Driving strategy selection for cooperative vehicles using maneuver templates

Manzinger, Stefanie; Leibold, Marion; Althoff, Matthias

doi:10.1109/ivs.2017.7995791

Cited by 19 publications

(8 citation statements)

References 25 publications

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“…There are basically two main options: a) One provides single trajectories of other traffic participants or b) provides a set of possible trajectories. In the first case one creates a scenario in which the motion planner has to find a safe solution when the other trajectory is known, which is typically the case in collaborative driving [38], [39]. In the second case, the future movement of other traffic participants is unknown, which is typically the case for noncommunicating traffic participants, such as e.g., bicyclists.…”

Section: A Predictions Of Other Traffic Participantsmentioning

confidence: 99%

Automatic Generation of Safety-Critical Test Scenarios for Collision Avoidance of Road Vehicles

Althoff

Lutz

2018

2018 IEEE Intelligent Vehicles Symposium (IV)

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105

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It is apparent that one cannot rely solely on physical test drives for ensuring the correct functionality of autonomous vehicles. Since physical test drives are costly and time consuming, it is advantageous to accompany them with computer simulations. However, since most traffic scenarios are not challenging, even simulations are often too time consuming. To address this issue, we present an approach that creates automatically critical driving situations, i.e., situations with a small solution space for avoiding a collision. Our approach combines reachability analysis for determining the size of the solution space with optimization techniques to shrink it. The solution space is reduced by shifting the initial states of traffic participants, demanding an immediate and correct action of the vehicle under test. We demonstrate our approach by automatically increasing the criticality of several initially uncritical situations recorded from real traffic.

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Section: A Predictions Of Other Traffic Participantsmentioning

confidence: 99%

Automatic Generation of Safety-Critical Test Scenarios for Collision Avoidance of Road Vehicles

Althoff

Lutz

2018

2018 IEEE Intelligent Vehicles Symposium (IV)

Self Cite

105

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“…On the one hand, authors in [20] presented an auction-based cooperative control for autonomous vehicles; on the other hand, authors in [21] proposed an approach to enhance common motion planning algorithms; this proposal allows cooperation with human-driven vehicles. Additionally, a novel concept is presented, based on a centralized strategy, using maneuver templates, which are formalized collaborative maneuvers, to select cooperative driving strategies [22]. All this work proves the importance of collaboration and communication among vehicles to allow a safe and efficient deployment of autonomous vehicles really in driving scenarios.…”

Section: Related Workmentioning

confidence: 86%

Hybrid Optimization-Based Approach for Multiple Intelligent Vehicles Requests Allocation

Hussein

Marín-Plaza

García

et al. 2018

Journal of Advanced Transportation

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Self-driving cars are attracting significant attention during the last few years, which makes the technology advances jump fast and reach a point of having a number of automated vehicles on the roads. Therefore, the necessity of cooperative driving for these automated vehicles is exponentially increasing. One of the main issues in the cooperative driving world is the Multirobot Task Allocation (MRTA) problem. This paper addresses the MRTA problem, specifically for the problem of vehicles and requests allocation. The objective is to introduce a hybrid optimization-based approach to solve the problem of multiple intelligent vehicles requests allocation as an instance of MRTA problem, to find not only a feasible solution, but also an optimized one as per the objective function. Several test scenarios were implemented in order to evaluate the efficiency of the proposed approach. These scenarios are based on well-known benchmarks; thus a comparative study is conducted between the obtained results and the suboptimal results. The analysis of the experimental results shows that the proposed approach was successful in handling various scenarios, especially with the increasing number of vehicles and requests, which displays the proposed approach efficiency and performance.

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“…The allocation of a subset of the resource to a vehicle shall be denoted a reservation. Reservations of space as a function of time could be described in many different ways: Polygons in earth fixed coordinates and time, polygons in lane or road relative, non-linear coordinates, earth fixed or road relative vehicle trajectories [12], buffer spaces attached to the position of certain vehicles [19], positions in a platoon [13], maneuver templates [20] and many more. Previously, we applied lanebased reservations [14], which identify the reserved area by a lane selecting start coordinate (x 0 , y 0 ), the extent along the lane l, an activation time interval [t 0 , t 1 ] and a description of movement along the lane, here based on a constant velocity v 0 .…”

Section: A Encoding Of a Reservationmentioning

confidence: 99%

Negotiation of Cooperative Maneuvers for Automated Vehicles: Experimental Results

Hes

Lattarulo

Pérez

et al. 2019

2019 IEEE Intelligent Transportation Systems Conference (ITSC)

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When the number of automated vehicles deployed in public traffic reaches a significant level, their form of interaction with other automated vehicles, human controlled vehicles and non-motorized participants will impact traffic overall safety and efficiency. While many studies have approached impact analysis on the side of efficiency and via simulation, we here elaborate on practically applicable methods for safe cooperation of automated vehicles from the perspective of life-size experimental platforms. The EU project UnCoVerCPS investigates on-line verification based safety analysis and control of cyberphysical system, applying the developed techniques to cooperation of automated vehicles. In a previous publication, a message set for negotiation of such a cooperation has been proposed, (STRP), which is compatible with the investigated verification approach. This publication follows up by providing results and analysis of test drives with two cooperating, automated vehicles with differing software and hardware architectures. The STRP messages are employed to negotiate a cooperative lane change via Car-to-Car radio in an urban scenario with non-trivial road-geometry. The applicability of the distributed cooperation scheme to real-world conditions is demonstrated.

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Driving strategy selection for cooperative vehicles using maneuver templates

Cited by 19 publications

References 25 publications

Automatic Generation of Safety-Critical Test Scenarios for Collision Avoidance of Road Vehicles

Automatic Generation of Safety-Critical Test Scenarios for Collision Avoidance of Road Vehicles

Hybrid Optimization-Based Approach for Multiple Intelligent Vehicles Requests Allocation

Negotiation of Cooperative Maneuvers for Automated Vehicles: Experimental Results

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