Project

Variational Bayesian Expectation Maximization for Radar Map Estimation

For self-localization, a detailed and reliable map of the environment can be used to relate sensor data to static features with known locations. This paper presents a method for construction of detailed radar maps that describe the expected intensity of

Poisson Multi-Bernoulli Mapping Using Gibbs Sampling

This paper addresses the mapping problem. Using a conjugate prior form, we derive the exact theoretical batch multiobject posterior density of the map given a set of measurements. The landmarks in the map are modeled as extended objects, and the

Considerations About Continuous Experimentation for Resource-Constrained Platforms in Self-driving Vehicles

Autonomous vehicles are slowly becoming reality thanks to the efforts of many academic and industrial organizations. Due to the complexity of the software powering these systems and the dynamicity of the development processes, an architectural solution

Adaptive Message Restructuring Using Model-Driven Engineering

Message exchange between distributed software components in cyber-physical systems is a frequent and resource-demanding activity. Existing data description languages simply map user-specified messages literally to the system implementation creating the

Continuous Experimentation on Cyber-Physical Systems: Challenges and Opportunities

Establishing and mastering continuous experimentation as an instrument in the portfolio of software product managers is of growing importance resulting in continuous renewal of products for continuous user satisfaction. Product managers for purely software

Design Criteria to Architect Continuous Experimentation for Self-Driving Vehicles

The software powering today's vehicles surpasses mechatronics as the dominating engineering challenge due to its fast evolving and innovative nature. In addition, the software and system architecture for upcoming vehicles with automated driving

Primal Decomposition of the Optimal Coordination of Vehicles at Traffic Intersections

In this paper we address the problem of coordinating automated vehicles at intersections, which we state as a constrained finite horizon optimal control problem. We present and study the properties of a primal decomposition of the optimal control problem

Multi-Bernoulli filtering for initially unresolved targets in clutter

Multiple target tracking (MTT) is a challenging task that aims to estimate the number of targets and their states in the presence of process noise, measurement noise and data association uncertainty. This paper considers a special MTT problem characterized

Multiple sensor Bayesian extended target tracking fusion approaches using random matrices

Gamma Gaussian inverse-Wishart Poisson multi-Bernoulli Filter for Extended Target Tracking

This paper presents a gamma-Gaussian-inverse Wishart (GGIW) implementation of a Poisson multi-Bernoulli mixture (PMBM) filter for multiple extended target tracking. The GGIW density is the single extended target conjugate prior assuming a Poisson

Metric for performance evaluation of elliptic extended object tracking methods

The objective of extended object tracking is to simultaneously track a target object and estimate its shape. As a consequence, it becomes necessary to incorporate both location and shape errors in the performance assessment of extended object tracking

Converted Measurements Bayesian Extended Target Tracking Applied to X-band Marine Radar Data

X-band marine radar systems are flexible and lowcost tools for monitoring multiple targets in a surveillance area. They can provide high resolution measurements both in space and time. Such features offer the opportunity to get accurate information not

Multistatic Bayesian Extended Target Tracking

To track an extended target presents challenges because the hypothesis of "one target means one detection" is not valid. Several approaches to extended target tracking (ETT) have been found promising, and in particular those involving random matrices have

Vehicle-to-Vehicle Communications with Urban Intersection Path Loss Models

Vehicle-to-vehicle (V2V) communication can improve road safety and traffic efficiency, particularly around critical areas such as intersections. We analytically derive V2V success probability near an urban intersection, based on empirically supported line

Coordination of Cooperative Autonomous Vehicles: Toward safer and more efficient road transportation

While intelligent transportation systems come in many shapes and sizes, arguably the most transformational realization will be the autonomous vehicle. As such vehicles become commercially available in the coming years, first on dedicated roads and under