Platooning heavy-duty vehicles (HDVs) on a highway is a method for improving energy and transport efficiency. On one hand, HDV platoon driving in small intervehicle distances could increase highway capacity; on the other hand, HDVs traveling in small intervehicle distances experience significant air-drag reduction and, therefore, improve fuel efficiency. However, although the majority of research has been conducted on the development of platoon systems, very few studies have focused on quantification of the impacts of HDV platooning on traffic flow. This paper initializes a simulation framework to facilitate the study of HDV platooning and establishes the corresponding concept and operations. The longitudinal driving behaviors of HDV platoons are modeled in detail, considering the acceleration capability of an HDV. The proposed framework is applied on three experimental cases: the first case is to study the impacts of HDV platooning on traffic flow and the second and third cases are about the influence of traffic on HDV platoon formation. In the first case, simulation outcomes show that the increasing percentage of HDV platooning in traffic flow generally results in more dramatic improvements on traffic efficiency, while preserving traffic safety for passenger vehicles. In the second and third cases, for the HDV platoon formation, deceleration of the first HDV to a low speed during platoon formation will increase the formation time to a large extent in medium and heavy traffic.

Heavy-duty vehicle (HDV) platooning is a mean to significantly reduce the fuel consumption for the trailing vehicle. By driving close to the vehicle in front, the air drag is reduced tremendously. Due to each HDV being assigned with different transport missions, platoons will need to be frequently formed, merged, and split. Driving on the road requires interaction with surrounding traffic and road users, which will influence how well a platoon can be formed. In this paper, we study how traffic may affect a merging maneuver of two HDVs trying to form a platoon. We simulate this for different traffic densities and for different HDV speeds. Even on moderate traffic density, a platoon merge could be delayed with 20% compared to the ideal case with no traffic. 

To meet policy requirements on increased transport energy efficiency and reduced emissions, smart control and management of vehicles and fleets have become important for the development of eco-friendly intelligent transportation systems (ITS). The emergence of new information and communication technologies and their applications, particularly vehicle-to-vehicle and vehicle-to-infrastructure communication, facilitates the implementation of autonomous vehicle concepts, and meanwhile serves as an effective means for control of vehicle fleet by continuously providing support and guidance to drivers. While convoy driving of trucks by longitudinal automation could save 5-15% of fuel consumption due to the reduction of airdrag resistance, this study attempts to investigate the energy saving potential of truck platoons by intelligent speed planning. Assuming that real-time traffic information is available because of communication, an efficient speed control algorithm is proposed based on optimal control theory. The method is faster than the conventional dynamic programming approach and hence applied in the study to analyze energy saving potential of simple platoon operations including acceleration and deceleration. The numerical result shows significant improvement on energy saving due to speed planning during platooning. It can be further applied for more complex platooning operations.

To meet policy requirements on increased transport energy eciency and reduced emissions, smart control and management of vehicles and eets have become important for the development of eco-friendly intelligent transportation systems (ITS). The emergence of new information and communication technologies and their applications, particularly vehicle to vehicle and vehicle-to-infrastructure communication, facilitates the implementation of autonomous vehicle concepts, and meanwhile serves as an eective means for control of vehicle eet by continuously providing support and guidance to drivers. While convoy driving of trucks by longitudinal automation could save 5-15% of fuel consumption due to the reduction of airdrag resistance, this study attempts to investigate the energy saving potential of truck platoons by intelligent speed planning. Assuming that real-time trac information is available because of communication, an ecient speed control algorithm is proposed based on optimal control theory. The method is faster than the conventional dynamic programming approach and hence applied in the study to analyze energy saving potential of simple platoon operations including acceleration and deceleration. The numerical result shows signicant improvement on energy saving due to speed planning during platooning. It can be further applied for more complex platooning operations.