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Technical Paper

Automotive ADAS Camera System Configuration Using Multi-Core Microcontroller

2015-03-10
2015-01-0023
It has become an important trend to implement safety-related requirements in the road vehicles. Recent studies have shown that accidents, which occurred when drivers are not focused due to fatigue or distractions, can be predicted in advance when using safety features. Advanced Driver Assistance Systems (ADAS) are used to prevent this kind of situation. Currently, many major tiers are using a DSP chip for ADAS applications. This paper suggests the migration from a DSP configuration to a Microcontroller configuration for ADAS application, for example, using a 32bit Multi-core Microcontroller. In this paper, the following topics will be discussed. Firstly, this paper proposes and describes the system block diagram for ADAS configuration followed by the requirements of the ADAS system. Secondly, the paper discusses the current solutions using a DSP. Thirdly, the paper presents a system that is migrated to a Multi-core microcontroller.
Technical Paper

Intention Aware Motion Planning with Model Predictive Control in Highway Merge Scenario

2019-03-25
2019-01-1402
Human drivers navigate by continuously predicting the intent of road users and interacting with them. For safe autonomous driving, research about predicting future trajectory of vehicles and motion planning based on these predictions has drawn attention in recent years. Most of these studies, however, did not take into account driver’s intentions or any interdependence with other vehicles. In order to drive safely in real complex driving situations, it is essential to plan a path based on other driver’s intentions and simultaneously to estimate the intentions of other road user with different characteristics as human drivers do. We aim to tackle the above challenges on highway merge scenario where the intention of other road users should be understood. In this study, we propose an intention aware motion planning method using finite state machine and model predictive control without any vehicle-to-vehicle (V2V) or vehicle-to-infrastructure (V2I) communications.
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