Road freight transport travel time estimation is an important task in fleet management and traffic planning. Goods often must be delivered in a predefined time window and any deviation may lead to serious consequences. It is possible to improve travel time estimation by considering more factors that may affect it. In this thesis work we identify factors that may affect travel time, find possible sources of information about them, propose a model for estimating travel time of heavy goods vehicles, and verify this model on real data. As results, the experiments showed that considering time related and weather related factors, it is possible to improve accuracy of travel time estimation. Also, it was shown that the influence of a particular factor on travel time depended on the considered road segment. Furthermore, it was shown that different data mining algorithms should be applied for different road segments in order to get the best estimation.

Congestion is a major problem in most metropolitan areas and given the increasingrate of urbanization it is likely to be an even more serious problem in the rapidlyexpanding mega cities. One possible method to combat congestion is to provide in-telligent traffic management systems that can in a timely manner inform drivers aboutcurrent or predicted traffic congestions that are relevant to them on their journeys. Thedetection of traffic congestion and the determination of whom to send in advance no-tifications about the detected congestions is the objective of the present research. Byadopting a grid based discretization of space, the proposed system extracts and main-tains traffic flow statistics and mobility statistics from the grid based recent trajectoriesof moving objects, and captures periodical spatio-temporal changes in the traffic flowsand movements by managing statistics for relevant temporal domain projections, i.e.,hour-of-day and day-of-week. Then, the proposed system identifies a directional con-gestion as a cell and its immediate neighbor, where the speed and flow of the objectsthat have moved from the neighbor to the cell significantly deviates from the histori-cal speed and flow statistics. Subsequently, based on one of two notification criteria,namely, Mobility Statistic Criterion (MSC) and Linear Movement Criterion (LMC),the system decides which objects are likely to be affected by the identified conges-tions and sends out notifications to the corresponding objects such that the numberof false negative (missed) and false positive (unnecessary) notifications is minimized.The thesis discusses the design and DBMS-based implementation of the proposedsystem. Empirical evaluations on realistically simulated trajectory data assess the ac-curacy of the methods and test the scalability of the system for varying input sizes andparameter settings. The accuracy assessment results show that the MSC based systemachieves an optimal performance with a true positive notification rate of 0.67 and afalse positive notification rate of 0.05 when min prob equals to 0.35, which is superiorto the performance of the LMC based system. The execution time of- and the spaceused by the system scales linearly with the input size (number of concurrently movingvehicles) and the methods mutually dependent parameters (grid resolution r and RTlength l) that jointly define a spatio-temporal resolution. Within the area of a large  city (40km by 40km), assuming a 60km/h average vehicle speed, the system, runningon a commodity personal computer, can manage the described congestion detectionand three-minute-ahead notification tasks within real-time requirements for 2000 and20000 concurrently moving vehicles for spatio-temporal resolutions (r=100m, l=19)and (r=2km, l=3), respectively.

Advanced Driver Assistance Systems (ADAS) and semi-autonomous driving systems are intended to enhance driver performance and improve transportation safety. The potential benefits of these technologies, such as reduction in number of crashes, enhancing driver comfort or convenience, decreasing environmental impact, etc., are well accepted and endorsed by transportation safety researchers and federal transportation agencies. Even though these systems afford safety advantages, they challenge the traditional role of drivers in operating vehicles. Driver acceptance, therefore, is essential for the implementation of ADAS and semi-autonomous driving systems into the transportation system. These technologies will not achieve their potential if drivers do not accept them and use them in a sustainable and appropriate manner. The potential benefits of these in-vehicle assistive systems presents a strong need for research. A comprehensive review of current literature on the definitions of acceptance, acceptance modelling approaches, and assessment techniques was carried out to explore and summarize the different approaches adopted by previous researchers. The review identified three major research needs: a comprehensive evaluation of general technology acceptance models in the context of ADAS, development of an acceptance model specifically for ADAS and similar technologies, and development of an acceptance assessment questionnaire. Two studies were conducted to address these needs. In the first study, data collection was done using two approaches: a driving simulator approach and an online survey approach. In both approaches, participants were exposed to an ADAS and, based on their experience, responded to several survey questions to indicate their attitude toward using the ADAS and their perception of its usefulness, usability, reliability, etc. The results of the first study showed the utility of the general technology acceptance theories to model driver acceptance. A Unified Model of Driver Acceptance (UMDA) and two versions (a long version with 21 items and a short version with 13 items) of an acceptance assessment questionnaire were also developed, based on the results of the first study. The second was conducted to validate the findings of first study. The results of the second study found statistical evidence validating UMDA and the two versions of the acceptance assessment questionnaire.

Traffic congestion is a constantly growing problem, with a wide array ofnegative effects on the society, from wasted time and productivity to elevated air pollution and increased number of accidents. Classical traffic control methods have long been successfully employed to alleviate congestion, improving the traffic situation of many cities and highways. However, traffic control is not universally employed, because of the necessity of installing additional equipment and instating new legislation.  The introduction of connected, autonomous vehicles offers new opportunities for sensing and controlling the traffic. The data that most of the vehicles nowadays provide are already widely used to measure the traffic conditions. It is natural to consider how vehicles could also be used as actuators, driving them in a specific way so that they affect the traffic positively. However, many of the currently considered strategies for congestion reduction using autonomous vehicles rely on having a high penetration rate, which is not likely to be the case in the near future. This raises the question: How can we influence the overall traffic by using only a small portion of vehicles that we have direct control over? There are two problems in particular that this thesis considers, congestion wave dissipation and avoidance, and platoon catch-up coordination. First, we study how to dissipate congestion waves by use of a directly controlled vehicle acting as a moving bottleneck. Traffic data can help predict disturbances and constraints that the vehicle will face, and the individual vehicles can be actuated to improve the overall traffic situation. We extend the classical cell transmission model to include the influence of a moving bottleneck, and then use this model to devise a control strategy for an actuator vehicle. By employing such control, we are able to homogenize the traffic without significantly reducing throughput. Under realistic conditions, it is shown that the average total variation of traffic density can be reduced over 5%, while the total travel time increases only 1%. Second, we study how to predict and control vehicles catching up in order to form a platoon, while driving in highway traffic. The influences of road grade and background traffic are examined and vehicles attempting to form a platoon are modelled as moving bottlenecks. Using this model, we are able to predict how much the vehicles might be delayed because of congestion and adjust the plan accordingly, calculating the optimal platoon catch-up speeds for the vehicles by minimizing their energy consumption. This leads to a reduction of energy cost of up to 0.5% compared to the case when we ignore the traffic conditions. More importantly, we are able to predict when attemptingto form a platoon will result in no energy savings, with approximately 80% accuracy. / Trafikstockning är ett ständigt växande problem, med ett brett utbud av negativa effekter på samhället, från bortkastad tid och produktivitet till ökade mängd luftföroreningar och antal olyckor. Klassiska metoder för trafik kontroll har länge använts framgångsrikt för att lindra detta problem, med förbättrad trafiksituation för många städer och motorvägar. Trafik kontrollen är emellertid inte universellt tillämpad eftersom den är beroende av ytterligare utrustning och ny lagstiftning som behover instaleras och införas. Införandet av uppkopplade, autonoma fordon medför nya möjligheter att mäta och kontrollera trafiken. Data som de flesta fordon tillhandahållar redan idag används allmänt för att mäta trafikförhållandena. Det är naturligt att överväga hur fordon också skulle kunna användas som ställdon, genom att driva dem på ett visst sätt så att de påverkar trafiken positivt. Men många av dagens strategierna för trängselnedsättning med hjälp av autonoma fordon är beroende av att de tillämpas av en stor del av fordonen, vilket sannoliktinte kommer att bli fallet inom en snar framtid. Det väcker frågan: Hur kan vi påverka den totala trafiksituationen genom att kontrollera en liten del avfordonen? Det finns två problem specifika problem som den här avhandlingentar hänsyn till, trängselvågsavledning och –undvikande samt koordinering av fordonståg av lastbilar. I det första problemet studerar vi hur vi kan skingra trängselvågor med hjälp av ett direktstyrt fordon som fungerar som en rörlig flaskhals. Trafikdatakan hjälpa till att förutsäga störningar och begränsningar som fordonet kommer att stöta på, och de enskilda fordonen kan styras för att förbättra den totala trafiksituation. Vi utvidgar den klassiska cellöverföringsmodellenför att inkludera påverkan av en rörlig flaskhals och använder sedan denna modell för att utforma en kontrollstrategi för ett styrbart fordon. Genom att använda sådan styrning kan vi homogenisera trafiken utan att avsevärt minska genomströmningen. Under realistiska förhållanden visar vi att den genomsnittliga totala variationen i trafiktäthet kan minskas med över 5%, medan den totala körtiden ökar med endast 1%. I det andra problemet studerar vi hur vi kan förutsäga och styra fordonens hastighetsprofiler vid formering av fordonståg under körning i motorvägstrafik. Påverkan av väglutning och motorvägstrafik undersöks, och fordon som försöker bilda en fordonståg modelleras som rörliga flaskhalsar. Med denna modell kan vi förutsäga förseningar på grund av trängsel och justera planen i enlighet med dessa, samt beräkna de optimala hastigheterna för fordonengenom att minimera energiförbrukningen. Detta leder till en minskning av energikostnaden på upp till 0,5% i jämförelse med fallet när vi ignorerar trafikförhållandena. Ännu viktigare är att vi kan vi förutsäga när försök att bildaett fordonståg kommer att resultera i utebliven energibesparing, med ungefär 80% noggrannhet. / <p>QC 20181212</p><p>The research leading to these results has received fundingfrom the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 674875, VINNOVA within the FFI program under contract 2014-06200, the Swedish Research Council, the Swedish Foundation for Strategic Research and Knut and Alice Wallenberg Foundation. The author is affiliated with the Wallenberg AI, Autonomous Systems and Software Program (WASP).</p>

No

A cidade de São Paulo é o município mais populoso do Brasil, caracterizado por uma segregação urbana responsável por inúmeros problemas relacionados a mobilidade urbana. As ações atuais para resolver os problemas de mobilidade urbana têm pouco aprofundamento em questões tecnológicas e melhorias dos sistemas computacio- nais existentes como as necessárias ao Sistema Integrado de Monitoramento e Transporte (SIM), utilizado para gestão e monitoramento do transporte público por ônibus de São Paulo. Uma das possíveis melhorias é integrar o SIM às Redes Sociais. Com essa perspectiva de integração, esse trabalho tem como objetivo uti- lizar tweets e dados do SIM na caracterização de eventos de exceção e de seus respectivos impactos no sistema de transporte público por ônibus da cidade de São Paulo. Para alcançar tal objetivo, esse trabalho propõe utilizar tweets publicados por instituições governamentais responsáveis por reportar eventos de exceção, dados dos módulos AVL (Automatic Vehicle Location) do SIM, responsáveis por rastrear e localizar os ônibus do município e GTFS (General Transit Feed Specification) da SPTrans. Visando alcançar o objetivo proposto, classificamos manualmente 60.984 tweets e treinamos diferentes modelos por meio de algoritmos de aprendizado de máquina supervisionado para identificar eventos de exceção. Além disso, propomos uma nova metodologia para extrair e geolocalizar os endereços dos eventos de exceção, por meio de Processamento de Língua Natural e Expressão Regular. Com isso, demonstramos que é possível correlacionar os dados desses eventos com os dados históricos do SIM e da GTFS, para caracterizar como o transporte público por ônibus da cidade de São Paulo é impactado nesses cenários. Adicionalmente, propomos uma arquitetura distribuída para exploração e visualização de grandes volumes de dados relacionados a transporte público / The city of São Paulo is the most populous municipality in Brazil, characterized by an urban segregation responsible for numerous problems related to urban mobility. The current actions to solve the problems of urban mobility have little deepening in technological issues and improvements of existing computer systems such as those required for the Integrated Monitoring and Transport System (in the Portuguese acronym: SIM), used for the management and monitoring of public transport by buses of the city of São Paulo. One of the possible improvements is integrating the SIM with Social Networks. With this perspective of integration, this work aims to use tweets and data from SIM in the characterization of exception events and their respective impacts on the public transport system by buses of the city of São Paulo. In order to achieve this objective, this work proposes to use tweets published by governmental institutions responsible for reporting exception events, data from SIM Automatic Vehicle Location (AVL) modules, responsible for the tracking and locating of urban buses and data from SPTrans GTFS (General Transit Feed Specification). In order to reach the proposed goal, we manually classified 60,984 tweets and trained different models through supervised machine learning algorithms to identify exception events. In addition, we propose a new methodology to extract and geolocalize the addresses of the exception events, through Natural Language Processing and Regular Expression. Using that approaches, we show that it is possible to correlate the data of these events with the historical data of the SIM and GTFS, to characterize how the public transport by bus of the city of São Paulo is impacted in these scenarios. Additionally, we propose a distributed architecture for exploration and visualization of large volumes of data related to public transport

Esta pesquisa traz à discussão a implantação de Sistemas Inteligentes de Transportes (ITS), em particular a funcionalidade Transit Signal Priority (TSP), ou Prioridade Semafórica, como uma solução a ser considerada para melhorar o desempenho de um corredor de ônibus. Os dados do Sistema Integrado de Monitoramento (SIM) foram empregados para identificar os locais com maior retardamento no Corredor Campo Limpo - Rebouças- Centro em São Paulo e, selecionado um trecho crítico, foi elaborada uma rede de microssimulação no software PTV - Vissim. A aplicação da prioridade semafórica foi feita através do VISVAP, controlador de lógica externo, no qual foram escritas as condicionantes de prioridade. O TSP foi simulado em quatro cenários distintos e, os resultados obtidos permitiram concluir que as expectativas verificadas no referencial teórico (por exemplo: aumento da velocidade média dos ônibus e automóveis), puderam ser comprovadas e, além disso, a prioridade semafórica condicional foi capaz de reduzir os retardos inclusive nas vias transversais não priorizadas. / This research brings to discussion the implementation of Intelligent Transportation Systems (ITS), particularly the Transit Signal Priority (TSP) feature as a solution to be considered to improve the performance of a bus corridor. Data from a Monitoring Integrated System (Sistema Integrado de Monitoramento - SIM) were used to identify most significant delay points at Campo Limpo - Rebouças- Centro Corridor in São Paulo and, after selected a critical stretch, it was developed a microsimulation with PTV Vissim software. The transit signal priority was made by VISVAP, external logic controller, in which were described the priority conditions. TSP was simulated in four different scenarios and, the obtained results have concluded that expectations examined in academic referencial (for example: increase in the average speed of buses and cars), could be confirmed, and, in addition, the transit signal priority was able to decrease delays in cross ways too (not prioritized).

Thesis on "Intelligent Transport Systems in the Czech Republic and their use" is focused on the analysis of intelligent transport systems, particularly for road transport in the Czech Republic. The aim of my work is to summarize the information and knowledge of ITS in the Czech Republic to introduce individual systems, their functions and to assess their contribution to road safety. Based on the evaluation of telematics systems used I suggest in the final part of the ITS elements in selected urban sprawl, particularly in the Czech Budejovice.

Esta pesquisa traz à discussão a implantação de Sistemas Inteligentes de Transportes (ITS), em particular a funcionalidade Transit Signal Priority (TSP), ou Prioridade Semafórica, como uma solução a ser considerada para melhorar o desempenho de um corredor de ônibus. Os dados do Sistema Integrado de Monitoramento (SIM) foram empregados para identificar os locais com maior retardamento no Corredor Campo Limpo - Rebouças- Centro em São Paulo e, selecionado um trecho crítico, foi elaborada uma rede de microssimulação no software PTV - Vissim. A aplicação da prioridade semafórica foi feita através do VISVAP, controlador de lógica externo, no qual foram escritas as condicionantes de prioridade. O TSP foi simulado em quatro cenários distintos e, os resultados obtidos permitiram concluir que as expectativas verificadas no referencial teórico (por exemplo: aumento da velocidade média dos ônibus e automóveis), puderam ser comprovadas e, além disso, a prioridade semafórica condicional foi capaz de reduzir os retardos inclusive nas vias transversais não priorizadas. / This research brings to discussion the implementation of Intelligent Transportation Systems (ITS), particularly the Transit Signal Priority (TSP) feature as a solution to be considered to improve the performance of a bus corridor. Data from a Monitoring Integrated System (Sistema Integrado de Monitoramento - SIM) were used to identify most significant delay points at Campo Limpo - Rebouças- Centro Corridor in São Paulo and, after selected a critical stretch, it was developed a microsimulation with PTV Vissim software. The transit signal priority was made by VISVAP, external logic controller, in which were described the priority conditions. TSP was simulated in four different scenarios and, the obtained results have concluded that expectations examined in academic referencial (for example: increase in the average speed of buses and cars), could be confirmed, and, in addition, the transit signal priority was able to decrease delays in cross ways too (not prioritized).

The main purpose of this thesis is to investigate potential synergies between an electronic waybill (e-Waybill) and other Intelligent Transport System (ITS) services. An e-Waybill service, as presented in this thesis, should be able to perform the functions of a paper waybill (which is an important transport document and contains essential information about a consignment) and it should contain at least the information specified in a paper waybill. To investigate synergies between the e-Waybill solutions and ITS services, we present 5 conceptual e-Waybill solutions that differ in where the e-Waybill information is stored, read, and written. These solutions are further investigated for functional and technical requirements (non-functional requirements), which can potentially impose constraints on a potential system that should implement the e-Waybill service. A set of 20 ITS services are considered for synergy analysis in this thesis. These services are mainly for road transport, however most of them are relevant to be considered for utilization in other modes of transport as well. For information synergy analysis, the e-Waybill solutions are assessed based on their synergies with ITS services. For different ITS services, the required input information entities are identified; and if at least one information entity can be provided by an e-Waybill at the right location we regard it to be a synergy. The result from our synergy analysis may support the choice of practical e-Waybill systems, which has the possibility to provide high synergy with ITS services. This may lead to a higher utilization of ITS services and more sustainable transport, e.g., in terms of reduced congestion and emissions. Additionally, a service design method has been proposed for supporting the process of designing new ITS services, which primarily utilizes on functional synergies with already existing ITS services. In order to illustrate the usage of the suggested method, we have applied it for designing a new ITS service, i.e., the Liability Intelligent Transport System (LITS) service. The purpose of the LITS service is to support the process of identifying when, where, and by whom a consignment has been damaged and who was responsible when the consignment was damaged.