Vehicle routing in urban areas based on the Oil Consumption Weight ‐Dijkstra algorithm

Zhang, Jindong; Feng, Yulin; Shi, Feifei; Wang, Gang; Ma, Baosong; Li, Ruisheng; Jia, Xiaoyan

doi:10.1049/iet-its.2015.0168

Cited by 54 publications

(23 citation statements)

References 16 publications

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“…Then, when the goal is reached by the algorithm, a feasible path is returned and used by the vehicle to get to the goal position. In recent years, practically all works use variations of the Dijkstra's algorithm [19][20][21], and older ones, like [22], use the algorithms without variations. Dijkstra's algorithm is described in the literature as a fast, simple path planning method.…”

Section: Related Workmentioning

confidence: 99%

A Comparison of Local Path Planning Techniques of Autonomous Surface Vehicles for Monitoring Applications: The Ypacarai Lake Case-study

Peralta

Arzamendia

Gregor

et al. 2020

Sensors

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Local path planning is important in the development of autonomous vehicles since it allows a vehicle to adapt their movements to dynamic environments, for instance, when obstacles are detected. This work presents an evaluation of the performance of different local path planning techniques for an Autonomous Surface Vehicle, using a custom-made simulator based on the open-source Robotarium framework. The conducted simulations allow to verify, compare and visualize the solutions of the different techniques. The selected techniques for evaluation include A*, Potential Fields (PF), Rapidly-Exploring Random Trees* (RRT*) and variations of the Fast Marching Method (FMM), along with a proposed new method called Updating the Fast Marching Square method (uFMS). The evaluation proposed in this work includes ways to summarize time and safety measures for local path planning techniques. The results in a Lake environment present the advantages and disadvantages of using each technique. The proposed uFMS and A* have been shown to achieve interesting performance in terms of processing time, distance travelled and security levels. Furthermore, the proposed uFMS algorithm is capable of generating smoother routes.

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Section: Related Workmentioning

confidence: 99%

A Comparison of Local Path Planning Techniques of Autonomous Surface Vehicles for Monitoring Applications: The Ypacarai Lake Case-study

Peralta

Arzamendia

Gregor

et al. 2020

Sensors

View full text Add to dashboard Cite

show abstract

“…Informasi yang terdapat pada sistem informasi geografis berupa deskripsi, gambar dan lokasi [13] khususnya untuk pencarian tempat parkir [14]. Pengguna terkadang sulit menemukan lokasi parkir serta ketersediaan tempat parkir yang ingin dituju [15]. Poin penting yang sangat bermanfaat bagi pengguna adalah menemukan rute terpendek untuk sampai ke lokasi [16].…”

Section: Iunclassified

Penerapan Algoritma Dijkstra Untuk Menentukan Rute Terbaik Pada Mobile E-Parking Berbasis Sistem Informasi Geografis

Prianto

Kusnadi

2018

jpit

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Lack of information about the posision of a place and find the best route to get to a destination is complicated, especially looking for a route in finding a parking space. Unavailability of applications that provide information and navigate parking users to find the best route in realtime is a problem that must be answered. Dijkstra's algorithm is one method of solving problems in finding the best route. The Dijkstra algorithm has compared the possible routes to be traversed and calculated every possible distance. The route with the shortest distance would be the best choice This application was built using an Android-based Geographic Information System that utilizes the Google Maps feature as a parking user interface service. This study uses the Java programming language with Android Studio as an IDE (Integrated Development Environment) and the prototyping model is used in developing problem solving and using UML (Unified Modeling Language) as a system design tool. The results that have been achieved from this research is that Dijkstra's algorithm can answer the problem faced by providing the best route navigation from the user's location to the parking lot at the destination Abstrak  Kurangnya informasi mengenai posisi suatu tempat dan menemukan rute terbaik untuk menuju sebuah tempat tujuan termasuk hal yang cukup rumit terutama mencari rute dalam menemukan tempat parkir. Tidak tersedianya aplikasi yang menyediakan informasi serta menavigasi pengguna parkir untuk menemukan rute terbaik secara realtime menjadi suatu masalah yang harus dicari jawabannya. Algoritma Dijkstra merupakan salah satu metode penyelesaian masalah dalam pencarian rute terbaik. Algoritma Dijkstra membandingkan kemungkinan rute yang akan dilalui dan dihitung setiap kemungkinan jarak. Rute dengan jarak terpendek akan menjadi pilihan terbaik. Aplikasi ini dibangun dengan menggunakan sistem informasi geografis berbasis android yang memanfaatkan fitur Google Maps sebagai layanan antar muka pengguna parker. Penelitian ini menggunakan bahasa pemrograman Java dengan Android Studio sebagai IDE (Integrated Development Environment) dan model prototyping digunakan dalam pengembangan penyelesaian masalah serta menggunakan UML (Unified Modelling Language) sebagai tools perancangan system. Hasil yang telah dicapai dari penelitian ini adalah algoritma Dijkstra dapat menjawab masalah yang dihadapi yakni memberikan navigasi rute terbaik dari lokasi pengguna menuju tempat parkir di lokasi tujuan.

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“…As a fundamental optimization method, SPO focus on how to solve the best path under static routing networks and ignores the changes in traffic environments [4]- [7]. There are numerous researches based on SPO, and most of them are designed for specific situations or problems to achieve practical applications [8]- [11]. Under the dynamic routing environments, a lot of sophisticated and stochastic uncertainties seriously affect path optimization, such as regular traffic congestions, signalized intersections and so on [12]- [15].…”

Section: Introductionmentioning

confidence: 99%

Co-Evolutionary Optimization Algorithm Based on the Future Traffic Environment for Emergency Rescue Path Planning

Wen

Lin

2020

IEEE Access

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Emergency rescue plays a key role in accident remediation and prevention. It has been the most critical factor to control the negative impacts of accident deterioration, which can save more lives and reduce property loss in time. As an essential component, emergency rescue path planning can effectively shorten the travelling time and improve the robustness of the rescue path. However, there still exist various uncertainties that may make a great impact on selecting the rescue path, which is less successful and still requires further research. To address the problem of low rescue efficiency, a co-evolutionary optimization algorithm (CEOA) is proposed in this study. Meanwhile, this study presents how the sub-path weight function co-evolves with the future traffic environment dynamics using the evolution mechanism, considering the complex vehicle running characteristics in the urban roads. Three sets of simulation experiments are conducted to test the comprehensive performance of CEOA under various scenarios. Experimental results show that the proposed CEOA is superior to traditional and emerging path optimization methods in terms of the travelling time and its stability, such as on-line re-optimization (OLRO) and co-evolutionary path optimization (CEPO). The proposed CEOA integrates the advanced advantages of regular re-optimization and co-evolutionary optimization, and opens the door to develop new path optimization technology. The findings provide powerful technology support and a theoretical basis for emergency rescue management improvement.

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Vehicle routing in urban areas based on the Oil Consumption Weight ‐Dijkstra algorithm

Cited by 54 publications

References 16 publications

A Comparison of Local Path Planning Techniques of Autonomous Surface Vehicles for Monitoring Applications: The Ypacarai Lake Case-study

A Comparison of Local Path Planning Techniques of Autonomous Surface Vehicles for Monitoring Applications: The Ypacarai Lake Case-study

Penerapan Algoritma Dijkstra Untuk Menentukan Rute Terbaik Pada Mobile E-Parking Berbasis Sistem Informasi Geografis

Co-Evolutionary Optimization Algorithm Based on the Future Traffic Environment for Emergency Rescue Path Planning

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