# Adaptive Cruise Control with Look-Ahead Anticipation for Driving on Freeways
## 1 Introduction  
Basic human car-following behavior and its impact on traffic stability have been studied extensively in various contexts [1; 2; 3; 4]. Automated driving technologies, mostly aiming at safe maneuver and rider comforts, have received increasing attention in recent years. Automation can partly alleviate the stress of a driver who requires a high level of concentration for driving explicitly in dense traffic. One of the key functionalities of any driving automation system is to regulate the gap with the preceding vehicle. Adaptive cruise control (ACC), which is such a commercially available automation technology equipped in most existing high-end cars, can dynamically control the vehicle speed and maintain a safe gap. Vehicles with ACC can provide smoother driving with less acceleration variation that directly enhances driving confronts and environmental benefits [5]. ACC has the potential to improve driving behavior, ameliorate fuel consumption, and provide driver comfort through in-vehicle driver assistance [6]. The principal objective of ACC is to offer driver assistance by adjusting both the throttle and brake of a vehicle within the restricted acceleration range in a high-speed (e.g., above 40 km/h) driving environment. Recent research on ACC is more focused on the extended range of driving (e.g., stop and go traffic) [7; 8] and enhancing the efficiency of traffic flows [9; 10; 11]. By setting the parameters of ACC, e.g., time gap, it is possible to improve traffic flow capacity and performance. In particular, using bi-directional sensing with inter-vehicle communication, cooperative ACC, called CACC, can control vehicles in a platoon by keeping a short time gap between the pairs of vehicles and improvingtraffic capacity significantly [9; 12; 13; 14; 15]. CACC can be implemented only when a group of dedicated vehicles with connectivity closely move on the same lane and share the same route without the interference or mixing of traditional vehicles. The prospects of CACC are further limited in heterogeneous traffic as the formation of a platoon or resizing a running platoon by incorporating diverse types of vehicles is technically not feasible. For these reasons, CACC has never been implemented on commercial cars, except for some limited experimental purposes [16; 17; 18]. Recent research on ACC or car-following schemes using the connectivity of automated vehicles received tremendous interest. A major part of such research introduces connectivity features to develop an enhanced car-following scheme using modified human car-following models [19; 20; 21]. A robust car-following control strategy is presented considering uncertainty and communication delay [4]. Although research on such connectivity-based driving is necessary for future transportation systems, research related to existing automated car-following technology or ACC found on commercial cars is very limited [22; 23]. Basic ACC studies focus on different spacing or time gap policies for individual vehicles without cooperating or communicating with the other vehicles. Several works examined the impacts of ACC-equipped vehicles (or simply, ACC vehicles) with adaptive time gaps on traffic flow at their various penetration rates [9; 11; 12; 24]. The operating ranges of some commercial ACC are limited to moderate to high speed, e.g., above 40 km/h. ACC often needs to be deactivated when the preceding vehicle brakes sharply unless a very conservative spacing is used [5; 22]. Furthermore, vehicles with such ACC are not always energy efficient, and they may cause shock waves or congestion due to the presence of disturbances in dense traffic. The offline multi-objective optimization technique was used to optimize parameters in order to have a suitable trade-off between safety and performance objectives [25]. These ACCs are unable to finetune their driving behavior dynamically by considering the changing trends of the traffic ahead; therefore, their performances are affected greatly in transient conditions.