# Adaptive Cruise Control with Look-Ahead Anticipation for Driving on Freeways
## 3 Evaluation of the Proposed La-ACC
### Impact of La-ACC Vehicles on Freeway Traffic  
Although numerical simulation conducted in controlled scenarios using a few vehicles, as described above, is a typical evaluation approach found in the literature, we consider further evaluation in more realistic traffic using a traffic simulator. Note that experimenting with any driving system by applying on many cars in traffic is not feasible at this point in time. In real traffic, a vehicle often necessitates braking aggressively, e.g., for cut-in, merging, or any emergency. In such situations, La-ACC may be required to be deactivated too. Furthermore, the estimated acceleration of the preceding vehicle, hence the corresponding look-ahead state, deviates from the actual value found later. Such deviations may affect the performance of the La-ACC vehicle. Considering these facts, La-ACC vehicles' behavior is  
Figure 4: Flowing behavior of ten vehicles in a platoon, where they are all controlled by (**a**) ACC and (**b**) La-ACC. The red curves show the deactivated period of ACC when they are driven by a human driver. investigated in naturalistic traffic using the AIMSUN Microscopic Traffic Simulator [40]. In the simulator, arbitrary vehicles are controlled by La-ACC on a freeway-ramp network with a merging zone of 50 m, as shown in Figure 5. On the freeway, some vehicles are randomly selected as the host vehicle and controlled by La-ACC. Using an application program interface (API), relevant traffic information from the simulator is obtained to control the host vehicles at every simulation interval of 0.2 s. The incoming traffic on the main road and the ramp is set at approximately 1200 Veh/h and 350 Veh/h, and the desired speeds of the vehicles are sampled from a truncated normal distribution (between 75 km/h to 90 km/h) by the simulator. Figure 6a illustrates the initial conditions of five vehicles, where vehicles 1 and 2 are the host vehicles, and the others are human-driven (according to the Gipps car-following model [1], which is the default control scheme in the AIMSUN simulator). The host vehicles (1 and 2) and their follower vehicles (3 and 4) are observed closely over a distance of 500 m, including 250 m before the merging point and 200 m after the merging zone. With the same aggressive braking behavior of the leading vehicle (vehicle 0) near the merging zone, both the host vehicles are driven by the original ACC and La-ACC in independent simulation, and the corresponding results are shown in Figure 6b,c, respectively. Both ACCs have to be deactivated as the speeds fall below 20 km/h. However, the vehicles with La-ACC exhibit better speed response than that of the ACC vehicles; consequently, the followers of La-ACC vehicles also improve their speed response while approaching the merging zone. For obtaining a more careful distinction between ACC and La-ACC, the average speed and fuel consumption of these five vehicles are compared in Figure 7a,b, respectively. Due to the abrupt deceleration of the leading vehicle at the merging zone, the second ACC vehicle (vehicle 2) oscillated its speed (Figure 6b); consequently, it exhibits the worst average speed and fuel consumption. However, with La-ACC (Figure 6c), both vehicles 1 and 2 show better average speed and fuel consumption; consequently, their followers, vehicles 3 and 4, also benefit from their behavior. Finally, the impacts of a small part of La-ACC or ACC vehicles on overall traffic are investigated over a one-hour simulation with the same traffic settings to the network. In this investigation, some vehicles are randomly selected as the host vehicles, and they are driven by La-ACC or ACC in independent simulation. Since ACC vehicles are not string-stable, to avoid high penetration rates of La-ACC or ACC vehicles, the maximum number of the host vehicles is limited to two at a time on the network. Note that approximately 2.3% of vehicles are found to be controlled either by ACC or La-ACC in a one-hour simulation.