# A Generic Framework for Enhancing Autonomous Driving Accuracy through Multimodal Data Fusion
## 2 Background and Motivation
### Overview about Sensors
#### 2.1.1 Sensor Characteristics  
It is important to first establish the general characteristics of these sensors before exploring the specifics of the many sensors utilized in AVs. The selection of sensors in fused and other techniques is critically influenced by the following technical characteristics [5]:  
1. Accuracy: the difference between the actual and measured values, recorded by the sensor. Inadequate data and improper environmental information acquired by the sensors will affect the accuracy of evaluations.
2. Resolution: The negligible dissimilarity between two measured values is far less accurate than the sensor's actual accuracy.
3. Sensitivity: the nominal value that is recognized and calculated. The slope of the output response curve or, more generally, the minimal input of a parameter that will result in a discernible output change is used to characterize a sensor's sensitivity.
4. Dynamic range: the least and highest values attained from the sensors, obtainable with precision.
5. Perspective: The term \"field of view\" is frequently used to describe this (FoV).
6. Active and passive: an inert sensor trusts ambient conditions to distribute statistics, whereas a dynamic sensor releases energy to observe an AV's surroundings.
7. Time scale: the pace of the sensor's frame rate and measuring range rate over time.
8. Output interface: the sensor's output, which might take the form of a cognate energy, automated signal, direct data flow, or data broadcast movement.  
LiDar: LiDAR, or light detection and ranging, was first developed and launched in the 1960s and has since become widely employed in the alignment of aeronautical and aerospace topography. Laser scanner manufacturers produced and sold the first commercial LiDARs with 2000 to 25,000 pulses per second (PPS) for topographic mapping applications in the mid-1990s. LiDAR technology has advanced at an astonishing rate in recent years, and it is now one of the most important sensing technologies for autonomous driving. LiDAR is a distant sensing technique that scatters ray from target objects using infrared/laser beam impulses.  
RADAR: RADAR stands for radio detection and ranging technology, and is a device that uses radio waves to detect things within a certain range. The surface of an object scatters waves back to the RADAR antenna when waves traveling across it (FoV) collide with it during transmission. The RADAR then picks up the backscattered signal (echo) from the object  
Ultrasonic Sensors: In industrial surroundings, ultrasonic sensors are extensively used for various identification errands. They are able to find particles that are hard, fluid, grainy, or crushed. For industrial applications, the sensors generate sonic waves in the 40 kHz to 70 kHz range using sound transducers. Humans may safely hear frequencies in this range since they are above their hearing threshold. A car's parking system may produce sound pressure levels of above 100 dB to assure clear reception, which is identical to the acoustic signal pressure generated by a jet engine. Most ultrasonic sensors detect the time of flight (ToF) of sonic waves between transmission and reception [6].  
Cameras: One of the most extensively utilized devices for monitoring the environment is a camera. A camera detects lights emitted by the surroundings on a photosensitive surface (image plane) through a camera lens to produce clear pictures of the surroundings (placed in front of the sensor). With the right software, affordable cameras can snap high-resolution pictures related to their surrounding environment as well as recognize mobile and immovable impediments in their range of view. These characteristics enable the vehicle's vision system to recognize various objects in off-road vehicles in addition to road signs, traffic signals, road lane markings, and obstacles in on-road vehicles. One of our articles [7] provides a comprehensive analysis of various sensors, outlining their distinct characteristics. Figure 3 illustrates the overview of sensors fixed in AVs.