7% for Eco-CACC-MS-Q and 4.2% for Eco-CACC-Q at 100% MPR. And, taking the vehicle queue into consideration, the Eco-CACC-MS-Q algorithm always performed better than Eco-CACC-O. In the two-lane intersection, due to lane-changing and passing behaviors, the proposed algorithm increased the total fuel consumption levels when the MPRs were less than 30%. Once the MPRs were larger than 30%, positive savings could be observed. In addition, the Eco-CACC-MS algorithm was implemented in a network with four consecutive intersections, and the fuel consumption savings were also observed to be as high as 7.7% for single-lane roads, and 4.8% for two-lane roads. Moreover, the Eco-CACC algorithm is implemented into an Eco-CACC system in the VTTI automated vehicle. In the Eco-CACC system, the computed speed profile can either be broadcasted as audio alert to the driver to manually control the vehicle, or be implemented into the automated vehicle (AV) to automatically control the vehicle. From an implementation standpoint the research addresses the challenges associated with communication latency, data errors, real-time computation, and ride smoothness. The system was tested in the Virginia Smart Road Connected Vehicle Test Bed. Four scenarios were tested for each participant under different combination of signal timing and road grade. The analyzed results demonstrate the benefits of the Eco-CACC system in assisting vehicle to drive smoothly in the vicinity of intersections and therefore reduce the fuel consumption levels. Compared to the uninformed drive, the longitudinally automated Eco-CACC system controlled vehicle resulted in savings in fuel consumption levels and travel times in the range of 37.8 and 9.3 percent, respectively.
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      Performing Organization Code KLK900-SB-002
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