Jörg Hillenbrand

Calculation of detection and false alarm probabilities in spectrum pooling systems

The innovative new strategy of spectrum pooling enables public access to spectral ranges of already licensed yet rarely used frequency bands by overlaying a secondary mobile radio system (the rental system, RS) to an existing one (the licensed system, LS). Coexistence of both systems is realized by filling the idle time-frequency gaps of the LS. A key issue in spectrum pooling is the reliable and efficient detection of those spectral ranges that are currently accessed by the LS as those ranges have to be spared from the RSs transmission power. In this letter, formulas for the calculation of the detection and false alarm probability are derived for the general case of an arbitrary measurement covariance matrix, allowing for a maximum exploitation of the proposed distributed detection approach.

A Multilevel Collision Mitigation Approach—Its Situation Assessment, Decision Making, and Performance Tradeoffs

This paper deals with the problem of decision making in the context of forward collision mitigation system design. The authors present a multilevel collision mitigation (CM) approach that allows a flexible tradeoff between potential benefit and the risk associated with driver acceptability and product liability. Due to its practical relevance, algorithms that allow for an efficient incorporation of both sensor and prediction uncertainties are further outlined. The performance tradeoffs that come along with different parameterizations are investigated by means of stochastic simulations on three dangerous traffic situations, namely 1) rear-end collisions due to an unexpected braking, 2) cutting-in vehicles, and 3) crossing traffic at intersections. The results show that an overly conservative CM system sacrifices much of its potential benefit. However, it is pointed out that the vision of accident-free driving can be achieved only through cooperative driving strategies

Situation assessment algorithm for a collision prevention assistant

In this paper, we present the concept of a collision prevention assistant, a system that we believe can significantly contribute to road safety. We propose a new situation assessment algorithm which is tailored to the action of braking and that further accounts for the nonlinearities that arise when vehicles cut out or come to a standstill. The effect of sensor uncertainty on the performance of the proposed algorithm is modelled using a Markov chain and analyzed by means of a Monte Carlo simulation on a typical traffic situation.

Efficient Decision Making for a Multi-Level Collision Mitigation System

This paper deals with the problem of decision making in the context of forward collision mitigation system design. We present a multi-level collision mitigation approach which allows a flexible tradeoff between potential benefit and the risk associated with driver acceptability and product liability. Due to its practical relevance, we further outline algorithms that allow for an efficient incorporation of both sensor and prediction uncertainty. The control behavior of the system is illustrated on a simulated example of a cutting-in vehicle

A Study on the Performance of Uncooperative Collision Mitigation Systems at Intersection-like Traffic Situations

Collision mitigation systems are important driver assistance systems which promise to improve traffic safety in terms of reducing the number of road accidents and accident severity. Increasing research effort has been devoted to these systems within the past few years and first systems have recently been introduced into the market. However, these systems clearly focus on avoiding or mitigating rear-end collisions. This is mainly due to the fact that the use case of cross-traffic requires advanced environmental perception and decision making. In this paper, we investigate the performance of a practical, uncooperative collision mitigation system capable of handling cross-traffic on a variety of intersection-like situations where two vehicles cross each other at different velocities and distances by means of stochastic dynamic simulations. Although our collision mitigation system does not employ cooperative control mechanisms, we also consider the interesting case of both vehicles being equipped with the system. The performance is analyzed under the assumption of perfect sensor information as well as using a realistic sensor model