TRAFFIC congestions and accidents are major concerns in today’s transportation systems. This thesis investigates how to improve traffic throughput by reducing or eliminating bottlenecks on highways, in particular for merging situations such as intersections where a ramp leads onto the highway. In our work, cars are equipped with sensors that can measure distance to neighboring cars, and communicate their velocity and acceleration readings with one another. Sensor-enabled cars can locally exchange sensed information about the traffic and adapt their behavior much earlier than regular cars. / We propose proactive algorithms for merging different streams of sensor-enabled cars into a single stream. A proactive merging algorithm decouples the decision point from the actual merging point. Sensor-enabled cars allow us to decide where and when a car merges before it arrives at the actual merging point. This leads to a significant improvement in traffic flow as velocities can be adjusted appropriately. We compare proactive merging algorithms against the conventional priority-based merging algorithm in a controlled simulation environment. Experimental results show that proactive merging algorithms outperform the priority-based merging algorithm in terms of flow and delay. / More importantly, the imprecise information (errors in sensor measurements) is a major challenge for merging algorithms, because inaccuracies can potentially lead to unsafe merging behaviors. In this thesis, we investigate how the accuracy of sensors impacts merging algorithms, and design robust merging algorithms that tolerate sensor errors. Experimental results show that one of our proposed merging algorithms, which is based on the theory of time geography, is able to guarantee safe merging while tolerating two to four times more imprecise positioning information, and can double the road capacity and increase the traffic flow by 25%.

TRAFFIC congestions and accidents are major concerns in today’s transportation systems. This thesis investigates how to improve traffic throughput by reducing or eliminating bottlenecks on highways, in particular for merging situations such as intersections where a ramp leads onto the highway. In our work, cars are equipped with sensors that can measure distance to neighboring cars, and communicate their velocity and acceleration readings with one another. Sensor-enabled cars can locally exchange sensed information about the traffic and adapt their behavior much earlier than regular cars. / We propose proactive algorithms for merging different streams of sensor-enabled cars into a single stream. A proactive merging algorithm decouples the decision point from the actual merging point. Sensor-enabled cars allow us to decide where and when a car merges before it arrives at the actual merging point. This leads to a significant improvement in traffic flow as velocities can be adjusted appropriately. We compare proactive merging algorithms against the conventional priority-based merging algorithm in a controlled simulation environment. Experimental results show that proactive merging algorithms outperform the priority-based merging algorithm in terms of flow and delay. / More importantly, the imprecise information (errors in sensor measurements) is a major challenge for merging algorithms, because inaccuracies can potentially lead to unsafe merging behaviors. In this thesis, we investigate how the accuracy of sensors impacts merging algorithms, and design robust merging algorithms that tolerate sensor errors. Experimental results show that one of our proposed merging algorithms, which is based on the theory of time geography, is able to guarantee safe merging while tolerating two to four times more imprecise positioning information, and can double the road capacity and increase the traffic flow by 25%.

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In freight transportation, a waybill is an important document that contains essential information about a consignment. The focus of this thesis is on a multi-purpose electronic waybill (e-Waybill) service, which can provide the functions of a paper waybill, and which is capable of storing, at least, the information present in a paper waybill. In addition, the service can be used to support other existing Intelligent Transportation System (ITS) services by utilizing on synergies with the existing services. Additionally, information entities from the e-Waybill service are investigated for the purpose of knowledge-building concerning freight flows. A systematic review on state-of-the-art of the e-Waybill service reveals several limitations, such as limited focus on supporting ITS services. Five different conceptual e-Waybill solutions (that can be seen as abstract system designs for implementing the e-Waybill service) are proposed. The solutions are investigated for functional and technical requirements (non-functional requirements), which can potentially impose constraints on a potential system for implementing the e-Waybill service. Further, the service is investigated for information and functional synergies with other ITS services. For information synergy analysis, the required input information entities for different ITS services 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. Additionally, a service design method has been proposed for supporting the process of designing new ITS services, which primarily utilizes on functional synergies between the e-Waybill and different existing ITS services. The suggested method is applied for designing a new ITS service, i.e., the Liability Intelligent Transport System (LITS) service. The purpose of the LITS service isto support the process of identifying when and where a consignment has been damaged and who was responsible when the damage occurred. Furthermore, information entities from e-Waybills are utilized for building improved knowledge concerning freight flows. A freight and route estimation method has been proposed for building improved knowledge, e.g., in national road administrations, on the movement of trucks and freight. The results from this thesis can be used to support the choice of practical e-Waybill service implementation, 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. Furthermore, the implemented e-Waybill service can be an enabler for collecting consignment and traffic data and converting the data into useful traffic information. In particular, the service can lead to increasing amounts of digitally stored data about consignments, which can lead to improved knowledge on the movement of freight and trucks. The knowledge may be helpful when making decisions concerning road taxes, fees, and infrastructure investments.

International Telemetering Conference Proceedings / October 26-29, 1998 / Town & Country Resort Hotel and Convention Center, San Diego, California / With the rapid development of intelligent transport system in the world during the past few years, it promotes some navigation & location technology to a wide application especially in the car application. This paper firstly introduces some kinds of navigation & location systems and then analyzes the advantage and disadvantage of each system. On the basis of integrating every system and considering the high accuracy which can be achieved by adopting the technology based on DGPS (Differential Global Position System) at present, vehicle navigation & location system based on DGPS/INS/GIS integrated technology is put forward. The propound of this system shortens the distance between academic plan and real application greatly, and it provides a high accuracy and high reliability navigation & location system for traffic department and some car manufacturing Inc. In addition, this system is also provided with a friendly interface that makes it very easy to the manipulator or the user. The emphasis of this paper is put on the hardware and software of this system through introducing the system performance, the system component and the system software, and the characteristic of each module that makes up the whole system. The propound of the vehicle navigation & location system based on DGPS/INS/GIS integrated technology is a new attempt for development of intelligent transport system in our country, it will be sure to accelerate the process of our intelligent transport system.

Thesis (MEng)--Stellenbosch University, 2015. / ENGLISH ABSTRACT: Road accidents are a growing concern for governments and is rising to become one of the leading causes of death in developing countries. Aggressive driving is one of the major causes of road accidents, and it is therefore important to investigate ways to improve people's driving habits. The ubiquitous presence of smartphones provides a new platform on which to implement sensor networks in vehicles, and therefore this thesis focuses on the use of smartphones to monitor a person's driving behaviour. The framework for a smartphone-based system that can detect and classify various driving manoeuvres is researched. As a proof of concept, a system is developed that specifically detects lateral driving manoeuvres and that classifies them as aggressive or not, using a supervised learning classification algorithm. Existing solutions found in research literature are investigated and presented. The best existing solution, a dynamic time warping classification approach, is also implemented and tested. We use an aggressive driving model that is based on the angle of a turn, the lateral force exerted on the vehicle and its speed through the turn. The tests and results of the implemented manoeuvre detection and classifcation algorithms are presented, and thoroughly discussed. The performance of each classifer is tested using the same data set, and a quantitative comparison are made between them. Ultimately, a lateral driving manoeuvre detection and recognition system was successfully developed, and its potential to be implemented on a smartphone was substantiated. The suitability of supervised learning classi ers for classifying aggressive driving, in comparison to dynamic time warping classifcation, was successfully demonstrated and used to validate our aggressive driving model. Conceivably, this work can be employed in the future to develop an holistic smartphone-based driver behaviour monitoring system, which can be easily deployed on a large scale to help make the public drive better. This would make our roads safer, reducing the occurrence of road accidents and fatalities. / AFRIKAANSE OPSOMMING: Padongelukkige is 'n groeiende bekommernis vir regerings en is een van die hoof oorsake van sterftes in ontwikkelende lande. Aggressiewe bestuur is een van die grootste oorsake van padongelukke, en dit is dus belangrik om ondersoek in te stel oor hoe mense se bestuurgewoontes verbeter kan word. Die alomteenwoordigheid van slimfone bied 'n nuwe platform waarop sensor netwerke geïmplementeer kan word in voertuie. Daarom fokus hierdie tesis op die gebruik van slimfone om 'n persoon se bestuurgedrag te moniteer. Die raamwerk vir 'n slimfoon-gebaseerde stelsel wat verskeie bestuurbewegings kan opspoor en klassifiseer is nagevors. As 'n bewys van die konsep, is 'n stelsel ontwikkel wat spesifiek laterale bestuurbewegings opspoor en dan klassifiseer of dit aggressief is of nie, met behulp van 'n klassifikasie algoritme wat onder toesig geleer is. Bestaande oplossings gevind in navorsingsliteratuur word ondersoek en aangebied. Die beste bestaande oplossing, 'n dinamiese tyd buiging klassifikasie benadering, word ook geïmplementeer en getoets. Ons gebruik 'n aggressiewe bestuurmodel wat gebaseer is op die hoek van 'n draai, die laterale krag wat uitgeofen is op die voertuig en sy spoed deur die draai. Die toetse en die resultate van die geïmplementeer beweging opsporing en klassifisering algoritmes word aangebied, en deeglik bespreek. Die prestasie van elke klassifiseerder is getoets met behulp van dieselfde stel data, en 'n kwantitatiewe vergelyking is tussen beide gemaak. Oplaas is 'n laterale bestuurbeweging bemerking en herkenning stelsel suksesvol ontwikkel en sy potensiaal om geïmplementeer te word op 'n slimfoon is gestaaf. Die geskiktheid van die onder-toesig-geleerde klassifiseerders vir die klassifikasie van aggressiewe bestuur, in vergelyking met dinamiese tyd buiging klassifikasie, was suksesvol gedemonstreer en gebruik om ons aggressiewe bestuurmodel te bewys. Hierdie werk kan in die toekoms gebruik word in 'n holistiese slimfoon-gebaseerde bestuurdergedrag monitering stelsel, wat maklik op groot skaal ontplooi kan word om te help verseker dat die publiek beter bestuur. Dit sal ons paaie veiliger maak, en die voorkoms van padongelukke en sterftes verminder.

This thesis will research and evaluate the state of the current ETSI VAM standard. The thesis evaluates and discusses the means of improving the speed and response of ETSI VAM by reducing the load on the radio medium. The research looks to prove that fewer messages broadcasted improve VRU awareness. The thesis focuses mainly on the benefits of VRU clustering as a means of reducing radio medium load through numerical evaluation and physical implementation testing. Evaluation of basic and alternate cluster parameters is performed to find the most optimal ones; alternate clustering strategies are also discussed and proposed. The thesis aims to improve the standard by finding and evaluating alternate methods and parameters in order to propose improved options. / Projektet utvärderar och diskuterar sätten att förbättra hastigheten och responsen hos ETSI VAM genom att minska belastningen på radiomediet. Forskningen syftar till att bevisa att färre meddelanden som sänds förbättrar systemets VRU-medvetenhet. Fokuset ligger huvudsakligen på att utvärdera fördelarna med "VRU-klustring" som ett sätt att minska radiomediebelastningen genom numerisk utvärdering och fysisk testning. Utvärdering av grundläggande och alternativa klusterparametrar utförs för att hitta de mest optimala; alternativa klustringsstrategier diskuteras och föreslås också. Projektet syftar till att förbättra standarden genom att hitta och utvärdera alternativa metoder och parametrar för att föreslå förbättrade alternativ.

International Telemetering Conference Proceedings / October 25-28, 1999 / Riviera Hotel and Convention Center, Las Vegas, Nevada / With the rapid development of urban economy, there are bus increasing, route extending, and shuttle frequency increasing etc. At the same time, road construction is subject to land surface, so traffic jam often occurs. It is a big trouble for life of citizens and problem for economy development. So it needs to be improved as fast as possible. Vehicle monitoring system for public traffic in Beijing can expediently monitor the state of each controlled bus, thereby making perfect management. With the integration of GPS, analog trunked communication and digital map, the old, blinding manage system of public traffic would be changed into advanced, visualized management mode, and several routes are dispatched in one dispatch center at the same time. The system frame and its components are introduced in this paper.

This thesis is concerned with the problem of situational awareness in autonomous vehicles. In this context, situational awareness refers to the ability of an autonomous vehicle to perceive the road layout ahead, interpret the implied semantics and gain an awareness of its surrounding - thus reading the road ahead. Autonomous vehicles require a high level of situational awareness in order to operate safely and efficiently in real-world dynamic environments. A system is therefore needed that is able to model the expected road layout in terms of semantics, both under normal and roadwork conditions. This thesis takes a three-pronged approach to this problem: Firstly, we consider reading the road surface. This is formulated in terms of probabilistic road marking classification and interpretation. We then derive the road boundaries using only a 2D laser and algorithms based on geometric priors from Highway Traffic Engineering principles. Secondly, we consider reading the road scene. Here, we formulate a roadwork scene recognition framework based on opponent colour vision in humans. Finally, we provide a data representation for situational awareness that unifies reading the road surface and reading the road scene. This thesis therefore frames situational awareness in autonomous vehicles in terms of both static and dynamic road semantics - and detailed formulations and algorithms are discussed. We test our algorithms on several benchmarking datasets collected using our autonomous vehicle on both rural and urban roads. The results illustrate that our road boundary estimation, road marking classification, and roadwork scene recognition frameworks allow autonomous vehicles to truly and meaningfully read the semantics of the road ahead, thus gaining a valuable sense of situational awareness even at challenging layouts, roadwork sites, and along unknown roadways.