Enabling Safe Autonomous Driving in Real-World City Traffic Using Multiple Criteria Decision Making

Furda, Andrei; Vlacic, Ljubo

doi:10.1109/mits.2011.940472

Cited by 136 publications

(50 citation statements)

References 6 publications

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“…The automaton worked on the distance between the vehicles and lane boundaries as input. Similar work exists in [21,22]. These travel decisions however only hold for organized traffic.…”

Section: Related Researchmentioning

confidence: 78%

Reactive Planning of Autonomous Vehicles for Traffic Scenarios

Kala

Warwick

2015

Electronics

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Autonomous vehicles operate in real time traffic scenarios and aim to reach their destination from their source in the most efficient manner possible. Research in mobile robotics provides a variety of sophisticated means with which to plan the path of these vehicles. Conversely professional human drivers usually drive using instinctive means, which enables them to reach their goal almost optimally whilst still obeying all traffic laws. In this paper we propose the use of fuzzy logic for novel motion planning. The planner is generated using an evolutionary algorithm which resembles the learning stage of professional drivers. Whether to overtake or not, is a decision which affects one's driving and the decision is made using some deliberation. We further extend the approach to perform decision making regarding overtaking for all vehicles. Further we coordinate the motion of the vehicles at a traffic crossing to avoid any potential jam or collision. Experimental results prove that by using this approach we have been able to make the vehicles move in an optimal manner in a variety of scenarios.

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“…The automaton worked on the distance between the vehicles and lane boundaries as input. Similar work exists in [21,22]. These travel decisions however only hold for organized traffic.…”

Section: Related Researchmentioning

confidence: 78%

Reactive Planning of Autonomous Vehicles for Traffic Scenarios

Kala

Warwick

2015

Electronics

View full text Add to dashboard Cite

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“…In fact, in the developed economies, traffic accidents cause millions of people killed or severely injured each year on the roads [6]. The design of intelligent transportation systems should be aimed not only at reducing the number of traffic accidents, and therefore the number of victims [7], but also at providing and deploying enhanced rescue coordination mechanisms so that, once the accident occurs, its consequences can be reduced [8]. A second area of great public concern focuses on intelligent transport systems to significantly alleviate the growing traffic congestions affecting urban areas [2].…”

Section: Tc Technical View On Itsmentioning

confidence: 99%

Highlights: IEEE ITS Society Technical Committee on Mobile Communications Networks for ITS [Technical Committees]

Toh¹,

Higashino²,

Cano³

et al. 2012

IEEE Intell. Transport. Syst. Mag.

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“…Even autonomous vehicles model and integrate different possible behaviours. For organized travel, a limited range of behaviours are possible, as demonstrated in [15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Motion Planning of Autonomous Vehicles on a Dual Carriageway without Speed Lanes

Kala

Warwick

2015

Electronics

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Abstract:The problem of motion planning of an autonomous vehicle amidst other vehicles on a straight road is considered. Traffic in a number of countries is unorganized, where the vehicles do not move within predefined speed lanes. In this paper, we formulate a mechanism wherein an autonomous vehicle may travel on the "wrong" side in order to overtake a vehicle. Challenges include assessing a possible overtaking opportunity, cooperating with other vehicles, partial driving on the "wrong" side of the road and safely going to and returning from the "wrong" side. The experimental results presented show vehicles cooperating to accomplish overtaking manoeuvres.

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Enabling Safe Autonomous Driving in Real-World City Traffic Using Multiple Criteria Decision Making

Cited by 136 publications

References 6 publications

Reactive Planning of Autonomous Vehicles for Traffic Scenarios

Reactive Planning of Autonomous Vehicles for Traffic Scenarios

Highlights: IEEE ITS Society Technical Committee on Mobile Communications Networks for ITS [Technical Committees]

Motion Planning of Autonomous Vehicles on a Dual Carriageway without Speed Lanes

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