# Data-Driven Test Scenario Generation for Cooperative Maneuver Planning on Highways
## 3 Results
### Case Study  
In order to identify the scenarios that are to be part of the scenario catalog, a naturalistic driving dataset is split into scenarios, which are then evaluated using the reference and the cooperative planner, as described in Section 2.2. This assessment process is illustrated using an exemplary scenario. The solution computed by the planners is depicted by means of two plots each. The first plot (Figure 3), referred to as the lateral plot, shows the scenario from the bird's eye perspective in each relevant time step. Besides the start and end of the scenario, relevant time steps are the first time steps of and after a lane change. The second plot (Figure 4) shows the velocity of all involved vehicles in solid lines as well as their desired velocities in horizontal dashed lines. The vertical dashed lines indicate the time steps where a lane change starts or ends. These time steps are the relevant time steps depicted in the bird's eye perspective plot and are assigned by unique numbers.  
The start situation is the same for both simulations. The lead vehicle 3 (red) drives in lane 2 at its desired velocity of \(26\,\mathrm{m}\,\mathrm{s}^{-1}\), followed by vehicle 1 (orange) at a lead distance of \(26.4\,\mathrm{m}\) and a speed of \(24.3\,\mathrm{m}\,\mathrm{s}^{-1}\). Both vehicles are approached by the small blue truck (vehicle 0) approaching at a considerably higher velocity of \(34\,\mathrm{m}\,\mathrm{s}^{-1}\). Due to its greater desired speed of \(34.6\,\mathrm{m}\,\mathrm{s}^{-1}\), it might want to overtake vehicles 1 and 2 during the scenario. In lane 1, vehicle 2 (green) catches up at \(35.4\,\mathrm{m}\,\mathrm{s}^{-1}\) and might block the blue truck from making a future lane change. The leftmost lane 0 is not occupied.  
Figures 3 and 4 show the solution of the reference IIDM planner. The blue truck changes to the left in time step \(t=0.2\,\mathrm{s}\) in order to overtake vehicles 1 and 3. To ensure a safe distance to vehicle 1 during the lane change, it decelerates subject to the IIDM until the end of the lane change at \(t=6.1\,\mathrm{s}\). Since vehicle 2 now has a slower object in front, it also starts a lane change to the free lane 0 at \(t=4.3\,\mathrm{s}\). Until the end of its lane change at \(t=8.2\,\mathrm{s}\), it must consider the slower blue truck as its lead vehicle and therefore decelerate. After their lane changes, vehicles 0 and 2 accelerate toward their respective desired velocities subject to the IIDM. The decelerations, the associated time loss, and the lane changes result in scenario costs of 7.6 according to the evaluation function presented in Section 2.3.  
The cooperative planner solves the scenario in a different way as depicted in Figures 5 and 6. In the computed solution, vehicle 1 accelerates over its desired velocity (dashed lines in Figure 6), making way for vehicle 0. Thus, the blue truck has more room for its lane change, allowing it to maintain its initial speed. Therefore, vehicle 2 is not affected by the blue truck until the end of the scenario. After the lane change, vehicles 0 and 1 approach their respective desired velocities. The scenario costs for the solution computed by the cooperative planner amount to 0.9 according to the cost function introduced in Section 2.3. In comparison to the reference planner solution, vehicle 1 accepts a drawback in terms of a deviation from its desired velocity in order to reduce the overall costs for this scenario. Therefore, it can be regarded as a scenario that benefits from cooperation.  
Figure 3: Lateral plot of the simple planner.  
Figure 4: Longitudinal plot of the simple planner.  
Figure 5: Lateral plot of the global planner.