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In this paper, an Artificial Neural Network (ANN) is employed for the estimation of LaTeral Misalignment (LTM) as well as compensation of its effect on Dynamic Wireless Power Transfer (DWPT) systems for Electric Vehicles (EVs) charging. In a DWPT system, energy efficiency and energy transfer capability are significantly affected by the degree of LTM. Therefore, the real-time estimation of LTM, followed...
In this paper an integrated feed-forward lateral dynamics controller, which considers the actuator dynamics and input delays, is presented. The proposed approach uses an optimization based model inversion of a nonlinear two-track model with magic formula tire model to describe the vehicle dynamics. The model is extended by the actuator models containing delays, which are identified with measurement...
Electric vehicles (EVs) play a significant role in the current transportation systems. The main factor that affects the acceptance of existing EV models is the range anxiety problem caused by limited charging stations and long recharge times. Recently, the solar-powered EV has drawn many attentions due to being free of charging limitations. However, the solarpowered EVs may still struggle with the...
The increase in population has increased congestion in traffic which has caused the users to take different routes between the same source and destination. Personalized route prediction system provides routes based on the user requirements, also the intent of the user to take a specific route. The user may prefer a long route with less congestion over a short route with more congestion. The route...
in recent decades, vehicle manufacturers and system suppliers equipping these vehicles have made considerable efforts to improve their technology and road safety. One of the major advances is the introduction of advanced systems for driver assistance. These assistance systems ensure continuous monitoring of the environment of the vehicle and driving mode, so early detection of potentially hazardous...
Knowledge about the driving behavior of a driver is important for applications in many different areas, especially for Advanced Driver Assistance Systems. The driving style does not only affect the current driver and his vehicle but also his environment. For example, usage-based insurances classify the driving style in order to reward calm drivers by granting them a discount. In this paper we present...
Taxi-ridesharing has significant benefits e.g. it reduces pollution as number of taxis on road are less, the cost to riders is low, the driver to make more profit. The general idea of Taxi-ridesharing is that drivers and riders use mobile phones connected to a web service to arrange rides. In this paper we propose a taxi-ridesharing service that reduces the total travelling distance per taxi and travelling...
Personal route prediction (PRP) has attracted much research interest recently because of its technical challenges and broad applications in intelligent vehicle and transportation systems. Traditional navigation systems generate a route for a given origin and destination based on either shortest or fastest route schemes. In practice, different people may very likely take different routes from the same...
The two-dimensional vehicle routing problem (2L-VRP) is a realistic extension of the classical vehicle routing problem where customers' demands are composed by sets of non-stackable items. Examples of such problems can be found in many real-life applications, e.g. furniture or industrial machinery transportation. Often, these real-life instances have to deal with uncertainty in many aspects of the...
Sustainable mobility is not merely a technological question. While automotive technology will be part of the solution, it will also be combined with a paradigm shift from car ownership to vehicle usage, which itself will be facilitated by the application of Information and Communication Technologies that make it possible for a user to have access to a mobility service from anywhere to anywhere at...
This paper presents an optimization approach which integrates Monte Carlo simulation (MCS) within a heuristic algorithm in order to deal with a rich and real-life vehicle routing problem. A set of customers' orders must be delivered from different depots and using a heterogeneous fleet of vehicles. Also, since the capacity of the firm's depots is limited, some vehicles might need to be replenished...
The goal of this work is to enable a team of quadrotors to learn how to accurately track a desired trajectory while holding a given formation. We solve this problem in a distributed manner, where each vehicle has only access to the information of its neighbors. The desired trajectory is only available to one (or few) vehicles. We present a distributed iterative learning control (ILC) approach where...
To satisfy specific real-life demand of freight transportation carriers, this paper proposes an arc-based formulation for service network design with time requirements to schedule heterogeneous fleet. The computational study indicates the validity of the formulation both academically and practically. The results shows that heterogeneous fleet is essential to tactical planning for increasing the loading...
In hybrid vehicular ad hoc networks (VANETs), content data can be downloaded either from 3G/4G cellular networks or from roadside units (RSUs) of VANETs. When downloading via cellular networks, the delay is low but the cost is expensive. While, downloading via VANETs, the cost is nearly free. However, due to the unique characteristics of VANETs, such as frequent disruptions, high speed mobility and...
Autonomous driving in urban environments depends on the ability to interpret the current situation and to react accordingly. This means to continuously make decisions for certain comfort-optimized maneuvers under the constraints of traffic rules and feasibility. This work presents a novel, longitudinal driving strategy formulated as a discrete planning problem. Instead of designing an algorithm for...
The aim of this work is the implementation of an intelligent system based ant colony algorithm to control a traffic signal intersection where the main goal is to reduce the average waiting time of the vehicles at the intersection. First a dynamic mathematical model of the flow at an intersection is given. Second, the intelligent system is implemented electronically around an Arduino microcontroller...
The management of pre hospital logistics is addressed by several researchers. That is due to the big impact that has healthcare around the city development. Thus, optimizing emergency traffic helps to smart cities growth. This paper includes coverage problems existing in literature and addresses the ambulance allocation to cover sectors in Casablanca region of Morocco and minimize the lateness of...
Ground-breaking innovations in transport, such as autonomous vehicles, the European Local Dynamic Map (LDM) and related on-line services heavily depend on reliable vehicular connectivity. In the most likely scenario, hybrid vehicular networks will use the IEEE 802.11p protocol for vehicle-to-vehicle (V2V) communication, and the cellular network (e.g. LTE or 5G) as a gateway to remote servers. Both...
Minimum Latency Problem (MLP) is a class of NP-hard combinatorial optimization problems which has many practical applications. In this paper, a general variant of MLP, also known as k-MLP is introduced. In k — MLP problem, the cost of objective function becomes the sum of waiting times at sites and k vehicles cover one of k routes. The goal is to find the order of customer visits that minimizes the...
The Cooperative Adaptive Cruise Control (CACC) is one of the most promising aiding systems to improve traffic flow in highways. When it comes to design a proper control algorithm, robustness against non-modeled dynamics and noise plays a key role not only for improving controller performance but also for increasing the ability of handling heterogeneous vehicle strings. This paper proposes a fractional...
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