ELEKTRİKLİ ARAÇLAR İÇİN ANALİTİK HİYERARŞİ SÜRECİ KULLANARAK SÜRÜCÜ TERCİHLERİNİ DİKKATE ALAN YOL PLANLAMA

Yıl 2025, Cilt: 33 Sayı: 3, 2054 - 2065, 19.12.2025

Mehmet Arıkan , Sinem Bozkurt Keser , İnci Sarıçiçek , Ahmet Yazici

https://doi.org/10.31796/ogummf.1698018

Öz

Sürdürülebilir taşımacılık ve yeşil lojistik giderek daha önemli hale gelmektedir ve elektrikli araçların verimli kullanımı kritik bir rol oynamaktadır. Ancak, sınırlı sürüş menzili ve optimize edilmiş şarj stratejilerine duyulan ihtiyaç nedeniyle elektrikli araçlar için verimli yol planlaması büyük bir zorluk olmaya devam etmektedir. Genellikle, yol önerileri tek bir kritere dayalı olarak yapılır. Ancak, sürücüler yol seçimi için birden fazla kriteri göz önünde bulundurmak isteyebilir. Bu çalışma, toplam seyahat süresi, enerji tüketimi ve seyahat mesafesini dikkate alarak sürücü tercihlerini içeren çok kriterli bir yol planlama algoritması oluşturmaya odaklanmaktadır. Uygun öneriyi elde etmek için bu üç kriter Analitik Hiyerarşi Süreci kullanılarak değerlendirilmiş ve sürücü tercihlerini dikkate alan yolları belirlemek için Dijkstra algoritması kullanılmıştır. Enerji geri kazanımı nedeniyle negatif enerji ağırlıklarını kaldırmak için Johnson tekniği kullanılmış ve Dijkstra algoritmasının negatif edge ağırlıkları ile uyumsuzluk sorunu çözülmüştür. Sonuçlar, önerilen algoritmanın sürücü tercihlerine göre tasarlanmış çözümleri verimli bir şekilde üretebildiğini ve elektrikli araç rotalama uygulamaları için uygun olduğunu göstermiştir. Bu çalışma, elektrikli araçların yaygın olarak benimsenmesini hedefleyerek kullanıcı memnuniyetini artırmaya yönelik bir yöntem sunmakta ve elektrikli araçların kendine özgü zorluklarının ele alınmasında çok kriterli karar vermenin önemini vurgulamaktadır.

Anahtar Kelimeler

Elektrikli araç , Yol planlama , Sürücü tercihi , Analitik Hiyerarşi Süreci , Dijkstra algoritması

Proje Numarası

101097267, 222N269

PATH PLANNING CONSIDERING DRIVER PREFERENCES USING ANALYTIC HIERARCHY PROCESS FOR ELECTRIC VEHICLES

Öz

Sustainable transportation and green logistics are becoming increasingly important, and the efficient use of electric vehicles (EVs) plays a critical role. However, efficient path planning for EVs remains a major challenge due to limited driving range and the need for optimised charging strategies. Usually, path recommendations are made based on a single criterion. However, drivers may want to consider multiple criteria for path selection. This study focuses on building a multi-criteria path planning algorithm that incorporates driver preferences by considering total travel time, energy consumption and travelling distance. To obtain the appropriate recommendation, these three criteria are evaluated using the Analytic Hierarchy Process (AHP) and Dijkstra algorithm is used to identify roads that take into account driver preferences. Johnson technique was used to remove negative energy weights due to energy recovery and solved the incompatibility problem of the Dijkstra algorithm with negative edge weights. The results have shown the proposed algorithm can efficiently generate solutions designed based on driver preferences and is suitable for EV routing applications. This study presents a method to increase user satisfaction by aiming at the widespread adoption of EVs and emphasizes the importance of multi-criteria decision making in addressing the unique challenges of EVs.

Anahtar Kelimeler

Electric vehicle , Path planning , Driver preference , Analytical Hierarchy Process , Dijkstra algorithm

Destekleyen Kurum

Key Digital Technologies Joint Undertaking (KDT JU) from the European Union’s Horizon Europe Programme and the National Authorities

Proje Numarası

101097267, 222N269

Teşekkür

This paper is supported by the OPEVA project that has received funding within the Key Digital Technologies Joint Undertaking (KDT JU) from the European Union’s Horizon Europe Programme and the National Authorities (France, Belgium, Czechia, Italy, Portugal, Turkey, Switzerland), under grant agreement 101097267. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or KDT JU. Neither the European Union nor the granting authority can be held responsible for them. This work is supported by the Scientific and Technical Research Council of Turkey (TUBITAK), Contract No 222N269, project title: “OPtimization of Electric Vehicle Autonomy (OPEVA)".

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