| 1. |
- Chandru, Rajashekar, 1991, et al.
(författare)
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Safe autonomous lane changes in dense traffic
- 2017
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Ingår i: IEEE International Conference on Intelligent Transportation Systems-ITSC. - 2153-0009. - 9781538615263 ; 2018-March
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Konferensbidrag (refereegranskat)abstract
- Lane change manoeuvres are complex driving manoeuvres to automate since the vehicle has to anticipate and adapt to intentions of several surrounding vehicles. Selecting a suitable gap to move/merge into the adjacent lane and performing the lane change can be challenging, especially in dense traffic. Existing gap selection methods tend to be either cautious or opportunistic, both of which directly affect the overall availability and safety of the autonomous feature. In this paper we present a method which enables the autonomous vehicles to increase the availability of lane change manoeuvres by reducing the required margins to ensure a safe manoeuvre. The required safety margins are first calculated by making use of the steering and braking capability of the vehicle. It is then shown that this method can be used to perform autonomous lane changes in dense traffic situations with small inter-vehicle gaps. The proposed solution is evaluated by using Model Predictive Control (MPC) to plan and execute the complete motion trajectory.
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| 2. |
- León Cano, Jorge Alejandro, et al.
(författare)
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Automatic incident detection and classification at intersections
- 2009
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Ingår i: 21st International Conference on Enhanced Safety of Vehicles, ESV. ; , s. Paper 09-0234
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Collisions at intersections are common and their consequences are often severe. This paper addresses the need for information on accident causation; a knowledge that can be used to obtain more effective countermeasures. A novel method that can be applied to data recorded in a groundbased observation system or similar is proposedfor classifying vehicle interactions into a set ofpredefined traffic scenarios. The classification isbased on possible combinations of trajectories of two interacting vehicles that have passed through an intersection. Additionally, the authors present an incident detection algorithm that uses the classified vehicle interactions. This algorithm constitutes the core of a video-based automatic incident detection at intersections (AIDI) system. The performance of the AIDI system was successfullyverified both in a driving simulator and in real traffic conditions.
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| 3. |
- Brännström, Mattias, 1980, et al.
(författare)
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A Probabilistic Framework for Decision-Making in Collision Avoidance Systems
- 2013
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Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; 14:2, s. 637-648
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Tidskriftsartikel (refereegranskat)abstract
- This paper is concerned with the problem of decision-making in systems that assist drivers in avoiding collisions. An important aspect of these systems is not only assisting the driver when needed but also not disturbing the driver with unnecessary interventions. Aimed at improving both of these properties, a probabilistic framework is presented for jointly evaluating the driver acceptance of an intervention and the necessity thereof to automatically avoid a collision. The intervention acceptance is modeled as high if it estimated that the driver judges the situation as critical, based on the driver's observations and predictions of the traffic situation. One advantage with the proposed framework is that interventions can be initiated at an earlier stage when the estimated driver acceptance is high. Using a simplified driver model, the framework is applied to a few different types of collision scenarios. The results show that the framework has appealing properties, both with respect to increasing the system benefit and to decreasing the risk of unnecessary interventions.
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| 4. |
- Brännström, Mattias, 1980, et al.
(författare)
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A Real-time Implementation of an Intersection Collision Avoidance System
- 2011
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Ingår i: IFAC Proceedings Volumes (IFAC-PapersOnline). - 2405-8963. - 9783902661937 ; 18:PART 1, s. 9794-9798
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Konferensbidrag (refereegranskat)abstract
- This paper presents a real-time implementation of a collision avoidance (CA) system that uses autonomous braking and model predictive control to assist drivers in avoiding collisions with other road users. To the authors knowledge, this is the first CA system that targets general vehicle collisions that has been implemented in a car. The system is based on a recently published decision-making algorithm which is described in [1]. To validate the CA system in various collision scenarios without endangering the driver of the vehicle, a novel test platform has been developed. The test platform consist of a soft crashable obstacle which is movable in speeds up to 70 km/h and safe to collide with in any angle in relative speeds up to 100 km/h. In the current implementation, estimates of the motion of the obstacle are obtained through a reference sensor fusion system that is based on a combination of in-vehicle sensors and a differential global positioning system. Results from both intersection and rear-end collision situations are presented. The results show that the proposed CA system can be implemented in a real-time environment and that the predictive brake control algorithm accurately accounts for delays and ramp-up times in the brake system of the vehicle.
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| 5. |
- Brännström, Mattias, 1980, et al.
(författare)
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A situation and threat assessment algorithm for a rear-end collision avoidance system
- 2008
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Ingår i: Intelligent Vehicles Symposium, 2008 IEEE. - 1931-0587. - 9781424425686 ; , s. 102-107
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Konferensbidrag (refereegranskat)abstract
- Rear-end collisions are common accident scenarios and a frequent cause of these accidents is driver distraction. This paper presents a situation assessment (SA) algorithm that estimates driver distraction by continuously assessing the steering actions of the driver. A collision avoidance (CA) system is proposed, which combines the SA with a threat assessment (TA) algorithm that estimates the effort needed to avoid a collision. It is shown that the SA algorithm proposed enables the CA system to initiate earlier brake interventions when the driver is assessed as being distracted, without significantly increasing the risk of false interventions in real traffic. The CA system has been evaluated in both collision situations on a test track and during 200 driving hours in real traffic conditions.
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| 6. |
- Brännström, Mattias, 1980
(författare)
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Decision-Making in Automotive Collision Avoidance Systems
- 2011
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis is concerned with decision-making in systems that can detect hazardous traffic situations and assist drivers in avoiding collisions by using automatic braking or steering. The aim with these systems is to reduce the number of accidents and their consequences without disturbing the driver with unnecessary interventions during normal traffic conditions.The main contribution of this thesis consists of algorithms for evaluating if the driver needs assistance to avoid colliding with a single road user in any traffic situation. The proposed algorithms, which are shown to work well in a real-time environment, are evaluated using data from both real traffic conditions, simulations and collision situations on a test track. Moreover, a probabilistic decision-making framework is presented for jointly evaluating the driver acceptance of an intervention and the necessity thereof to automatically avoid an accident. The framework enables earlier interventions in critical traffic situations, thereby increasing the benefit of the system. Additionally, a method is proposed for estimating driver distraction by observing the driver's steering behavior prior to near-crash situations. It is shown that earlier interventions can be triggered when the driver is assessed as being distracted without significantly increasing the risk of unnecessary interventions. Decision-making on when to assist the driver by steering and when to assist by braking is discussed and an algorithm for finding suitable evasive steering maneuvers to pass between multiple moving objects is presented.
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| 7. |
- Brännström, Mattias, 1980, et al.
(författare)
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Decision-making on when to brake and when to steer to avoid a collision
- 2014
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Ingår i: International Journal of Vehicle Safety. - 1479-3105 .- 1479-3113. ; 7:1, s. 87-106
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Tidskriftsartikel (refereegranskat)abstract
- By either autonomously steering or braking, accidents can be avoided or mitigated by a number of active safety functions which are available on the market today. However, these functions are often tailored for specific accident types and for each type either braking or steering may be possible. This contribution considers an algorithm for threat assessment which can be used in general traffic situations not only to decide if an intervention is necessary to avoid an accident, but also to select which type of intervention, steering or braking. The algorithm is evaluated on four accident types: rear-end accidents showing how the appropriate intervention depends on the lateral offset between host vehicle and target vehicle; single-target straight crossing path collisions where the decision depends on the vehicles' speed; collision scenarios with oncoming vehicles; and finally situations where multiple obstacles need to be considered.
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| 8. |
- Brännström, Mattias, 1980, et al.
(författare)
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Decision Making on when to Brake and when to Steer to Avoid a Collision
- 2011
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Ingår i: First International Symposium on Future Active Safety Technology toward zero-traffic-accident, September 5-9, 2011, Tokyo, JAPAN.
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Konferensbidrag (refereegranskat)abstract
- By either autonomously steering or braking, accidents can be avoided or mitigated by a number of active safety functions which are available on the market today. However, these functions are often tailored for specific accident types and for each type either braking or steering may be possible. This contribution considers an algorithm for threat assessment which can be used in general traffic situations not only to decide if an intervention is necessary to avoid an accident, but also to select which type of intervention, steering or braking. The algorithm is evaluated on four accident types; rear-end accidents showing how the appropriate intervention depends on the lateral offset between host vehicle and target vehicle, single-target straight crossing path collisions where the decision depends on the vehicles’ speed, collision scenarios with oncoming vehicles and finally situations where multiple obstacles need to be considered.
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| 9. |
- Brännström, Mattias, 1980, et al.
(författare)
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Model-Based Threat Assessment for Avoiding Arbitrary Vehicle Collisions
- 2010
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Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; 11:3, s. 658-669
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents a model-based algorithm that estimates how the driver of a vehicle can either steer, brake, or accelerate to avoid colliding with an arbitrary object. In this algorithm, the motion of the vehicle is described by a linear bicycle model, and the perimeter of the vehicle is represented by a rectangle. The estimated perimeter of the object is described by a polygon that is allowed to change size, shape, position, and orientation at sampled time instances. Potential evasive maneuvers are modeled, parameterized, and approximated such that an analytical expression can be derived to estimate the set ofmaneuvers that the driver can use to avoid a collision. This set of maneuvers is then assessed to determine if the driver needs immediate assistance to avoid or mitigate an accident. The proposed threat-assessment algorithm is evaluated using authentic data from both real traffic conditions and collision situations on a test track and by using simulations with a detailed vehicle model. The evaluations show that the algorithm outperforms conventional threat-assessment algorithms at rear-end collisions in terms of the timing of autonomous brake activation. This is crucial for increasing the performance of collisionavoidance systems and for decreasing the risk of unnecessary braking. Moreover, the algorithm is computationally efficient and can be used to assist the driver in avoiding or mitigating collisions with all types of road users in all kinds of traffic scenarios.
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| 10. |
- Brännström, Mattias, 1980
(författare)
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On Threat Assessment and Decision-Making for Avoiding Automotive Vehicle Collisions
- 2009
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Road traffic accidents are one of the world’s largest public health problems. In the EU alone, traffic accidents cause approximately 1.8 million injuries and 43.000 fatalities each year. This thesis is concerned with the development of in-vehicle systems that can detect hazardous traffic situations and assist drivers in avoiding or mitigating accidents.An overview is given of different types of accidents and measures that are taken to reduce the number of accidents and their consequences. From this overview, certain types of accidents have been selected to be addressed in this research project. The contribution of this thesis is a number of algorithms that can assess traffic situations and make decisions to actively assist the driver in avoiding or mitigating these accident types.The approach that is used for making decisions on when and how to assist the driver, is to first estimate how a collision can be avoided by the driver. Secondly, the brakes are applied autonomously if hard braking is the only option to avoid or mitigate an accident. The algorithms proposed in this thesis are capable of estimating how collisions can be avoided in any type of collision scenario, such as rear-end collisions andintersection collisions. These algorithms can be used to avoid or mitigate collisions with all types of road users, such as pedestrians, cyclists and other vehicles.The algorithms have been evaluated using data from both real traffic conditions and collision situations on a test track. The results show that the algorithms can improve the performance of conventional rear-end collision avoidance systems, without significantly increasing the risk of unnecessary braking.
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