Arbitration for balancing control between the driver and ADAS systems in an automated vehicle: Survey and approach

Abstract

Automated functions for real scenarios have been increasing in last years in the automotive industry. Many research contributions have been done in this field. However, other problems have come to the drivers: When should they (the drivers or the new automated systems) be able to take control of the vehicle? This question has not a simple answer; it depends on different conditions, such as: the environment, driver condition, vehicle capabilities, fault tolerance, among others. For this reason, in this work we will analyze the acceptability to the ADAS functions available in the market, and its relation with the different control actions. In this paper a survey on arbitration and control solutions in ADAS is presented. It will allow to create the basis for future development of a generic ADAS control (the lateral and longitudinal behavior), based on the integration of the application request, the driver behavior and driving conditions in the framework of the DESERVE project (DEvelopment platform for Safe and Efficient dRiVE 1 , a ARTEMIS project 2012-2105). The main aim of this work is to allow the development of a new generation of ADAS solutions where the control could be effectively shared between the vehicle and the driver. Different solutions of shared control have been analyzed. A first approach is proposed, based on the presented solutions.

A Review of Shared Control for Automated Vehicles: Theory and Applications

“…Arbitration in the context of cooperative vehicle guidance is a time-critical-structured negotiation between the human and the machine that achieves, in a timely fashion, a clear and optimal goal for the overall system [37]. In shared control of vehicles, an arbitration system is necessary to harmonize the decision and control actions of the driver and automation [45].…”

Development and design of a platform for arbitration and sharing control applications

“…Every decision making should be adapted to each scenario defined in the framework of DESERVE project. Based on these previous works described in [10], a two levels fuzzy approach is presented for the arbitration (IWI manager) and vehicle sharing (VMC) modules. The sentences used are of the following form: IF... THEN..., for instance:…”

The Traffic Scene Understanding and Prediction Based on Image Captioning

“…Up to the present, most attention has been paid to the researches on single or multiple target detection. However, there are various targets likely not belonging to the above ones in reality, and the ADAS will omit the new targets to put the driver in danger [58] [59]. Second, the current ADASs could not supply the driver intelligent driving suggestion and strategy of traffic scene ahead yet [55]- [57].…”