Papers by Andreas Eidehall
SAE Technical Paper Series, 2016
2006 IEEE Intelligent Transportation Systems Conference, 2006
16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013), 2013
2006 IEEE Intelligent Transportation Systems Conference, 2006
Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005., 2005
This paper presents a new automotive safety function called emergency lane assist (ELA). ELA comb... more This paper presents a new automotive safety function called emergency lane assist (ELA). ELA combines conventional lane guidance systems with a threat assessment module that tries to activate and deactivate the lane guidance interventions according to the actual risk level of lane departure. The goal is to only prevent dangerous lane departure maneuvers. Such a threat assessment algorithm is dependent on detailed information about the vehicle surroundings, i.e., positions and motion of other vehicles, but also information about road and lane geometry is used and the performance is improved by introducing a nonlinear model which uses a road aligned, curved coordinate system. The ELA decision algorithm has been tested in a demonstrator and it successfully distinguishes between dangerous and safe lane changes on a small set of test scenarios. It is also able to take control of the vehicle and put it in a safe position in the original lane.
IEEE Proceedings. Intelligent Vehicles Symposium, 2005., 2005
This paper deals with the problem of estimating the vehicle surroundings (lane geometry and the p... more This paper deals with the problem of estimating the vehicle surroundings (lane geometry and the position of other vehicles), which is needed for intelligent automotive systems, such as adaptive cruise control, collision avoidance and lane guidance. This results in a nonlinear estimation problem. For automotive tracking systems, these problems are traditionally handled using the extended Kalman filter. In this paper we describe the application of the marginalized particle filter to this problem. Studies using both synthetic and authentic data shows that the marginalized particle filter can in fact give better performance than the extended Kalman filter. However, the computational load is higher.
IEEE Intelligent Vehicles Symposium, 2004, 2004
Detection and tracking of other vehicles and lane geometry will be required for many future intel... more Detection and tracking of other vehicles and lane geometry will be required for many future intelligent driver assistance systems. By integrating the estimation of these two features into a single filter, a more optimal utilization of the available information can be achieved. For example, it is possible to improve the lane curvature estimate during bad visibility by studying the motion of other vehicles. This paper derives and evaluates various approximations that are needed in order to deal with the non-linearities that are introduced by such an approach.
2006 IEEE Intelligent Vehicles Symposium, 2006
An essential part of future collision avoidance systems is to be able to predict road curvature. ... more An essential part of future collision avoidance systems is to be able to predict road curvature. This can be based on vision data, but the lateral movement of leading vehicles can also be used to support road geometry estimation. This paper presents a method for detecting lane departures, including lane changes, of leading vehicles. This information is used to adapt the dynamic models used in the estimation algorithm in order to accommodate for the fact that a lane departure is in progress. The goal is to improve the accuracy of the road geometry estimates, which is affected by the motion of leading vehicles. The significantly improved performance is demonstrated using sensor data from authentic traffic environments.
2006 IEEE Intelligent Vehicles Symposium, 2006
In many applications of tracking and sensing systems, reference data for tuning and verification ... more In many applications of tracking and sensing systems, reference data for tuning and verification of system performance is unavailable. In this article the problem of automotive on-line road shape estimation is discussed and a method for obtaining reference data for this application is presented. The reference data is based on a least squares curve which is fitted geometrically to the lane boundaries. It does not require any extra sensors or other hardware. It is also shown that the accuracy of the estimate is high enough to be used as a reference in most applications.
2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC), 2011
Auto-brake systems have been on the market for a few years, but in order to continue improving th... more Auto-brake systems have been on the market for a few years, but in order to continue improving their performance, multi-target threat assessment is a key component. The goal is to early be able to say that a collision can no longer be avoided by a steering maneuver, and thus braking can be started earlier. This is done by looking at all objects in the road scene, including other vehicles and barriers, and then looking for escape paths. The paper presents a computationally efficient way of determining whether an escape path can be found in a scenario with generally positioned objects, given the limited dynamics of the vehicle.
2007 IEEE Intelligent Vehicles Symposium, 2007
ABSTRACT This paper presents improvements and extensions of a previously presented threat assessm... more ABSTRACT This paper presents improvements and extensions of a previously presented threat assessment algorithm. The algorithm uses Monte Carlo simulation to find threats in a road scene. It is shown that by using a wider sample distribution and only apply the most likely samples from the Monte Carlo simulation for the threat assessment, improved results are obtained. By using this method more realistic paths was chosen by the simulated vehicles and more complex traffic situations will be adequately handled. An improvement of the dynamic model is also suggested, which improves the realism of the Monte Carlo simulations. Using the new dynamic model less false positive and more valid threats are detected.
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Papers by Andreas Eidehall