Public transport route planning: Modified dijkstra's algorithm

Bozyiğit, Alican; Alankuş, Gazihan; Nasiboğlu, Efendi

doi:10.1109/ubmk.2017.8093444

Cited by 42 publications

(23 citation statements)

References 4 publications

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“…If the i-th intersection to the j-th intersection are not directly connected or i = j, d i,j and tr i,j are assigned ∞. In this paper, the travelling time is calculated by vehicle license plate data collected by video-imaging detectors referring to [22][23][24].…”

Section: Preparations For the Trip Chain Buildingmentioning

confidence: 99%

Vehicle Trajectory Prediction Method Based on License Plate Information Obtained from Video-Imaging Detectors in Urban Road Environment

Zhang

Liu

Rai

et al. 2020

Sensors

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The vehicle license plate data obtained from video-imaging detectors contains a huge volume of information of vehicle trip rules and driving behavior characteristics. In this paper, a real-time vehicle trajectory prediction method is proposed based on historical trip rules extracted from vehicle license plate data in an urban road environment. Using the driving status information at intersections, the vehicle trip chain is acquired on the basis of the topologic graph of the road network and channelization of intersections. In order to obtain an integral and continuous trip chain in cases where data is missing in the original vehicle license plate, a trip chain compensation method based on the Dijkstra algorithm is presented. Moreover, the turning state transition matrix which is used to describe the turning probability of a vehicle when it passes a certain intersection is calculated by a massive volume of historical trip chain data. Finally, a k-step vehicle trajectory prediction model is proposed to obtain the maximum possibility of downstream intersections. The overall method is thoroughly tested and demonstrated in a realistic road traffic scenario with actual vehicle license plate data. The results show that vehicles can reach an average accuracy of 0.72 for one-step prediction when there are only 200 historical training data samples. The proposed method presents significant performance in trajectory prediction.

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Section: Preparations For the Trip Chain Buildingmentioning

confidence: 99%

Vehicle Trajectory Prediction Method Based on License Plate Information Obtained from Video-Imaging Detectors in Urban Road Environment

Zhang

Liu

Rai

et al. 2020

Sensors

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“…Using one parameter can"t say we have achieved the optimal path between source and destination. To resolve this above problem, in [26], A. Bozyiğit, G. Alankuş and E. Nasiboğlu, proposed a modified Dijkstra's algorithm and it is implemented in a real-world public transport network. In this approach, the author assigned some negative value for each path and found the alternate road to achieve a good result.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal packet routing for wireless body area network using software defined network to handle medical emergency

Manickavasagam¹,

Amutha²,

Priyanka³

2020

IJECE

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<span lang="EN-US">The packet forwarding node selection is one of the main constraints in the Software Defined Network (SDN). To improve the network performance, the SDN controller has to choose the shortest and optimised path between source and destination in routine and emergency packet transmission. In e-health service, information of the emergency patient has to be transferred immediately to remote hospitals or doctors by using efficient packet routing approach in Wireless Body Area Network (WBAN). In WBAN, to improve the packet transmission, the optimal packet routing policy developed based on packets priority with the support of a greedy algorithm for SDN. The SDN Controller selects the forwarding node based on node propagation delay and available bandwidth between two forwarding nodes. The mesh network topology network created for implementation, implementation results are compared with existing research works. Finally, this algorithm implemented in our institution, Software defined communication testbed laboratory (SDCTestbed Lab) with the support of 13 Zodiac-Fx (Forwarding device), 2 Raspberry-Pi3 B+ Model (host) and Arduino kit (sensor node).</span>

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“…A. Bozyigit et al [2] also proposed another technique to calculate the shortest path. Dijkstra's algorithm is mostly used in order to find the shortest path, but it is not efficient for public transport route planning because it ignores the number of transfer and walking distances.…”

Section: Related Workmentioning

confidence: 99%

Multi-Modal Route Recommender System for Bangkok Public Transportation

Poonsilp*

2020

IJRTE

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Currently, Bangkok has a 151 kilometers service of a rail line, whereas the total plan is 540 kilometers. More rail lines are now under construction and supposed to be done by a few years. Regarding a massive public transportation network, we need a route recommender system to make traveling more efficient. This paper proposes the route recommender system which supports multi modes of transportation in Bangkok, including BTS, MRT, ARL, BMTA bus, and Chaophraya Riverboat. Users can see suggested routes and sort routes by travel time, fare, number of transfer, and overall score. The A* algorithm with the Haversine formula as the heuristic function is used to calculate the possible routes. Then the best route is selected based on the score, which is calculated form four factors: travel time, fare, number of transfer, and distance. The database contains 13,510 stops, and the results show that the system can suggest accurate routes within a few seconds, which is fast enough for all use cases and achieved overall user satisfaction at 84.8% from our user experience survey.

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Public transport route planning: Modified dijkstra's algorithm

Cited by 42 publications

References 4 publications

Vehicle Trajectory Prediction Method Based on License Plate Information Obtained from Video-Imaging Detectors in Urban Road Environment

Vehicle Trajectory Prediction Method Based on License Plate Information Obtained from Video-Imaging Detectors in Urban Road Environment

Optimal packet routing for wireless body area network using software defined network to handle medical emergency

Multi-Modal Route Recommender System for Bangkok Public Transportation

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