Urban Navigation Handling Openstreetmap Data for an Easy to Drive Route

Atualmente, os cidadãos podem escolher as suas opções de viagem com base no tempo, distância, emissões, consumo, entre outros parâmetros. Não obstante, a literatura indica que os sistemas de planeamento de rotas atuais têm, maioritariamente, por base a distância e o tempo. Com efeito, verificou-se uma falta de sistemas de planeamento de rotas que se preocupem com as preferências dos utilizadores num ponto de vista mais qualitativo. Este projeto de investigação desenvolve um framework de planeamento de rotas com a integração de diferentes atributos da rede rodoviária como semáforos, passadeiras e paragens de autocarro, com o objetivo de providenciar aos utilizadores a opção de evitar estes mesmos atributos, oferecendo uma opção easy drive, nomeadamente em ambiente urbano. O estudo foi conduzido através de dados georreferenciados da cidade de Lisboa, Portugal. No entanto, é transferível para qualquer outra cidade. O algoritmo providencia alternativas para a rota mais curta, easy drive e rota balanceada, considerando apenas um modo de viagem: carro/mota. O modelo foi desenvolvido no PostgreSQL com a extensão PostGIS e PgRouting, e os resultados foram visualizados no software QGIS. O software permite customizar pesos para cada uma das restrições para a escolha das rotas e estes pesos são modificados com o objetivo de encontrar o caminho ótimo consoante as preferências de cada utilizador.Currently, citizens can choose their travel options based on time, distance, consumption, emission, among other parameters. Nevertheless, the literature indicates that current route planning systems are based on distance and time. In fact, there is a lack of route planning systems which are concerned with users' preferences from a more qualitative point of view. This research project develops a route planning framework with the integration of different road network features like traffic lights, pedestrian crossings, and bus stops, to provide users with the option to avoid these features, offering an easy drive option, namely in an urban environment. The study was conducted using georeferenced data from the city of Lisbon, Portugal. However, it is transferable to any other city. The algorithm provides alternatives for the shortest route, easy drive, and balanced route, considering only one travel mode: car/motorbike. The model was developed in PostgreSQL with the PostGIS extension and PgRouting, and the results were visualized in QGIS software. The software allows to custom weights for each of the constraints for route choices, and these weights are modified to find the optimal route according to the preferences of each user

Ergonomics of intelligent vehicle braking systems

The present thesis examines the quantitative characteristics of driver braking and pedal operation and discusses the implications for the design of braking support systems for vehicles. After the current status of the relevant research is presented through a literature review, three different methods are employed to examine driver braking microscopically, supplemented by a fourth method challenging the potential to apply the results in an adaptive brake assist system. First, thirty drivers drove an instrumented vehicle for a day each. Pedal inputs were constantly monitored through force, position sensors and a video camera. Results suggested a range of normal braking inputs in terms of brake-pedal force, initial brake-pedal displacement and throttle-release (throttle-off) rate. The inter-personal and intra-personal variability on the main variables was also prominent. [Continues.

Intelligent control and look-ahead energy management of hybrid electric vehicles

A review of the state of knowledge in the field of control and energy management in HEVs is carried out. The key innovation of the project is the development of a model of a PHEV using the real road data with an intelligent look-ahead online controller. Another novelty of this work is the method of route planning. It combines the information of vehicle sensors such as accelerometer and speedometer with the data of a GPS to create a road grade map for use within the look-ahead energy management strategy in the vehicle. For the PHEV, an adaptive cruise controller is modelled and an optimisation method is applied to obtain the best speed profile during a trajectory. Finally, the nonlinear model of the vehicle is applied with the sliding mode controller. The effect of using this controller is compared with the universal cruise controller. The stability of the system is studied and proved

Implementation and in-depth analyses of a battery-supercapacitor powered electric vehicle (E-Kancil)

This thesis contributes to the research issue pertaining to the management of multiple energy sources on-board a pure electric vehicle; particularly the energy dense traction battery and the power dense supercapacitor or ultracapacitor. This is achieved by analysing real world drive data on the interaction between lead acid battery pack and supercapacitor module connected in parallel while trying to fulfil the load demands of the vehicle. The initial findings and performance of a prototype electric vehicle conversion of a famous Malaysian city car; the perodual kancil, is presented in this thesis. The 660 cc compact city car engine was replaced with a brushless DC motor rated at 8KW continuous and 20KW peak. The battery pack consists of eight T105 Trojan 6V, 225 Ah deep cycle lead acid battery which builds up a voltage of 48V. In addition to this, a supercapacitor module (165F, 48V) is connected in parallel using high power contactors in order to investigate the increase in performance criteria such as acceleration, range, battery life etc. which have been proven in various literatures via simulation studies. A data acquisition system is setup in order to collect real world driving data from the electric vehicle on the fly along a fixed route. Analysis of collected driving data is done using MATLAB software and comparison of performance of the electric vehicle with and without supercapacitor module is made. Results show that with a parallel connection, battery life and health is enhanced by reduction in peak currents of up to 49%. Peak power capabilities of the entire hybrid source increased from 9.5KW to 12.5KW. A 41% increase in range per charge was recorded. The author of this work hopes that by capitalizing on the natural peak power buffering capabilities of the supercapacitor, a cost effective energy management system can be designed in order to utilize more than 23.6% of the supercapacitor energy

Implementation and in-depth analyses of a battery-supercapacitor powered electric vehicle (E-Kancil)

This thesis contributes to the research issue pertaining to the management of multiple energy sources on-board a pure electric vehicle; particularly the energy dense traction battery and the power dense supercapacitor or ultracapacitor. This is achieved by analysing real world drive data on the interaction between lead acid battery pack and supercapacitor module connected in parallel while trying to fulfil the load demands of the vehicle. The initial findings and performance of a prototype electric vehicle conversion of a famous Malaysian city car; the perodual kancil, is presented in this thesis. The 660 cc compact city car engine was replaced with a brushless DC motor rated at 8KW continuous and 20KW peak. The battery pack consists of eight T105 Trojan 6V, 225 Ah deep cycle lead acid battery which builds up a voltage of 48V. In addition to this, a supercapacitor module (165F, 48V) is connected in parallel using high power contactors in order to investigate the increase in performance criteria such as acceleration, range, battery life etc. which have been proven in various literatures via simulation studies. A data acquisition system is setup in order to collect real world driving data from the electric vehicle on the fly along a fixed route. Analysis of collected driving data is done using MATLAB software and comparison of performance of the electric vehicle with and without supercapacitor module is made. Results show that with a parallel connection, battery life and health is enhanced by reduction in peak currents of up to 49%. Peak power capabilities of the entire hybrid source increased from 9.5KW to 12.5KW. A 41% increase in range per charge was recorded. The author of this work hopes that by capitalizing on the natural peak power buffering capabilities of the supercapacitor, a cost effective energy management system can be designed in order to utilize more than 23.6% of the supercapacitor energy

Towards perceptual intelligence : statistical modeling of human individual and interactive behaviors

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Architecture, 2000.Includes bibliographical references (p. 279-297).This thesis presents a computational framework for the automatic recognition and prediction of different kinds of human behaviors from video cameras and other sensors, via perceptually intelligent systems that automatically sense and correctly classify human behaviors, by means of Machine Perception and Machine Learning techniques. In the thesis I develop the statistical machine learning algorithms (dynamic graphical models) necessary for detecting and recognizing individual and interactive behaviors. In the case of the interactions two Hidden Markov Models (HMMs) are coupled in a novel architecture called Coupled Hidden Markov Models (CHMMs) that explicitly captures the interactions between them. The algorithms for learning the parameters from data as well as for doing inference with those models are developed and described. Four systems that experimentally evaluate the proposed paradigm are presented: (1) LAFTER, an automatic face detection and tracking system with facial expression recognition; (2) a Tai-Chi gesture recognition system; (3) a pedestrian surveillance system that recognizes typical human to human interactions; (4) and a SmartCar for driver maneuver recognition. These systems capture human behaviors of different nature and increasing complexity: first, isolated, single-user facial expressions, then, two-hand gestures and human-to-human interactions, and finally complex behaviors where human performance is mediated by a machine, more specifically, a car. The metric that is used for quantifying the quality of the behavior models is their accuracy: how well they are able to recognize the behaviors on testing data. Statistical machine learning usually suffers from lack of data for estimating all the parameters in the models. In order to alleviate this problem, synthetically generated data are used to bootstrap the models creating 'prior models' that are further trained using much less real data than otherwise it would be required. The Bayesian nature of the approach let us do so. The predictive power of these models lets us categorize human actions very soon after the beginning of the action. Because of the generic nature of the typical behaviors of each of the implemented systems there is a reason to believe that this approach to modeling human behavior would generalize to other dynamic human-machine systems. This would allow us to recognize automatically people's intended action, and thus build control systems that dynamically adapt to suit the human's purposes better.by Nuria M. Oliver.Ph.D

Multi-Agent Systems

A multi-agent system (MAS) is a system composed of multiple interacting intelligent agents. Multi-agent systems can be used to solve problems which are difficult or impossible for an individual agent or monolithic system to solve. Agent systems are open and extensible systems that allow for the deployment of autonomous and proactive software components. Multi-agent systems have been brought up and used in several application domains