Shortest viable hyperpath in multimodal networks

Lozano, Angélica; Storchi, Giovanni

doi:10.1016/s0191-2615(01)00038-8

Cited by 67 publications

(31 citation statements)

References 6 publications

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“…Finding an "optimal" strategy for a user (that minimizes expected travel times), has been tackled via the the hypergraph model and the shortest hyperpath problem, introduced by Nguyen and Pallottino in [20] for a single public transportation mode. This approach has been extended to the bi-objective "expected travel time"/"number of transfers" multi-modal viable networks in [16] but no computational experiments where reported. Adapting our algorithms to the hypergraph model is also a promising research direction.…”

Section: Concluding Remarks and Further Extensionsmentioning

confidence: 99%

State-based accelerations and bidirectional search for bi-objective multi-modal shortest paths

Artigues

Huguet

Guèye

et al. 2013

Transportation Research Part C: Emerging Technologies

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Taking into account the multi-modality of urban transportation networks for computing the itinerary of an individual passenger introduces a number of additional constraints such as mode restrictions and various objective functions. In this paper, constraints on modes are gathered under the concept of viable path, modeled by a non deterministic finite state automaton (NFA). The goal is to find the non-dominated viable shortest paths considering the minimization of the travel time and of the number of modal transfers. We show that the problem, initially considered by Lozano and Storchi [15], is a polynomially-solvable bi-objective variant of the mono-objective regular language-constrained shortest path problem [2,8].We propose several label setting algorithms for solving the problem: a topological label-setting algorithm improving on algorithms proposed by Pallottino and Scutellà [23] and Lozano and Storchi [15], a multi-label algorithm using buckets and its bidirectional variant, as well as dedicated goal oriented techniques. Furthermore, we propose a new NFA state-based dominance rule. The computational experiments, carried-out on a realistic urban network, show that the state-based dominance rule associated with bidirectional search yields significant average speed-ups. On an expanded graph comprising 1 859 350 nodes, we obtain on average 3.5 non-dominated shortest paths in less than 180 ms.keywords: bi-objective regular language-constrained shortest path problem, multimodal transportation, finite state automaton, label-setting algorithms, state-based dominance rule, bidirectional search, state-based estimated travel times.

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Section: Concluding Remarks and Further Extensionsmentioning

confidence: 99%

State-based accelerations and bidirectional search for bi-objective multi-modal shortest paths

Artigues

Huguet

Guèye

et al. 2013

Transportation Research Part C: Emerging Technologies

View full text Add to dashboard Cite

show abstract

“…Presently, many navigator producers, such as Apple, Google, and Baidu (China) have started to address pedestrians for its navigation services rather than drivers, which demand that a navigation system integrates all kinds of roads (e.g., pedestrian ways and motor ways) to allow a reasonable and efficient routing for multi-modal navigations [3,4]. Due to the data acquisition ways, however, Tele Atlas (which is now "TOMTOM") and NAVTEQ (which is now "here"), as the most well-known routing-capable database in the world, were not so qualified for such services when we started to investigate relevant works for multi-modal navigation in the year of 2011.…”

Section: Introductionmentioning

confidence: 99%

Automatic and Accurate Conflation of Different Road-Network Vector Data towards Multi-Modal Navigation

Zhang

Yao

Meng

2016

IJGI

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Abstract:With the rapid improvement of geospatial data acquisition and processing techniques, a variety of geospatial databases from public or private organizations have become available. Quite often, one dataset may be superior to other datasets in one, but not all aspects. In Germany, for instance, there were three major road network vector data, viz. Tele Atlas (which is now "TOMTOM"), NAVTEQ (which is now "here"), and ATKIS. However, none of them was qualified for the purpose of multi-modal navigation (e.g., driving + walking): Tele Atlas and NAVTEQ consist of comprehensive routing-relevant information, but many pedestrian ways are missing; ATKIS covers more pedestrian areas but the road objects are not fully attributed. To satisfy the requirements of multi-modal navigation, an automatic approach has been proposed to conflate different road networks together, which involves five routines: (a) road-network matching between datasets; (b) identification of the pedestrian ways; (c) geometric transformation to eliminate geometric inconsistency; (d) topologic remodeling of the conflated road network; and (e) error checking and correction. The proposed approach demonstrates high performance in a number of large test areas and therefore has been successfully utilized for the real-world data production in the whole region of Germany. As a result, the conflated road network allows the multi-modal navigation of "driving + walking".

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“…Many works have been treated the SPP in MTN. An overview of this literature can be found in [13,19,18] [10,17,4,5] [15,20] [22,6] [16,7]. In this type of problem, three constraints are considered.…”

Section: Introductionmentioning

confidence: 99%

“…[7] studied the time-dependent least time paths on MTN. Few studies studied the constraint of the path viability, eliminating paths with illogical sequence of used modes [13,19,18] [4,5]. Ref.…”

Section: Introductionmentioning

confidence: 99%

A fuzzy TOPSIS approach for finding shortest path in multimodal transportation networks

Yamani¹,

Mouncif²,

Rida³

2014

ijco

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The paper must have abstract. In this paper, we present a fuzzy shortest path algorithm in Multimodal Transportation Networks (MTN). To extend the classical problem of shortest path, an innovative framework is presented, which integrates Fuzzy Logic and Multi Criteria Decision Making (MCDM) techniques. The aim is to deal with an efficient design for the multimodal shortest path computation taking into accounts not only the expected travel time, but also additional constraints such as: delays at mode and arc switching points, costs, viability of the sequence of the used modes and the number of modal transfers. To this scope, all previously mentioned constraints are evaluated following a new approach based on Fuzzy Logic and aggregated using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to find the shortest path in MTN. A numerical example is also presented to demonstrate the computational process of the proposed approach.

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Shortest viable hyperpath in multimodal networks

Cited by 67 publications

References 6 publications

State-based accelerations and bidirectional search for bi-objective multi-modal shortest paths

State-based accelerations and bidirectional search for bi-objective multi-modal shortest paths

Automatic and Accurate Conflation of Different Road-Network Vector Data towards Multi-Modal Navigation

A fuzzy TOPSIS approach for finding shortest path in multimodal transportation networks

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