Eco-driving has acquired great importance in recent years because it is a way to reduce energy consumption that can be applied to any type of vehicle. However, for these rules to be applied requires a process of continuous learning and motivation. For this reason many eco-driving assistants have emerged. This paper presents Green Driving, a driver safety app for Android that detects inattentive driving behaviors and gives corresponding feedback to drivers, scoring their driving and alerting them in case their behaviors are unsafe.  It’s about changing a person’s driving behavior by providing some kind of advice to the driver.  I have worked on an algorithm that is meant to reduce the fuel consumption of users. The algorithm is deployed in an android application. This application “Green Driving” is aimed at users with cars. It is basically like an assistant, suggesting the user when he should make the right gear changes, when to increase/decrease speed and avoids hard braking and rapid acceleration and etc. It is in order to drive economically, ecologic and in turn save money and safety. This is a smart way of letting a user drive economically and ecologic since almost everyone has an Android smartphone now.

Diverging diamond interchanges (DDI) have been proved to outperform other types of diamond interchanges in terms of safety, cost-effectiveness and efficiency, but few research efforts have been done to conduct the analytic calculation of delay, with which optimization of timing plans can be acquired more efficiently. This paper develops the control strategies based on the introduction of overlap and offset analysis, which provide a uniform representation of sequences for DDI signal control. Based on the developed timing plan then the delay calculation equations are put forward and results show the calculation fit simulation very well with R-Square to be 0.9949 for total delay of those two directions. Ecodriving aims to achieve the best fuel efficiency by guiding vehicles travel at planned and optimized speed trajectories. This study opens the door for safety concerns for following normal driving vehicles (FNVs) when following ecodriving vehicles (EVs). To examine the safety issues under different circumstance. Three road elements: initial signal status, ambient vehicles and speed limit along with three EV elements: SpeedTolimit, DistanceToStoplight and acceleration were chosen as potential influential elements, and time to collision (TTC) was selected as the dependent variable. Therefore, six testing scenarios and six baseline were designed and implemented using a drive safety DNS-250 simulator. 29 drivers participated in the driving simulator study. The results show the aforementioned road elements and EV elements have significant influence on TTC of FNV in different testing parts. Therefore, these finding can be used as guidance for future ecodriving algorithm design and implementation. / Master of Science

Det finns ekonomiska, säkerhetsmässiga och miljömässiga vinster att göra genom att tillämpa ecodriving. Tidigare forskning pekar på att transportslagen bilar, tåg och flyg har gjort stora besparingar i ekonomiskt och miljömässigt hänseende, men hur ser det ut inom sjöfarten? Med denna frågeställning som bakgrund är syftet med studien att studera intresset för ecodriving bland svenska rederier och svenska myndigheter med en fartygsflotta. Dataunderlaget för studien utgörs av material från kvalitativa intervjuer med personer i exekutiv position. Resultatet av studien visar på att de flesta verksamheterna står i startgroparna eller redan arbetar utifrån en eller flera aktivt valda metoder för ecodriving. Resultatet visar också att det finns en blandning av förutsättningar och uppfattningar om vad ecodriving är och vad det kan bli inom sjöfarten. När frågor om automatisering i samband med ecodriving behandlas är resultatet tvetydigt. / There are economical, safetylike and environmental benefits of applying eco-driving. Previous research has shown that cars, trains and aviation have made significant savings economically and environmentaly speaking, but how does that transcend into the maritime business? With this question as a background, the aim with this thesis is to examine the interest of ecodriving among Swedish shipowners and authorities. The data in this thesis is derived from qualitative interviews with employees in executive land-based positions. The result shows that several of the shipowners and authorities are in the starting pits or are already conducting one or more eco-driving methods in their operations. The result also shows that there is a variety of prerequisites and perceptions of what eco-driving is and what is could become in the future among the respondents. When questions about automatization in relation to eco-driving are brought up, the result is ambiguous.

Energy consumption reduction is one of the priorities of metro operators, due to financial cost and environmental impact. The new signalling system Communications-Based Train Control (CBTC) is being installed in new and upgraded metro lines to increase transportation capacity. But its continuous communication feature also permits to improve the energy performance of traffic operation, by updating the control command of the Automatic Train Operation (ATO) system at any point of the route. The present research addresses two main topics. The first is the design of efficient CBTC speed profiles for undisturbed train trajectory between two stations. The second takes into account the interaction between two consecutive trains under abnormal traffic conditions and proposes a tracking algorithm to save energy. In the first part of the research an off-line methodology to design optimal speed profiles for CBTC-ATO controlled trains is proposed. The methodology is based on a new multi-objective optimisation algorithm named NSGA-II-F, which is used to design speed profiles in such a way that can cover all the possible efficient solutions in a pseudo-Pareto front. The pseudo–Pareto front is built by using dominated solutions to make available a complete set of feasible situations in a driving scenario. The uncertainty in the passenger load is modelled as a fuzzy parameter. Each of the resulting speed profiles is obtained as a set of parameters that can be sent to the ATO equipment to perform the driving during the operation. The proposed optimisation algorithm makes use of detailed simulation of the train motion. Therefore, a simulator of the train motion has been developed, including detailed model of the specific ATO equipment, the ATP constraints, the traction equipment, the train dynamics and the track. A subsequent analysis considers the effect in the design of considering the regenerative energy flow between the train and the surrounding railway system. The second part of the research is focused on the proposal and validation of a fuzzy tracking algorithm for controlling the motion of two consecutive trains during disturbed conditions. A disturbed condition is understood as a change in the nominal driving command of a leading train and its consequences in the subsequent trains. When a train runs close enough to the preceding one, a tracking algorithm is triggered to control the distance between both trains. The following train receives the LMA (limit of movement authority) via radio, which is updated periodically as the preceding train runs. The aim of the proposed algorithm is to take actions in such a way that the following train could track the leading train meeting the safety requirements and applying an energy saving driving technique (coasting command). The uncertainty in the variations of the speed of the preceding train is modelled as a fuzzy quantity. The proposed algorithm is based on the application of coasting commands when possible, substituting traction/braking cycles by traction/coasting cycles, and hence saving energy. Both algorithms were tested and validated by using a detailed simulation program. The NSGA-II-F algorithm provided additional energy savings when compared to fixed block distance-to-go configurations, and giving a more even distribution of the solutions. The fuzzy tracking algorithm provides energy savings with a minor impact on running times while improving comfort, because of the reduction of the inefficient traction/braking cycles. / <p>QC 20170216</p>

Under 1980-talet introducerades den första tågsimulatorn i svensk lokförarutbildning. Denna simulator är fortfarande den enda fullskalesimulator som används för att utbilda lokförare i Sverige. En anledning till att det inte finns fler tycks vara att det bl.a. saknas pedagogiska och ekonomiska motiv för en utvidgad användning av simulatorer i undervisning och träning. Energibesparingar inom spårtrafik dvs. att köra tåg energieffektivt är idag mycket aktuellt hos alla tågoperatörer i Sverige. Vissa operatörer utbildar redan sina förare teoretiskt i energieffektiv körning och tester av energieffektiv körning i verklig trafik har visat på en möjlig besparing om 16 % energi efter det att lokförare genomgått en teoretisk utbildning i energieffektiv körning. Då det emellertid fanns en del osäkerhet i mätdata från de tester som genomförts i verklig trafik och betingelserna samt försöksprocedur varierade mellan förarna fanns det ett behov av att undersöka besparingspotentialen under mer kontrollerade former. Dessutom visade sig att utbildning samt tillgång till ett stödsystem under körning gav en mindre besparing i energi (13 %). Således genomfördes en studie med hjälp av en tågsimulator. I simulatorn har man full kontroll på mätdata och betingelserna är lika för alla förare. Simulatorn som användes i studien är utvecklad på VTI (Statens väg- och transportforskningsinstitut) och är modellerad efter en X50 Regina. Syftet med denna studie var således att undersöka om samma teoretiska utbildning i energieffektiv körning, i kombination med simulatorträning under ideala förhållanden skulle ge lika bra eller bättre energibesparing jämfört med resultaten från tester i verklig trafik. Vidare undersöktes effekten av återkoppling under träningen med avseende på energibesparing. I studien deltog 24 lokförarelever som delades in i tre grupper med 8 elever i varje. Två av grupperna fick genomföra två körningar (referens- och testkörning) med utbildning och simulatorträning mellan tillfällena, medan den tredje gruppen (kontrollgrupp) endast genomförde referens- och testkörning utan utbildning och träning. De två grupperna som fick utbildning fick dock träna under två olika betingelser, en med återkoppling (energiförbrukning och banlutning) och en utan återkoppling. Det visade sig att utbildning i energieffektiv körning i kombination med 30 minuters simulatorträning resulterade i en total besparing för båda grupperna på ungefär 24 % energi, om man sen tar hänsyn till att man förbättrar sin körning genom att bara få tillfälle att köra upprepade gånger (kontrollgruppen använde 8 % mindre energi andra gången) så visade det sig att besparingen blev lika stor som den man fann i verklig trafik (16 %). Då resultaten blev lika fast betingelserna var olika finns det anledning till att vidare undersöka hur olika körförhållanden påverkar utfallet. Dessutom behöver man bättre förstå varför utbildning plus stödsystem gav mindre effekt än bara utbildning i verklig trafik samt varför återkoppling under träning inte gav någon påvisbar effekt. Det vill säga det finns anledning till ytterligare insatser för att utforma träning och stödsystem till förarna. Förutom energibesparing visade resultatet att rättidigheten förbättrades efter utbildning och simulatorträning. Resultaten talar för att det finns outnyttjad potential för tågsimulatorer i den svenska lokförarutbildningen både för att träna och utvärdera effekter av utbildningsinsatser. / During the 80’s, the first train simulator was introduced in Swedish train driver education and is still the only full scale simulator being used to educate train drivers in Sweden. The reason for this seems to be a lack of educational and economic motives for an expanded usage of simulators within education and training. Energy savings within the railway domain, i.e. energy-efficient driving, is currently a topic for all train operators in Sweden. Some operators already educate their drivers in energy efficient driving and tests of energy efficiency in real traffic has shown a potential energy saving of 16 %, after drivers have completed a theoretical education in energy-efficient driving. Because there were some uncertainties in the data from the tests carried out in real traffic, where conditions and experimental procedures varied between the drivers and it also turned out that education and access to a support system while driving resulted in a small saving in energy (13 %) there was a need to examine the potential savings under controlled conditions. Therefore, a study was conducted using a train simulator. In the simulator, the researcher has full control over the data and conditions are the same for all drivers. The simulator used in the study was developed by VTI (Swedish National Road and Transport Research Institute) and modeled after an X50 Regina. The purpose of this study was to investigate whether the same theoretical education in energy-efficient driving, in combination with simulator training under ideal conditions, could contribute to the same, or better energy saving compared to the results of the tests from real traffic. Furthermore, the effect of feedback during training with regard to energy savings was also investigated. 24 train driver students were divided into three groups with 8 students in each. Two of these groups completed two sessions (reference and test session) with theoretical education and simulator training between the sessions. The last group (control group) completed two sessions (reference and test session) without education and training between the sessions. The two groups that were given theoretical education conducted their simulator training under two different conditions, where one group trained with feedback (energy consumption and rail gradient) and the other group trained without feedback. It turns out that a theoretical education in energy efficient driving, combined with 30 minutes of simulator training, resulted in a total saving of about 24 % energy for both groups. Also, considering that the control group improved their energy consumption by simply driving the simulator two times (8 % total energy saving), the energy saving was almost equal to the result of the tests in real traffic. Since the results were equal even though the conditions differed, there is reason to investigate how different driving conditions affect the outcome. There is also a need to better understand why education in combination with a support system resulted in a lower energy saving than for those who were only given education during the tests in real traffic, and also why feedback during training in the simulator did not give a detectable effect. Basically, there are many reasons to further investigate how to design simulator training and support systems for train drivers. In addition to the energy savings, the results showed that drivers improved their arrival times i.e. arrive more accurate in relation to the time table. The results suggest that there is great potential for train simulators in the Swedish train driver education, both for training and for evaluating the effects of the training.