Dynamic situation and threat assessment for collision warning systems: the euclide approach

Polychronopoulos, A.; Tsogas, Manolis; Amditis, Angelos; Scheunert, U.; Andreone, Luisa; Tango, Fabio

doi:10.1109/ivs.2004.1336458

Cited by 49 publications

(23 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Both approaches, however, do not allow a timely warning of the driver before the intervention. Other metrics are the so-called Predicted-Minimum-Distance (PMD) and the Time-ToPredicted-Minimum-Distance (TPMD) introduced in [199]. They provide a method to warn in near-collision scenarios as a situation is already considered as critical if predicted trajectories come close to each other and the minimum object distances fall below a threshold.…”

Section: Criticality Assessmentmentioning

confidence: 99%

Bayesian environment representation, prediction, and criticality assessment for driver assistance systems

Schreier

2017

At - Automatisierungstechnik

View full text Add to dashboard Cite

The dissertation approaches the questions i) how to represent the driving environment in an environment model, ii) how to obtain such a representation, and iii) how to predict the traffic scene for criticality assessment. Bayesian inference provides the common framework of all designed methods. First, Parametric Free Space (PFS) maps are introduced, which compactly represent the vehicle environment in form of relevant, drivable free space. They are obtained by a novel method for grid mapping and tracking in dynamic environments. In addition, a maneuver-based, long-term trajectory prediction and criticality assessment system is introduced and the application of all methods within the advanced driver assistance system PRORETA 3 is described.

show abstract

Section: Criticality Assessmentmentioning

confidence: 99%

Bayesian environment representation, prediction, and criticality assessment for driver assistance systems

Schreier

2017

At - Automatisierungstechnik

View full text Add to dashboard Cite

show abstract

“…In [15] and [16], the authors defined the Time to Collision (TTC) as the simple quotient between the distance to the obstacle and the relative speed of that obstacle with respect to the vehicle, provided that any action is made by the driver to avoid the impact. In [16], the concept of Predicted Minimum Distance (PMD) was defined as the minimum distance between a vehicle and a potential obstacle predicted in real time, assuming constant values in the main variables of vehicle dynamics: turn rate, longitudinal and lateral acceleration. In [16], the authors used the idea of the Required Deceleration (RD) to stop the car in the measured distance of the pedestrian position, and used a first order braking model of the system response obtained from tests.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In [16], the concept of Predicted Minimum Distance (PMD) was defined as the minimum distance between a vehicle and a potential obstacle predicted in real time, assuming constant values in the main variables of vehicle dynamics: turn rate, longitudinal and lateral acceleration. In [16], the authors used the idea of the Required Deceleration (RD) to stop the car in the measured distance of the pedestrian position, and used a first order braking model of the system response obtained from tests. Several concepts assessing the risk in terms of Time-to-X were presented in [17] and [18].…”

Section: Literature Reviewmentioning

confidence: 99%

Certainty and Critical Speed for Decision Making in Tests of Pedestrian Automatic Emergency Braking Systems

Rosado

Chien

et al. 2017

IEEE Trans. Intell. Transport. Syst.

View full text Add to dashboard Cite

show abstract

“…The main focus of this framework is the comprehension of the way a vehicle is driven, but not to predict the actions of drivers, especially under mutual influence. An approach using model based motion prediction for situation and threat assessment is presented in [9]. For that purpose, the authors introduce two parameters: Predicted Object Minimum Distance (PMD) and Predicted Time to Object Minimum Distance (TPMD), which serve as a measure for the threat of a situation, outperforming the commonly used Time to Collision parameter in their experimental results.…”

Section: Introductionmentioning

confidence: 99%

Interactive scene prediction for automotive applications

Lawitzky

Althoff

Passenberg

et al. 2013

2013 IEEE Intelligent Vehicles Symposium (IV)

View full text Add to dashboard Cite

Abstract-In this work, a framework for motion prediction of vehicles and safety assessment of traffic scenes is presented. The developed framework can be used for driver assistant systems as well as for autonomous driving applications. In order to assess the safety of the future trajectories of the vehicle, these systems require a prediction of the future motion of all traffic participants. As the traffic participants have a mutual influence on each other, the interaction of them is explicitly considered in this framework, which is inspired by an optimization problem. Taking the mutual influence of traffic participants into account, this framework differs from the existing approaches which consider the interaction only insufficiently, suffering reliability in real traffic scenes. For motion prediction, the collision probability of a vehicle performing a certain maneuver, is computed. Based on the safety evaluation and the assumption that drivers avoid collisions, the prediction is realized. Simulation scenarios and real-world results show the functionality.

show abstract

Dynamic situation and threat assessment for collision warning systems: the euclide approach

Cited by 49 publications

References 3 publications

Bayesian environment representation, prediction, and criticality assessment for driver assistance systems

Bayesian environment representation, prediction, and criticality assessment for driver assistance systems

Certainty and Critical Speed for Decision Making in Tests of Pedestrian Automatic Emergency Braking Systems

Interactive scene prediction for automotive applications

Contact Info

Product

Resources

About