A Mobile Application for Multimodal Trip Planning

Dimokas, Nikos; Kalogirou, Kostas; Spanidis, Pavlos; Kehagias, Dionysios

doi:10.1109/iisa.2018.8633665

Cited by 8 publications

(3 citation statements)

References 11 publications

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“…The research suggests a model to find solutions for traffic flow with the participation of carpooling, public buses and trains within the framework of a single traffic system. The developers in [26] designed a mobile platform that offers suggestions for planning a trip that includes only two modes of transport, including carpooling and public buses. This solution ensures the shortest route for the passenger while considering delays caused by road accidents and traffic congestion.…”

Section: Related Workmentioning

confidence: 99%

A Dynamic Mobility Traffic Model Based on Two Modes of Transport in Smart Cities

2021

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This paper focuses on transportation models in smart cities. We propose a new dynamic mobility traffic (DMT) scheme which combines public buses and car ride-sharing. The main objective is to improve transportation by maximizing the riders’ satisfaction based on real-time data exchange between the regional manager, the public buses, the car ride-sharing and the riders. OpenStreetMap and OMNET++ were used to implement a realistic scenario for the proposed model in a city like Ottawa. The DMT scheme was compared to a multi-loading system used for a school bus. Simulations showed that rider satisfaction was enhanced when a suitable combination of transportation modes was used. Additionally, compared to the other scheme, this DMT scheme can reduce the stress level of car ride-sharing and public buses during the day to the minimal level.

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Section: Related Workmentioning

confidence: 99%

A Dynamic Mobility Traffic Model Based on Two Modes of Transport in Smart Cities

2021

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“…The research suggests a model to find solutions for traffic flow with the participation of carpooling, public buses, and trains within the framework of a single traffic system. The developers in [24] designed a mobile platform that offers suggestions for planning a trip that includes only two modes of transport, that is, carpooling and public buses. This solution ensures the shortest route for the passenger while considering delays caused by road accidents and traffic congestion.…”

Section: Related Workmentioning

confidence: 99%

Game theoretic approach for public multi‐mode transportation in smart cities

2021

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Here, a dynamic multi-mode transportation model is developed in which the passenger, for his trip, can use one or a combination of the transportation forms such as a car, a bus or a bicycle. This model is based on the game theory concept-based trip costoptimization and it is called game theory multi-mode transportation. The proposed system is implemented through a realistic scenario in a specific city using the OMNET++ and the OpenStreetMap software tools. The results show that the average trip price and the average trip time are improved when using the proposed model.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…Considering composing multiple different travel modes, the trip planning issue turns to be more complicated. In order to supply the necessary information for multimodal trip planning, the network usually consists of many layers [5]. Each layer represents a different transport mode, and interlayer links are representing the transfer from one mode to the other.…”

Section: Introductionmentioning

confidence: 99%

A Microservice–based Big Trajectory Data Processing Platform for Multimodal Trip Planning

Na¹,

Wang²,

Xu³

et al. 2019

Proceedings of the 2019 International Conference on Big Data, Electronics and Communication Engineering (BDECE 2019)

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Trip planning is an essential function provided by an intelligent transportation system. As many different transport modes have been emerging recently, it becomes a common requirement to mix available transport types to find the most comfort and fastest solutions for getting given destinations. A key challenge for achieving such a desired trip plan is to get quality estimations of all possible traveling services rapidly and accurately. Thanks to the rapid growth of mobile computing, lots of real-time data about traffic status can be collected throw smartphones. Based on such continuously acquired data, we would get quality estimations more accurately and efficiently. Thus, we design and implement a big trajectory data processing platform based on microservices for supporting multimodal trip planning. The paper introduces not only the services and service processes for dealing with the big trajectory data but also the implementation and distributed deployment based on microservices deployed in multiple Dockers. Regarding the loosely-coupled nature of microservices, this platform can provide a flexible way to support trip planning applications consider new available travel modes quickly.

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A Mobile Application for Multimodal Trip Planning

Cited by 8 publications

References 11 publications

A Dynamic Mobility Traffic Model Based on Two Modes of Transport in Smart Cities

A Dynamic Mobility Traffic Model Based on Two Modes of Transport in Smart Cities

Game theoretic approach for public multi‐mode transportation in smart cities

A Microservice–based Big Trajectory Data Processing Platform for Multimodal Trip Planning

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