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| Lučanin, Vojkan | Belgrade |
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Herrmann, Martin
in Cooperation with on an Cooperation-Score of 37%
Topics
- autonomous vehicle
- perception
- driving
- forecasting
- safety
- infrastructure
- comfort
- passenger
- optimisation
- behavior
- decision making
- vehicle occupant
- trajectory
- autonomous driving
- experiment
- intersection
- sensor
- social science
- engineering
- sampling
- uncertainty
- detector
- passenger comfort
- automated guided vehicle system
- estimate
- traveller
- acceleration
- velocity
- machinery
- learning
- neural network
- data file
- workshop
- highway
- deep learning
- yaw
- estimating
- telecommunication
- connected vehicle
- standardisation
- roadside
- offside
- data
- computer science
- automobile
- simulation
- filter
- contrast
- mining
- data mining
- urban area
- electrical engineering
- interface
- automobile travel
- automation
- robotics
- automobile driving
- signal processing
- industry
- algorithm
- intelligent vehicle
- computer vision
- vision
- intelligence
- artificial intelligence
- calibration
- stereoscopic camera
- modeling
- costs
- distributed processing
- driver
- vehicle
- driver support system
- radar
- theory
- highway traffic
- filtration
- traffic engineering
- data fusion
- radar tracking
- evolution
- cruise control
- speed control
- show 53 more
Publications (10/10 displayed)
- 2022Motion Planning for Connected Automated Vehicles at Occluded Intersections With Infrastructure Sensors
- 2021Multiple trajectory prediction with deep temporal and spatial convolutional neural networks
- 2021Safety-relevant Test Scenarios for Automated Driving Functions
- 2021An extension proposal for the collective perception service to avoid transformation errors and Include object predictions
- 2020LMB filter based tracking allowing for multiple hypotheses in object reference point association
- 2019LACI: Low-effort Automatic Calibration of Infrastructure Sensorscitations
- 2019Environment Modeling Based on Generic Infrastructure Sensor Interfaces Using a Centralized Labeled-Multi-Bernoulli Filter *citations
- 2019Efficient Sensor Development Using Raw Signal Interfacescitations
- 2019Environment modeling based on generic infrastructure sensor interfaces using a centralized labeled-multi-bernoulli filter
- 2017Scenario-based approach for developing ADAS and automated driving functionscitations
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article
Motion Planning for Connected Automated Vehicles at Occluded Intersections With Infrastructure Sensors
Abstract
Motion planning at urban intersections that accounts for the situation context, handles occlusions, and deals with measurement and prediction uncertainty is a major challenge on the way to urban automated driving. In this work, we address this challenge with a sampling-based optimization approach. For this, we formulate an optimal control problem that optimizes for low risk and high passenger comfort. The risk is calculated on the basis of the perception information and the respective uncertainty using a risk model. The risk model combines set-based methods and probabilistic approaches. Thus, the approach provides safety guarantees in a probabilistic sense, while for a vanishing risk, the formal safety guarantees of the set-based methods are inherited. By exploring all available behavior options, our approach solves decision making and longitudinal trajectory planning in one step. The available behavior options are provided by a formal representation of the situation context, which is also used to reduce calculation efforts. Occlusions are resolved using the external perception of infrastructure-mounted sensors. Yet, instead of merging external and ego perception with track-to-track fusion, the information is used in parallel. The motion planning scheme is validated through real-world experiments.
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