Decision Support for Route Search and Optimum Finding in Transport Networks under Uncertainty

Szücs, Gábor

doi:10.1016/s1665-6423(15)30011-0

Cited by 10 publications

(7 citation statements)

References 24 publications

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“…In the article (Szücs, 2015), the authors proposed to solve the transport problem using the Dempster-Shafer theory. Cost interval information for each route was used as a basis.…”

Section: Review Of the Literaturementioning

confidence: 99%

Intelligent System for Automation Search of Public Transport Routes

Holyk

Zhesan

Miroshnichenko

et al. 2022

SJPU

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This article is devoted to automation of search of routes of passenger flows of inhabitants of the city on the basis of routes of public transport. To do this, it is proposed to use satellite data that reflect the movement of passengers. Based on the analysis of data arrays of information on the movement of cellular subscribers and the use of message messages to determine the effectiveness of passenger routes of public transport, the article proposes to create a system of automatic search of public transport routes, which includes different classes of charts and data bases. You can use data from cellular operators to do this. This can increase the accuracy of certain traffic volumes and the ability to monitor them in real time. Reliable information on the routes of urban public transport allows to determine passenger flows and efficiently perform transport services. The main requirements for modeling the city’s passenger traffic are presented. Methods of obtaining data on determining the city’s passenger traffic and public transport are considered. Documentation for the creation of the ISASR (Intelligent System for Automation Search of Routes) project has been developed. The MVC (Model-View-Controller) architectural template was used to develop the project. Class diagrams and precedent diagrams have been developed for the model. Database structures have been created and vehicle types and user types have been defined. Algorithms for finding routes for different situations, with different latitude and longitude coordinates, as well as different number of stops and transfers have been developed.

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“…In the article (Szücs, 2015), the authors proposed to solve the transport problem using the Dempster-Shafer theory. Cost interval information for each route was used as a basis.…”

Section: Review Of the Literaturementioning

confidence: 99%

Intelligent System for Automation Search of Public Transport Routes

Holyk

Zhesan

Miroshnichenko

et al. 2022

SJPU

View full text Add to dashboard Cite

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“…In [ 26 ], the authors’s main objective was to find a solution to the path-planning problem in the street network, and then find the equilibrium point of this optimization problem. The streets in this problem have uncertain objectives.…”

Section: Related Workmentioning

confidence: 99%

“…Previous research solved the parking problem as an optimization problem [ 24 , 26 , 27 , 33 ], game theoretic problem [ 28 , 30 , 31 , 34 , 35 ], queueing problem [ 39 ], and machine learning problem [ 38 ]. Different preferences were considered in this research, such as driving distance to the parking area, parking cost, physical positions, availability of parking resources, traffic congestion on the streets to the parking area, and driving time to the parking area.…”

Section: Related Workmentioning

confidence: 99%

A Balanced Algorithm for In-City Parking Allocation: A Case Study of Al Madinah City

Abdeen

Nemer

Sheltami

2021

Sensors

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Parking in heavily populated areas has been considered one of the main challenges in the transportation systems for the past two decades given the limited parking resources, especially in city centres. Drivers often waste long periods of time hunting for an empty parking spot, which causes congestion and consumes energy during the process. Thus, finding an optimal parking spot depends on several factors such as street traffic congestion, trip distance/time, the availability of a parking spot, the waiting time on the lot gate, and the parking fees. Designing a parking spot allocation algorithm that takes those factors into account is crucial for an efficient and high-availability parking service. We propose a smart routing and parking algorithm to allocate an optimal parking space given the aforementioned limiting factors. This algorithm supports choosing the appropriate travel route and parking lot while considering the real-time street traffic and candidate parking lots. A multi-objective function is introduced, with varying weights of the five factors to produce the optimal parking spot with the least congested route while achieving a balanced utilization for candidate parking lots and a balanced traffic distribution. A queueing model is also developed to investigate the availability rate in candidate parking lots while considering the arrival rate, departure rate, and the lot capacity. To evaluate the performance of the proposed algorithm, simulation scenarios have been performed for different cases of high and low traffic intensity rates. We have tested the algorithm on in-city parking facility in the city of Al Madinah as a case study. The results show that the proposed algorithm is effective in achieving a balanced utilization of the parking lots, reducing traffic congestion rates on all routes to candidate parking lots, and minimizing the driving time to the assigned parking spot. Additionally, the proposed algorithm outperforms the MADM algorithm in terms of the selected three metrics for the five periods.

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“…Path planning in a graph represents one of the most fundamental tasks in a graph space. In the literature, several approaches deal with this task by limiting and conditioning it to particular contexts, rendering it computable in closed scenarios [1][2][3][4][5]. In this context, the main approaches developed to deal with the problem of best-searching path planning are the following.…”

Section: Introductionmentioning

confidence: 99%

Algorithm Based on Morphological Operators for Shortness Path Planning

Perez-Ramos,

Ramirez-Rosales,

Canton-Enriquez

et al. 2024

Algorithms

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The problem of finding the best path trajectory in a graph is highly complex due to its combinatorial nature, making it difficult to solve. Standard search algorithms focus on selecting the best path trajectory by introducing constraints to estimate a suitable solution, but this approach may overlook potentially better alternatives. Despite the number of restrictions and variables in path planning, no solution minimizes the computational resources used to reach the goal. To address this issue, a framework is proposed to compute the best trajectory in a graph by introducing the mathematical morphology concept. The framework builds a lattice over the graph space using mathematical morphology operators. The searching algorithm creates a metric space by applying the morphological covering operator to the graph and weighing the cost of traveling across the lattice. Ultimately, the cumulative traveling criterion creates the optimal path trajectory by selecting the minima/maxima cost. A test is introduced to validate the framework’s functionality, and a sample application is presented to validate its usefulness. The application uses the structure of the avenues as a graph. It proposes a computable approach to find the most suitable paths from a given start and destination reference. The results confirm that this is a generalized graph search framework based on morphological operators that can be compared to the Dijkstra approach.

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Decision Support for Route Search and Optimum Finding in Transport Networks under Uncertainty

Cited by 10 publications

References 24 publications

Intelligent System for Automation Search of Public Transport Routes

Intelligent System for Automation Search of Public Transport Routes

A Balanced Algorithm for In-City Parking Allocation: A Case Study of Al Madinah City

Algorithm Based on Morphological Operators for Shortness Path Planning

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