Path-finding through flexible hierarchical road networks: An experiential approach using taxi trajectory data

Li, Qingquan; Zeng, Zhe; Zhang, Tong; Li, Jonathan; Wu, Zhongheng

doi:10.1016/j.jag.2010.07.003

Cited by 51 publications

(21 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this study, probe vehicles were assumed to travel on the shortest path between two GPS points. In reality, travellers may choose the optimal path based on multiple criteria, such as travel time, number of turns and so on (Li et al 2011c, Ramaekers et al 2013). The incorporation of travellers' route choice behaviour is suggested as an interesting extension of the proposed algorithm, potentially improving the MM accuracy when the sampling time interval is large.…”

Section: Discussionmentioning

confidence: 99%

Map-matching algorithm for large-scale low-frequency floating car data

Chen

Yuan

et al. 2013

International Journal of Geographical Information Science

Self Cite

154

View full text Add to dashboard Cite

Large-scale global positioning system (GPS) positioning information of floating cars has been recognised as a major data source for many transportation applications. Mapping large-scale low-frequency floating car data (FCD) onto the road network is very challenging for traditional map-matching (MM) algorithms developed for in-vehicle navigation. In this paper, a multi-criteria dynamic programming map-matching (MDP-MM) algorithm is proposed for online matching FCD. In the proposed MDP-MM algorithm, the MDP technique is used to minimise the number of candidate routes maintained at each GPS point, while guaranteeing to determine the best matching route. In addition, several useful techniques are developed to improve running time of the shortest path calculation in the MM process. Case studies based on real FCD demonstrate the accuracy and computational performance of the MDP-MM algorithm. Results indicated that the MDP-MM algorithm is competitive with existing algorithms in both accuracy and computational performance.

show abstract

Section: Discussionmentioning

confidence: 99%

Map-matching algorithm for large-scale low-frequency floating car data

Chen

Yuan

et al. 2013

International Journal of Geographical Information Science

Self Cite

154

View full text Add to dashboard Cite

show abstract

“…Many Studies have focused on the optimal route analysis algorithms suitable for vehicle navigation and most of them rely on a specific topological structure of the road network [11][12][13][14]. For example, the natural road hierarchy network is a kind of topological structure used by hierarchical network models and is popular for navigation applications.…”

Section: Route Computing Models Of the Cndf Modelmentioning

confidence: 99%

A Novel Dynamic Physical Storage Model for Vehicle Navigation Maps

Wang

Zhong

et al. 2016

IJGI

View full text Add to dashboard Cite

Abstract:The physical storage model is one of the key technologies for vehicle navigation maps used in a navigation system. However, the performance of most traditional storage models is limited in dynamic navigation due to the static storage format they use. In this paper, we proposed a new physical storage model, China Navigation Data Format (CNDF), which helped access and update the navigation data. The CNDF model used the reach-based hierarchy method to build a road hierarchal network, which enhanced the efficiency of data compression. It also adopted the Linear Link Coding method, in which the start position was combined with the end position as the identification code for multi-level links, and each link traced up-level links consistently without recording the array of identifications. The navigation map of East China (including Beijing, Tianjin, Shandong, Hebei, and Jiangsu) at 1:10,000, generated using the CNDF model, and the real time traffic information in Beijing were combined to test the performance of a navigation system using an embedded navigation device. Results showed that it cost less than 1 second each time to refresh the navigation map, and the accuracy of the hierarchal shortest-path algorithm was 99.9%. Our work implied that the CNDF model is efficient in vehicle navigation applications.

show abstract

“…Reference [6] found that driver's travel experience as well as a renewal of all acquirable traffic information that can assist in confirming the reference points in road network have influence on the route choice of the next trip. Reference [7] presented an experiential approach to compute optimal paths, in which path-planning was supported by a flexible road network hierarchy using the experience of taxi drivers. Other studies that investigated driving experience are Yu et al's work on modelling bus arrival times [8,9] and vehicle's route choice [10], and Yao et al's study on accident detection [11], etc.…”

Section: Literature Reviewmentioning

confidence: 99%