Commerce companies have experienced a rise in the number of parcels that need to be delivered each day. The goal of this study is to provide a decision-making procedure to assist carriers in taking a more significant role in selecting cost and risk-efficient truck-drone intermodal delivery routing plan. The congestion-based model is developed to select the method of parcel delivery utilizing a truck and a drone for optimizing cost and time. A study also has been conducted to compare drone-only and truck-only delivery routing plan. The proposed A* Heuristic algorithm and the OSRM application generate the travel path for drone and a truck along with the time of travel. Case studies have been conducted by varying the weight provided to cost and risk variable, studies indicate that there is a significant change in drone delivery travel time and cost with increase of cost weightage.

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>

This research effort is motivated by the need to quickly obtain origin-destination (0-0) trip information for an urban area, without expending the excessive time and effort usually accompanying survey-based methods. The intent is to utilize this information to facilitate diversion of traffic in real time, in the event of congestion-causing incidents such as accidents. The O-D trip table information is a key to successful diversion planning, where user destinations are considered in developing the plans. Traffic volumes on the links of the road network contain information which can be exploited advantageously to derive the trip patterns. This approach of synthesizing a trip table from link volumes, and perhaps using a prior trip table to guide the derivation, has useful applications in the context of diversion planning. Unlike conventional O-D surveys, it has the potential of yielding results quickly, a requisite for real-time applications. This research work details a new methodology for synthesizing origin-destination (0-0) trip tables. The approach, which is based on a non-proportional assignment, user-equilibrium motivated, linear programming model, is the principal component of this dissertation. The model is designed to determine a traffic equilibrium network flow solution which reproduces the link volume data, if such a solution exists. If such alternate solutions exist, then it is designed to find that which most closely resembles a specified target trip table. However. it recognizes that due to incomplete information, the traffic may not conform to an equilibrium flow pattern, and moreover, there might be inconsistencies in the observed link flow data, or there might be incomplete information. Accordingly, the model permits violations in the equilibrium conditions as well as deviations from the observed link flows, but at suitable incurred penalties in the objective function. A column generation solution technique is presented to optimally solve the problem. The methodology also accommodates a specified prior target trip table, and drives the solution toward a tendency to match this table using user controlled parameters. Implementation strategies are discussed, and an illustration of the proposed method is presented using some sample test networks. The results from the model are discussed vis-a-vis other relevant, available approaches. The quality of the results and the computational effort required are used as a set of criteria in the comparisons. The comparisons of test results demonstrate the superiority of the linear programming model over the other models considered. The model is also applied to a real network of Northern Virginia, where congestion problems present a serious concern. As a result of this experience, several implementation strategies relevant to the application of the model on a real network are presented, and some general conclusions are derived. The potential application of the model in real-time traffic diversion planning for the study area is discussed. Recommendations for further research are also presented. / Ph. D.

The motivation behind this research is the need for a real-time implementable, yet accurate, procedure for estimating an origin-destination (O-D) trip-table based on entering and exiting traffic volume data for a given freeway section. These tables help in on-line control of traffic facilities, and consequently, are of significant use in alleviating traffic congestion. The dynamism of the approach captures the variations in the traffic counts with time which are in tum used to predict user travel patterns. Two models have been developed for this problem, one based on a least squares estimation and the other based on an <i>1</i>₁ norm approach. Two projected conjugate gradient schemes are investigated for solving the constrained least squares problem, and an interior point affine scaling algorithm that is applied to the dual problem is explored for solving the <i>1</i>₁ estimation linear programming problem. Computational results are presented on a set of test problems involving the determination of O-D trip tables for both intersection and freeway scenarios in order to demonstrate the viability of the proposed methods. These results exhibit that, unlike as reported in the literature based on previous efforts, properly designed parameter optimization methods can indeed provide accurate estimates in a realtime implementation. Hence, this research presents a competitive alternative to the iterative statistical techniques that have been heretofore used because of their real-time processing capabilities, despite their inherent inaccuracies. We hope that the proposed technology enhances existing methods for constructing O-D trip-tables from traffic counts. / Master of Science

An impressive population growth and a rapidly expanding motor vehicle fleet have resulted in the "strangulation" of the city of Athens. Smog, traffic congestion, parking shortages, noise and excessive delays are everyday problems for the Athenians. The street network and the public transportation systems are not able to accommodate the existing traffic demands. An effort was made to address the transportation needs, that require an immediate solution, in the central Athens area. Traffic counts and physical characteristics were obtained for the street network of the central city. A traffic simulation model, MASSVAC2, was employed for simulating existing traffic conditions during the noon peak period, assessing the quality of operations, identifying street deficiencies and testing and evaluating different traffic management strategies for the central city of Athens. The need for the establishment of a comprehensive transportation plan, which consists of traffic management policies, traffic restraints, public transport improvements, and construction of a rail rapid transit system and a freeway-expressway system, was particularly stressed. The essential for effective coordination between agencies related to transportation management was also emphasized, for the alleviation of traffic congestion in the central area and the increase in the overall transport efficiency in the city of Athens. / Master of Science

With the economic growth, the number of motor vehicles has increased rapidly for the last decades, especially in developing countries like China and India. Availability of more vehicles makes it more convenient for people to travel and merchandise transport. The increase of the number of vehicles also brings stresses to public traffic and pollution to the environment. When the number of vehicles on the road is over the available space, it results in traffic congestion. The problem is being studied and there are several solutions to it, like building more roads, rebuilding the existing streets and enlarging the cities. Based on the traffic reason and the environment reason, the government and the institute of environmental protection appeal to the public to take public transport means instead of private cars. But the measure affects the utilization ofmotor vehicles. Global Positioning System (GPS) provides autonomous geo-spatial positioningand navigation service. Once the user enters the destination, the navigation service will show the shortest path from the location of the user to the destination. Following the guide makes the vehicles running purposively, and it is also favorable for traffic control and management. Theoretically, if the diver keeps the same driving mode, the shortest path will cost the shortest time, but in reality, the traffic environment is complex and the driving speed is variable thus the shortest path is probably not the fastest path. In this study, the hinder factors of the speed and traffic are fixed constructions on the road, like: turnings, hospitals, schools, residential areas, traffic lights and the user-controlled factor (sites of traffic jams, accidents, and temporary construction on the road). We take the hinderfactors of traffic and driving speed into consideration while providing the route plan, finding the shortest-time path, and showing the result as an online map via the web Geographic Information System (GIS) application. We show that reducing the travelling time of motor vehicles, makes the traffic flow more rapid and efficient. Alsoreducing the emission time of motor vehicles, diminishes the greenhouse effect. Beside these, the achievement of our study also shows that the public can take advantage of open source tools and data to build their GIS application to do spatial and data analysis.

Traffic congestion can cause late deliveries, decreased profits from vehicle fuel idling in traffic, and delayed distribution in tight delivery windows. The focus of this study was on developing strategies that business leaders could use to increase on-time deliveries. The conceptual frameworks for this case study were systems theory, traffic equilibrium theory, bathtub theory, and kinematic wave theory. Data were collected from semistructured interviews with 6 delivery service leaders from 3 delivery businesses in Southcentral Alaska. In addition, secondary data were collected from government information. Interview responses were coded to identify trends including delivery time, business activity, and amount of roadway congestion. Two major themes emerged from the interviews: time of day affecting when traffic congestion occurred, and limited alternate transportation routes causing congestion in Southcentral Alaska. The findings indicated that the best strategy to help reduce traffic congestion involved instituting toll optimization and high occupant vehicles lanes. The implications for effecting social change include how business leaders can help reduce traffic congestion using toll optimization, and how high occupant vehicle lanes could encourage Southcentral Alaskans to carpool.

Traffic congestion is one of the most concerning issues in the transportation system. Recurrent congestion and non-recurrent congestion are explored in this research. This research will investigate one of the most concerning issues with the transportation system, congestion, using an overall delay analysis study. A developed fused database program was used to access and analyze the complete database data. Two online databases were used for obtaining traffic, incident and weather data. Eleven different scenarios such as peak-hours, rain scenario, incidents scenario, and work zone scenario were developed for the analysis. An overall delay study was performed on all scenarios to find the impact recurring and non-recurring congestion on the highway. The results of this research were interesting for future adjustment and improvements on the two segments of highways selected. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2014. / FAU Electronic Theses and Dissertations Collection

The road traffic along with other key infrastructure sectors such as telecommunication, power, etc. has an important role in economic and technological growth of one country. Traffic engineers and analysts are responsible for solving a diversity of traffic problems, such as traffic data acquisition and evaluation. In response to the need to improve traffic operation, researchers implement advanced technologies and integration of systems and data, and develop state-of-the-art applications. This thesis introduces three novel web applications with an aim to offer traffic operators, managers, and analysts’ possibility to monitor the congestion, and analyze incidents and signal performance measures. They offer more detailed analysis providing users with insights from different levels and perspectives. The benefit of providing these visualization tools is more efficient estimation of the performance of local networks, thus facilitating the decision making process in case of emergency events. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2015 / FAU Electronic Theses and Dissertations Collection

Our cities have been continually growing at an uncontrolled rate leading to the problem of trafficcongestion, which has discernable effects on all the aspects of sustainability, be it social,environmental or economical. This continual shift of increasing size of centre and decreasingsize of periphery poses huge sustainability challenge of meeting the consumption demands. Wepresently face the most unprecedented times in terms of the pace at which our natural resourcesare getting consumed. It is clear that replenishing some of these resources is totally out ofquestion. On the other side of the coin, the advances of human technology have provided itsgreatest gift of information &amp; communication technology (ICT). Today we have access to datafrom any point of the world to anywhere. There is a growing need to use this data andinformation with a holistic view to build more Intelligent Transport Systems. In our paper wediscuss how the advent of ICT can have an impact on bringing a sustainable transportationsystem. The work is divided in two folds, by first understanding the direct role of ICT intransport sustainability and then observing the direct correlation between usage of ICT andtravel demand. The problems of traffic congestion and its solutions like congestion pricing haveexisted in practice since ages; the perspective which we add to it is the role of ICT in making itbetter. The greater perspective that is being researched here is at an absolute fundamental leveland takes us to the question if and how ICT can work on root level challenges, like findingmethods to have a better traceability without compromising on privacy, changing driverbehaviour patterns and stopping the expansion of centre &amp; contraction of periphery.