# Truck Platoon Control Considering Heterogeneous Vehicles
## 1 Introduction  
This paper is on developing technology that enables autonomous heterogeneous trucks to drive in platoons. A platoon is defined as a collection of trucks where a manually driven truck (leader truck) is followed by several automatically controlled following trucks. In this case, only one trained truck driver is required to lead the entire platoon. Moreover, it is well known that a truck platooning can reduce fuel consumption of a following truck considerably [1]. In the literature on autonomous cars, many works have been done on tracking a curve (lane for autonomous cars) while avoiding collision assisted by vision sensors [2], range sensors [3], or sonar sensors [4]. Specifically, [5] proposed a lane detection algorithm based on Support Vector Machines (SVM) classifier, and a splines-based lane model combined with Kalman filters was used for the tracking algorithm. Reference [6] presented a method of detecting and tracking the boundaries of drivable regions in a road without road-markings. Using vision sensors, an autonomous truck can follow a lane. However, vision sensors may not work in the case where a lane is not clearly visible. Moreover, there may be a case where a vision sensor on an autonomous car is disabled. This paper considers the scenario where the leader truck is driven by a trained truck driver. A trained driver has the ability to perform reliable driving in unstructured environments. For instance, a human driver can control a truck even in environments where there is no lane. Thus, this paper considers the scenario where the leader truck is driven by a trained truck driver. Then, all autonomous trucks follow the leader's trajectory. In summary, driving in truck platoons has the following benefits: 1. Fuel consumption decreases compared to the case where the trucks do not form a platoon. 2. Only one trained truck driver is required to lead the entire platoon even in unstructured environments. The truck platoon control is composed of the lateral control and the longitudinal control. The _lateral control_ is to keep a following truck behind its predecessor truck [7]. In addition, an autonomous truck must change its speed to maintain a designated distance with its predecessor truck. Controlling the speed of a truck is called the _longitudinal control_ of the truck. As far as the author knows, only a few papers handled the lateral control of the truck platoon. Reference [8] introduced a lateral control which depends on lane markings, which are captured by a monocular camera. However, lane markings may not exist in unstructured environments. The lateral control can be performed by letting every truck set its predecessor truck as its reference point. Suppose that one truck is broken and it gets out of its lane. In this case, all trucks behind the broken truck also get out of the lane, since each truck sets its predecessor truck as its reference point. This implies that this following strategy is not robust to truck failures. This paper presents a lateral control which does not depend on lane markings. For lateral maneuver, this paper proposes making every autonomous truck keep following the leader's waypoints while maintaining a designated distance from its predecessor truck. By following the leader's waypoints, one can avoid the case where all trucks after a broken truck get out of the lane. This implies that this following strategy is robust to truck failures. Moreover, [9] mentioned that information on the leader position can stabilize the string of the truck platoon. Many papers developed longitudinal control of the truck platoon as follows. Reference [10] developed a longitudinal control based on a distributed controller known as Cooperative Adaptive Cruise Control (CACC). Reference [11] used consensus control strategy for longitudinal control of truck platoons. The consensus control was used to make the speed of every vehicle converge to the speed of the leader. Reference [12] proposed a reference model-based control approach for automotive longitudinal control.