A R T I C L E I N F O

A B S T R A C T

1. Introduction

2. Modular system architecture  
2.1. Components of modular pipeline  
2.2. Input and output modality of modular pipeline  

3. End-to-End system architecture  

4. Input modalities in End-to-End system  
4.1. Camera  
4.2. LiDAR  
4.3. Multi-modal  
4.4. Navigational inputs  

5. Output modalities in End-to-End system  
5.1. Waypoints  
5.2. Cost function  
5.3. Direct control and acceleration  
5.4. Auxiliary output  

6. Learning approaches for End-to-End system  
6.1. Imitation learning  
6.2. Reinforcement learning  

7. Learning domain adaptation from simulator to real  

8. Safety  

9. Explainability  
9.1. Local explanations  
9.2. Global explanations  

10. Evaluation  

11. Datasets and simulator  
11.1. Datasets  
11.2. Simulators and toolsets  

12. Future research directions  
12.1. Learning robustness  
12.2. Enhanced safety  
12.3. Advancing model explainability  
12.4. Collaboration perception systems  
12.5. Large language and vision models  

13. Conclusion