TY - JOUR
T1 - Cooperative Exchange-Based Platooning Using Predicted Fuel-Optimal Operation of Heavy-Duty Vehicles
AU - Earnhardt, Christian
AU - Groelke, Ben
AU - Borek, John
AU - Pelletier, Evan
AU - Brennan, Sean
AU - Vermillion, Chris
N1 - Publisher Copyright:
© 2000-2011 IEEE.
PY - 2022/10/1
Y1 - 2022/10/1
N2 - Several driving situations exist where fuel-optimal driving in terms of aggregate performance can only be achieved when one or more vehicles incurs a sacrifice in its own fuel consumption. For these situations, an economic incentive is needed to entice that vehicle to participate in aggregate fuel-optimal driving. Focusing on platooning amongst automated heavy-duty vehicles and using real trucking routes, we examine the precise extent to which the benefits of platooning can be expanded through the incorporation of exchange-based incentives. We focus on two mechanisms for incentivized platooning: (i) incentivized 'catch-up' along a prescribed highway route and (ii) incentivized re-routing to allow for platooning. For the incentivized 'catch-up' mechanism, platoon capable vehicles begin at staggered positions, using a novel platoon catch-up algorithm capable of determining the fuel-optimal platoon engagement position and fuel-optimal velocity trajectories. Additionally, the incentivized re-routing mechanism determines the optimal route for a network of platoon-capable vehicles, allowing for a vehicle to reroute its trajectory to engage within the platoon. Because such scenarios will be shown to frequently lead to aggregate benefit, while actually hurting the fuel economy of one or more participants, we propose three methods for explicitly computing the monetary value of the exchange. Assuming a known trajectory and traffic pattern, the first uses the Shapley value to determine the exchange value. The second method adjusts the Shapley value, accounting for uncertainty associated with traffic modeling. The final method assumes a competitive market, requiring each individual operator to implement a bid.
AB - Several driving situations exist where fuel-optimal driving in terms of aggregate performance can only be achieved when one or more vehicles incurs a sacrifice in its own fuel consumption. For these situations, an economic incentive is needed to entice that vehicle to participate in aggregate fuel-optimal driving. Focusing on platooning amongst automated heavy-duty vehicles and using real trucking routes, we examine the precise extent to which the benefits of platooning can be expanded through the incorporation of exchange-based incentives. We focus on two mechanisms for incentivized platooning: (i) incentivized 'catch-up' along a prescribed highway route and (ii) incentivized re-routing to allow for platooning. For the incentivized 'catch-up' mechanism, platoon capable vehicles begin at staggered positions, using a novel platoon catch-up algorithm capable of determining the fuel-optimal platoon engagement position and fuel-optimal velocity trajectories. Additionally, the incentivized re-routing mechanism determines the optimal route for a network of platoon-capable vehicles, allowing for a vehicle to reroute its trajectory to engage within the platoon. Because such scenarios will be shown to frequently lead to aggregate benefit, while actually hurting the fuel economy of one or more participants, we propose three methods for explicitly computing the monetary value of the exchange. Assuming a known trajectory and traffic pattern, the first uses the Shapley value to determine the exchange value. The second method adjusts the Shapley value, accounting for uncertainty associated with traffic modeling. The final method assumes a competitive market, requiring each individual operator to implement a bid.
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U2 - 10.1109/TITS.2022.3169390
DO - 10.1109/TITS.2022.3169390
M3 - Article
AN - SCOPUS:85129394040
SN - 1524-9050
VL - 23
SP - 17312
EP - 17324
JO - IEEE Transactions on Intelligent Transportation Systems
JF - IEEE Transactions on Intelligent Transportation Systems
IS - 10
ER -