And of course I would like to express my gratitude to the members of the jury who participated in my PhD. In particular, I would like to thank the efforts of the referees of my dissertation, Sylvie Le Hégarat and Olivier Aycard.
Résumé
Exploitation des données cartographiques pour la perception de véhi- cules intelligents
Streszczenie
Wykorzystanie map w systemach percepcji pojazdów inteligentnych
Contents
Acronyms
Notation
Author’s publications
Preliminaries
Chapter
General introduction
Context
One of the most impressive recent examples has been the Bertha Benz memorial drive (Ziegler et al.). Even with the ongoing progress, one of the biggest concerns in intelligent vehicles is still the complexity of the environment.
Base components of an autonomous driving system
In general, the next module that builds on the localization and perception subsystems is the one responsible for trajectory planning. Compliance with traffic rules is another example where the system has to decide on a driving strategy.
Goal and scope of the thesis
Prior knowledge from geodata is also used to control scene dynamics. The aim and scope of the thesis can be combined at different times, i.e. in different positions.
Contributions
Dissertation organisation
In addition to the open source PACPUS platform, this thesis resulted in the creation of a Matlab toolbox and an open source C++ library for data fusion using belief function theory¹.
Research on maps and uncertain data fusion for autonomous vehicles
Using digital maps and city models for intelligent vehicles
We address the domains of localization and perception, from time to time, and mention navigation, in the following sections.
Digital cartographic maps
In this way only an approximate model is obtained, as the exact shape of the building cannot be determined. The final phase, the global phase, integrates intermediate results constructed at different positions of the robot into a single global map.
Maps for localisation
Before the reconstruction is done, the position of the receiver must be assessed. One of the most important steps of the algorithm is the detection of road boundaries.
Automatic perception enhanced by map data
One of the most important steps of the algorithm is the detection of road edges. however, this step is highly sensor-dependent and less interesting for the discussion here. Providing an accurate description of the environment and understanding the scene in which the vehicle is evolving was the object (Stiller and Ziegler.
Data fusion using belief functions theory
Introduction
In this chapter we present a theoretical tool, called belief function theory (BFT), that is routinely used for aggregating uncertain information. Since in this thesis the theory of belief functions has been chosen as the main tool for information fusion, we will provide a detailed description of this formalism and its tools.
Addressing data fusion problem
Last part of the information fusion, the decision making translates the result of the combination into a final decision. In an object perception system, the inaccuracy is, for example, an error in the estimated position of the object.
Probability theory
Moreover, probability theory is well suited to cases where there are large amounts of data and statistical reasoning is fully justified. Disadvantages A major drawback of probability theory is the way it models ignorance.
Possibility theory
Advantages As probability theory is an established tool, well known in various societies, there are many theoretical and practical tools available. Among the practical reasons for the predominance of probability theory, one can mention its simplicity, efficiency and the fact that it is computationally light (cf. further section).
Belief functions theory
Avacuous bba m is a mass function corresponding to the state of complete ignorance about the variable R. Acategorical bba mis a mass function corresponding to the state of complete certainty about the state of the variable R.
Rationale for using belief functions
Furthermore, for the last theory, it has been shown that a necessity measure N can be expressed by belief functions (Shafer). Unfortunately, like almost every theoretical tool, the theory of belief functions should also be avoided in some cases.
Remanence in occupancy grids
Environment modelling with evidential grids
Object-based approaches, which consist of detecting, recognizing and tracking objects in the scene, although useful and semantically rich, are difficult to handle, except in the case of familiar environments. In the following, we will present original probabilistic covering grids as well as their multidimensional improvements.
Occupancy grids
Later in this chapter, an evidentiary version of occupancy grids, called 'perception grids', adapted for the theory of belief functions, will be introduced. One of the problems with dealing with occupancy schedules is that their large memory footprint increases rapidly as scheduling resolutions increase.
Evidential occupancy grids and perception grids
Next, both networks are combined to integrate the information into the new SG. Unlike the world-centered grids, in the ego-centered case, it is the local dynamic map that is moved to the vehicle coordinate system.
Perception grids for dynamic perception
Such clearance can be thought of as the drivable space that is reduced to take into account the geometric model of the vehicle. In our approach we limited the use of this data to geometric information about the surface of the road and buildings.
Sensor models
On the surface of the road R, it is possible to have free drivable space, as well as prohibited and moving objects M.
Sensor model for a lidar
In general, these effects can introduce uncertainty about the existence and position of the obstacle. Impact function On the other hand, the impact function stores information about the impact position and the space occupied by the corresponding obstacle.
Virtual sensor model for maps
Without assuming such a claim, we would admit that, for example, a building can stand in the middle of a road, which is absurd. In this model, imprecision and inaccuracy are not taken into account explicitly, as can be seen from the example in Figure.b.
Conclusion
We solved this problem by using a homogeneous representation, evidence grid, capable of modeling extremely diverse sensor data. We have also shown that such a representation is able to model other types of data, such as maps, and successfully convey geometric and contextual information.
Incorporation of prior knowledge into perception system
Figure . – Part of the perception system where the information fusion takes place independently of the exact sensor types. Bilinear transformation can interpolate values, so in the transformed cell masses are set to average values of the neighborhood of the polar cell.
Temporal fusion
To take advantage of the dynamic characteristics of the scene, we propose an analysis of the induced conflict masses. In the proposed fusion scheme, ∅F O denotes the conflict that occurs when a free cell in PerceptionGridis merged with an occupied cell in SensorGrid.
Illustrative examples
Temporal fusion behaviour analysis
Due to a non-zero time lag between these two instants, we have to compensate for the possible changes in the dynamic environment. We have therefore proposed a family of temporal discount operators, which are described in the next chapter.
Management of ageing information
In the case of the presented perception system, the need to deal with the information age arises, for example, when predicting the future state of the world based on our judgment on outdated evidence. In this situation, the state of the environment at the time of the previous sensor scan is represented by an observation grid.
Temporal discounting
In general, the more outdated information is, the more it should be discounted. In other words, the mass attributed to a piece of information is twice the initial mass after half-life1/2 =τ ·ln2.
Existing methods
We argue that the discounting result should be independent of the order of operations. In our case, the role of contextual discounting is to check the remanence of different classes.
Conservative, optimistic and proportional discounting
One note that the most discounted mass is m(∅), which is affected by all discount rates.
Properties
For all the proposed schemes, the result of two discounting operations on setsΘ1,Θ2and discount rate vectorsα1,α2 done one after the other is equal to a single discounting operation on combined discount rate vectorα =concatenated(α1, α2).
Examples
Namely, the discount factor is set to the same value but attributed to the set {a}, and the resulting mass function is identical.
Case study: temporal discounting using proposed methods
Case Study: Time Discounting Using Proposed Methods Simplified Calculation Assume that m is a normal mass function, ie. In addition to the already mentioned applications, the authors consider the use of time discounting in
System & setup
Map-aided perception system architecture
Figure . – Simplified view of components of the Pacpus framework used to implement the perception system.
Dataset
It is a four-scan sensor that displays a D point cloud of the environment with each scan. Figure . – Angular resolution Alaska XT as a function of the measuring angle and the frequency.
Defining grid parameters
Remanence characteristics and discount factors The discount factors describe the persistence of the information from a given class, or in other words the rate at which the information becomes obsolete. To calculate the values δ and γ, let us consider an object of length L moving at a speed Vmin, which is the smallest speed one would be able to detect.
Results
Contribution of map data
Figure . shows the effect of temporal descent, which is particularly evident in the free space behind the vehicle. To better understand the information contained in the PerceptionGrid, we show, in Figure ., the pignistic probabilities at a grid level of several classes of interest.
Obstacle detection
Other colors result from the pignistic probabilities (and their associated colors) being mixed together. Similarly, cars parked on the left side of the road are detected as stopped (blue cells at the bottom right of the grids).
Free space detection and characterisation
However, in this chapter, we do not present any parameter studies and all parameters have fixed values. We judge that this can be justified by the fact that extensive manual tuning was performed during the experiments.
Conclusion
Conclusion & perspectives
An important part of the fusion rule is about using the previous result to predict the current state. An intermediate solution, the proportional operator, discounts supersets in proportion to the cardinality of the subset covered by the discount factor.
Perspectives
In addition, an important modification of the tentacle approach would be to make full use of the rich information encoded in perceptual grids. Emergency mode Another possibility to improve the trajectory planning system is to add an emergency driving mode.
Appendices
Appendix A
Proofs
A. Discounting
Appendix B
Implementation notes
B. Soware analysis
Code MUST be documented in a computer-readable format, compliant with the Doxygen² automatic documentation generation tool. Maintenance tasks such as isolating and correcting defects, change or new requirements SHOULD be easy to achieve.
B. Algorithms
B. ird-party libraries
Bibliography
Building maps with mobile robots in dynamic environments”. IEEE International Conference on Robotics and Automation (ICRA). Proceedings of the IROS Workshop: Planning, Perception and Navigation for Intelligent Vehicles (PP-NIV)” (). IEEE International Conference on Intelligent Robot Systems (IROS).
Index
