Limited driving range remains one of the barriers for widespread adoption of electric vehicles (EVs). To address the problem of range anxiety, this paper presents an energy consumption prediction method for EVs, designed for energy-efficient routing. This data-driven methodology combines real-world measured driving data with geographical and weather data to predict the consumption over any give...

Classification is very important in the process of Machine Learning and Data Mining. Traditional Neural Network classifier work with many kinds of data such as items, text documents, signals, networks, but there is lack of study on Trajectory Classification based on Neural Network. In this paper, proposing a system for classification of Trajectories on Road Network using classifier Neural Netwo...

Earthquakes have often led to many damage points throughout the road-network in Japan and America. Therefore, mass travelers can’t be efficiently conducted via the post-quake road-network. Since the road-network is important to maintain the basic life and daily transit after disaster, it is very necessary to develop available reconstruction strategies for the broken road-network. To aid the rec...

The solutions used to solve bi-level congestion pricing problems are usually based on heuristic network optimization methods which may not be able to find the best solution for these type of problems. The application of meta-heuristic methods can be seen as viable alternative solutions but so far, it has not received enough attention by researchers in this field. Therefore, the objective of thi...

We study an important practical aspect of the route planning problem in real-world road networks – maneuvers. Informally, maneuvers represent various irregularities of the road network graph such as turnprohibitions, traffic light delays, round-abouts, forbidden passages and so on. We propose a generalized model which can handle arbitrarily complex (and even negative) maneuvers, and outline how...

This paper presents an automatic method for road network extraction from low-resolution images using hierarchical grouping. The method consists of three major steps: firstly it extracts lines from original images and generates smooth lines in a split-and-merge operation; a hierarchy of line images is generated using different thresholds for line length, based on the extracted line images; the l...

How does the development of one transport mode influence the development of another? This paper uses time-series data to test whether inter-model network externalities influenced the development of road, canal, and port infrastructure in England from 1760 to 1830. The main finding is that road development had a positive effect on canal development. The results suggest that the option value of w...

We study an important practical aspect of the route planning problem in real-world road networks – maneuvers. Informally, maneuvers represent various irregularities of the road network graph such as turnprohibitions, traffic light delays, round-abouts, forbidden passages and so on. We propose a generalized model which can handle arbitrarily complex (and even negative) maneuvers, and outline how...