Autonomous vehicle overtaking- an online solution

Ghumman, Usman; Kunwar, Faraz

doi:10.1109/ical.2009.5262854

Cited by 24 publications

(18 citation statements)

References 13 publications

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“…T . With the objective function (4a), whereĴ and Q are chosen as in (6) and 7, the problem (4) is an SOCP. This program is solved sequentially and updating is done by moving in the direction of the current optimal solution…”

Section: Sequential Socpmentioning

confidence: 99%

“…There exist several methods for solving the overtaking problem described above. For example, in [6], the overtaking is made using a so-called shadow vehicle and the Rendezvous-guidance technique, while in [7] by approximating lane change maneuvers using fifth order minimal jerk trajectories. Other approaches include grid/graph based search [8], [9], but these methods rely on the availability of good heuristics, i.e., does not fulfill requirement a.…”

Section: Introductionmentioning

confidence: 99%

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Comparison between mixed-integer and second order cone programming for autonomous overtaking

Karlsson

Murgovski

Sjöberg

2018

2018 European Control Conference (ECC)

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This paper concerns optimally controlling an autonomous vehicle to perform safe and comfortable overtaking of a slower moving leading vehicle. The contribution is an analysis of the comparisons between a convex relaxation with the standard mixed integer quadratic program. The main difference between the formulations is that the sampling is performed in the temporal domain in the standard formulation, but in the spatial domain for the convex relaxation. The case of varying lateral position and longitudinal velocity is studied for both algorithms and the solution quality and computational effort are discussed. The results are given in a case study where an ego vehicle is forced to accelerate when overtaking a leading vehicle, due to the presence of an oncoming vehicle. The results illustrate that the temporal and spatial formulation's yield similar solutions but obtaining them require less computational effort in the spatial domain.

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Section: Sequential Socpmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comparison between mixed-integer and second order cone programming for autonomous overtaking

Karlsson

Murgovski

Sjöberg

2018

2018 European Control Conference (ECC)

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“…Most recently, the University of Ulster, in Northern Ireland, have been working in microscopic model (behavior of individual vehicles), which considerate the actions of the close cars [8]. Finally, other simulations consid ering trajectory-generation method for autonomous overtaking capable of handling emergency situations and aborting the maneuver have been developed in [9].…”

Section: Rel Ated Workmentioning

confidence: 99%

Longitudinal fuzzy control for autonomous overtaking

Pérez

Milanés

Onieva

et al. 2011

2011 IEEE International Conference on Mechatronics

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“…A simulated guidance-based on-line trajectory planning algorithm -based on the principles of Rendezvous Guidance -is defined in Usman and Kunwar (2009). A mathematical model is used in Shamir (2004) to design a smooth and comfortable optimal lane-change trajectory for simulation purposes.…”

Section: Introductionmentioning

confidence: 99%

Intelligent automatic overtaking system using vision for vehicle detection

Milanés

Llorca

Villagrá

et al. 2012

Expert Systems with Applications

114

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There is clear evidence that investment in intelligent transportation system technologies brings major social and economic benefits. Technological advances in the area of automatic systems in particular are becoming vital for the reduction of road deaths. We here describe our approach to automation of one the riskiest autonomous manoeuvres involving vehicles -overtaking. The approach is based on a stereo vision system responsible for detecting any preceding vehicle and triggering the autonomous overtaking manoeuvre. To this end, a fuzzy-logic based controller was developed to emulate how humans overtake. Its input is information from the vision system and from a positioning-based system consisting of a differential global positioning system (DGPS) and an inertial measurement unit (IMU). Its output is the generation of action on the vehicle's actuators, i.e., the steering wheel and throttle and brake pedals. The system has been incorporated into a commercial Citroen car and tested on the private driving circuit at the facilities of our research center, CAR, with different preceding vehicles -a motorbike, car, and truck -with encouraging results.

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Autonomous vehicle overtaking- an online solution

Cited by 24 publications

References 13 publications

Comparison between mixed-integer and second order cone programming for autonomous overtaking

Comparison between mixed-integer and second order cone programming for autonomous overtaking

Longitudinal fuzzy control for autonomous overtaking

Intelligent automatic overtaking system using vision for vehicle detection

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