Using Simulation-Based Testing to Evaluate the Safety Impact of Network Disturbances for Remote Driving

Sammanfattning: The transportation industry has been transforming because of rapid digitalization and autonomy. Because of this the demand for more connected and autonomous vehicles is increasing for both private individuals and businesses. Reducing human interaction emphasizes the need for higher road safety. Autonomous vehicles, in general, have different sources of faults which might lead to severe accidents and injuries. Testing and validating autonomous vehicles can be useful for avoiding such cases. Remote driving is a potential fallback option whenever autonomous vehicles fail. The remote operator can take direct or indirect control of the remotely-operated vehicle whenever the need arises. Tele-operated driving has three main parts - the vehicle, the remote operator, and communication between the two. Communication plays an important role in this feedback control system. Any communication disturbance in the video feed from the vehicle to the remote operator or in the commands from the operator to the vehicle can result in safety violations and even accidents. These disturbances can have different sources. This work presents a methodology to inject network disturbances to analyze the effect of these disturbances on vehicle manoeuvrability. A driving simulator, CARLA, was used as a vehicle model to solve this problem and to allow human-in-the-loop. NETEM was used to inject different faults on the outgoing traffic to emulate network disturbances. The implementation was done on LocalHost to avoid any delays that might occur due to the presence of physical devices in the network. It was concluded from the Time-to-Collision (TTC) results that road safety decreased whenever the fault was injected in a vehicle-following case. Another important insight was that the packet loss of 5% always showed a TTC violation for a 6-sec threshold. The highest steering reversal rate was also observed for 5% packet loss. It was observed from the results that the steering reversal rate (SRR) was consistently higher in the faulty run. This indicates that the drivers were more distracted. Based on the results, it is observed that network disturbances affected driving in a remote driving setup. The results can be further utilized for more comprehensive studies to understand how simulator-in-loop can be used for testing, verification, and validation.