Statistical signal processing for automotive safety systems

Abstract

The amount of software in general and safety systems in particular increases rapidly in the automotive industry. The trend is that functionality is decentralized, so new safety functions are distributed to common shared computer hardware, sensors and actuators using central data buses. This paper overviews recent and future safety systems, and highlights the big challenges for researchers in the signal processing area.

Smartphone-Based Vehicle Telematics: A Ten-Year Anniversary

“…Other notable studies III-A [28]- [30] [31] III-B [15], [32] [33] III-C [14], [34]- [37] [38] III-D [39]- [41] [42] III-E [43]- [45] [46] III-F [47], [48] [49]-[51] IV-A [52], [53] [13], [54] IV-B [55], [56] [57], [58] IV-C [9], [10], [59]- [63] [64], [65] IV-D [66] [67] projects are discussed in Section II. Then, Section III reviews system aspects, including sensor characteristics, energy efficiency, interfaces for wireless communication, the human-machine interface (HMI) interface, and mobile cloud computing (MCC).…”

Rotational speed sensors: limitations, pre-processing and automotive applications

“…Since their introduction thirty years ago, these sensors have found many new applications such as Electronic Stability Control (ESC), traction control systems, tire pressure monitoring systems (TPMS), and odometry (navigation system support) to mention a few. See the survey [4] for details and more examples.…”

“…r denotes the right wheel speed, r r the right wheel radius, similarly for the left side, and B is the wheel base. This is a virtual yaw rate sensor, as an alternative to a gyroscope; see [4] for a derivation. Suppose the radii are the same, r r = r l .…”

Statistical signal processing approaches to fault detection

“…A positive residual gives a vote for isolating a fault in tire 2 (the pressure cannot increase), and so on. Another residual may be r = p 3 − p 4 , so two residuals would suffice to isolate all Similar multi-model based diagnosis units utilizing residual fusion are natural to introduce in vehicles, as the number of sensors for driver assistance and safety systems increases, and the sensor fusion software becomes more integrated over the different sub-systems, see Figure 14 and Gustafsson (2005).…”

“…Road prediction is in current systems solved by computer vision systems inside the camera, while vehicle tracking is an algorithm that takes input from both radar, lidar and camera Gustafsson (2005). One approach based on joint tracking and road prediction is suggested in .…”