Dynamic distributed lanes: motion planning for multiple autonomous vehicles

Kala, Rahul; Warwick, Kevin

doi:10.1007/s10489-014-0517-1

Cited by 8 publications

(5 citation statements)

References 39 publications

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“…Centralized MAP involves using an intermediary agent that has complete knowledge of the task. The distributed or decentralized approach spreads the planning responsability among agents, which are in charge of interacting with each other to coordinate their local solutions, if necessary [28,18]. The adoption of a centralized approach is aimed at improving the planner performance by taking advantage of the inherent structure of the MAP tasks [22,8].…”

Section: Related Workmentioning

confidence: 99%

FMAP: Distributed cooperative multi-agent planning

2014

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This paper proposes FMAP (Forward MultiAgent Planning), a fully-distributed multi-agent planning method that integrates planning and coordination. Although FMAP is specifically aimed at solving problems that require cooperation among agents, the flexibility of the domain-independent planning model allows FMAP to tackle multi-agent planning tasks of any type. In FMAP, agents jointly explore the plan space by building up refinement plans through a complete and flexible forward-chaining partial-order planner. The search is guided by h DT G , a novel heuristic function that is based on the concepts of Domain Transition Graph and frontier state and is optimized to evaluate plans in distributed environments. Agents in FMAP apply an advanced privacy model that allows them to adequately keep private information while communicating only the data of the refinement plans that is relevant to each of the participating agents. Experimental results show that FMAP is a general-purpose approach that efficiently solves tightly-coupled domains that have specialized agents and cooperative goals as well as loosely-coupled problems. Specifically, the empirical evaluation shows that FMAP outperforms current MAP systems at solving complex planning tasks that are adapted from the International Planning Competition benchmarks.

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Section: Related Workmentioning

confidence: 99%

FMAP: Distributed cooperative multi-agent planning

2014

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“…The average speed includes any time spent in waiting for traffic lights at V 2 (if any). In a related publication [20], we showed that vehicles may be waiting for prolonged times at the traffic crossings and hence, accounting for this waiting time is important.…”

Section: Algorithmmentioning

confidence: 99%

Computing journey start times with recurrent traffic conditions

Kala

Warwick

2014

IET Intelligent Transport Systems

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In this paper we discuss how technology can be used to effectively solve the problem of deciding on journey start times for recurrent traffic conditions. The developed algorithm guides vehicles to travel on more reliable routes which are not easily prone to congestion or travel delays, ensures that the start time is as late as possible to avoid the traveller waiting too long at their destination and attempts to minimize the travel time. Experiments show that in order to be more certain of reaching their destination on time, a traveller has to leave early and correspondingly arrive early, resulting in a large waiting time. The application developed here asks the user to set this certainty factor as per the task in hand, and computes the best start time and route.

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“…The factor is only of importance when there are far too many vehicles waiting to cross an intersection, and as in other cases, the queue clears well before this factor comes into play. Complete details regarding the traffic light operations can be found in Kala [22].…”

Section: Traffic Simulationmentioning

confidence: 99%

“…A synthetic overtaking scenario is shown in Figure 2. Complete details regarding the overtaking procedure can be found in Kala [22].…”

Section: Single-lane Overtakingmentioning

confidence: 99%

Congestion avoidance in city traffic

Kala

Warwick

2014

J of Advced Transportation

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SUMMARYThe number of vehicles on the road (worldwide) is constantly increasing, causing traffic jams and congestion especially in city traffic. Anticipatory vehicle routing techniques have thus far been applied to fairly small networked traffic scenarios and uniform traffic. We note here a number of limitations of these techniques and present a routing strategy on the assumption of a city map that has a large number of nodes and connectivity and where the vehicles possess highly varying speed capabilities. A scenario of operation with such characteristics has not previously been sufficiently studied in the literature. Frequent short-term planning is preferred as compared with infrequent planning of the complete map. Experimental results show an efficiency boost when single-lane overtaking is allowed, traffic signals are accounted for and every vehicle prefers to avoid high traffic density on a road by taking an alternative route. Comparisons with optimistic routing, pessimistic routing and time message channel routing are given.

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Dynamic distributed lanes: motion planning for multiple autonomous vehicles

Cited by 8 publications

References 39 publications

FMAP: Distributed cooperative multi-agent planning

FMAP: Distributed cooperative multi-agent planning

Computing journey start times with recurrent traffic conditions

Congestion avoidance in city traffic

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