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Vägtransportsektorn står för en betydande del av de totala utsläppen av miljöfarliga ämnen. Av koldioxidutsläppen är andelen cirka 30 procent. Fordonstillverkningen utvecklas för varje år med förbättrade motorer som släpper ut mindre andel avgaser. Men antalet transporter på vägarna ökar. Det finns därför ett behov av att utbilda chaufförer till att köra mer miljövänligt, inte låta motorerna gå på tomgång mm. I dag ställs krav på chaufförerna av buss och lastbil att de ska ha ett yrkeskompetensbevis (YKB) för att kunna fortsätta inom sitt yrke. Detta är ett steg i rätt riktning för en bättre miljö på vägarna. Bra utbildade chaufförer innebär dessutom lägre bränsle- och däckkostnader för åkeriet. Men förutom en direkt styrning från myndigheterna behöver chaufförerna även se ett ökat pengaflöde i börsen för att en förändring ska kunna ske. De bör få ta del av besparingarna för åkeriet. Jag är intresserad av vad åkare och chaufförer anser om denna extra yrkesförarutbildning.Speciellt intressant är det delmål som handlar om sparsam körning. Genom intervjuer med ägare till tunga fordon vill jag få fram en bild av vad branschen anser.Av resultatet framgår att YKB är accepterad. Ingen av de intervjuade önskade att utbildningen skulle försvinna som krav för yrkeschaufförer. Fem av sex håller speciellt fram avsnittet om sparsam körning som mycket bra. Eftersom YKB-utbildningen är ny krävs det fortlöpande undersökningar för att se om chaufförerna och åkeriägarna fortsätter att ha ett positivt synsätt.

During the time I've attended the programme to become a Transportation manager, I've been presented with quite a large number of different words. My purpose with this paper is to take a closer look at them, and see if they're sustainable concepts. This paper will be a literary study, and be on a wholly theoretical level. After a thorough examination of the various words, I've come to the conclusion that these words that I've chosen aren't just fad-words. They're going to be around for quite a while, this due to the fact that they're based on good ideas from the get-go. Many of them represent simple but functional solutions, that every one at work or at home that may partake in and thus create a better environment / Under den tiden jag har gått på Transportation manager programmet har jag fått ta del av en mängd ord. Dessa tänker jag gå in lite närmare på och se ifall de kan vara hållbara koncept. Detta arbetet kommer vara en litteraturstudie, och kommer att vara på en rent teoretiskt nivå. Efter att ha gått igenom de olika orden har jag kommit fram till att detta inte är några modeflugor jag har valt. De kommer att finnas kvar en lång tid, mest för att de är baserade på goda idéer från början. Många av dem representerar enkla men funktionella lösningar som var och en på företaget och hemma kan ta del av för att skapa en bättre miljö.

The accelerating climate change, which is mainly driven by human-caused CO2 emissions, requires not only the rapid introduction of new technologies and the far-reaching implementation of national and international regulations and laws, but also changes in human behavior. In this regard, behavioral changes in the transport sector are of special importance, not only because CO2 emissions of the transport sector have remained at a particularly high level for years, but also because many behavioral changes in this sector are associated with high CO2 emission savings potential (e.g., reducing vehicle use, using public transportation). Therefore, this dissertation investigated different eco-driving behaviors that have a positive effect on the climate due to reduced fuel or energy consumption and affect not only the driving task itself (operational decisions; e.g., driving at moderate speed) but also decisions before and after driving (tactical decisions; e.g., charging electric vehicles with renewable electricity) and decisions in the mobility context in general (strategic decisions; e.g., carpooling). Although the determinants of eco-driving have been intensively studied in the past, some determinants (e.g., different motivational reasons, behavioral difficulty) have been neglected and some of the identified impact factors were found not to be sufficient to deeply understand and effectively change eco-driving behaviors. In addition, the investigation of the relationship between multiple impact factors has been scarce to date. Therefore, one aim of this dissertation was to investigate the role of motivational (i.e., motivational reasons; e.g., environmental protection) and contextual factors (i.e., behavioral costs; e.g., time losses, physical/monetary effort) and their relationship for predicting eco-driving behaviors (studies 1, 2, 3). Moreover, past studies investigating interventions to promote eco-driving behaviors showed inconsistent and diminishing effects and missed to consider the impact of contextual factors. Therefore, another aim of this dissertation was to develop and identify effective eco-driving interventions, and to examine whether and how their effectiveness depends on the presence of contextual factors (studies 3, 4, 5). Study 1 was designed to investigate the relevance of motivational factors for eco-driving based on the theory of self-concordance (i.e., the consistency between a behavior/goal with the person’s pre-existing values and interests). For this, data of 539 German drivers of a cross-sectional online survey was analyzed. The findings indicate that self-reported eco-driving was significantly predicted by sustained effort towards eco-driving, which in turn was predicted by self-concordance. Therefore, individuals pursuing eco-driving out of strong interest or deep personal beliefs (i.e., autonomous motivation) as opposed to external forces or internal pressure (i.e., controlled motivation) reported greater effort towards this behavior. Furthermore, biospheric striving coherence, i.e., the coherence between biopsheric values (addressing the well-being of the environment/biosphere) and eco-driving, significantly predicted effort towards eco-driving. These findings allow the conclusion that autonomous rather than controlled motives and coherence between behavior and intrinsic rather than extrinsic values are relevant predictors of eco-driving. To gain insights into the relationship between autonomous motivations and behavioral costs for eco-driving, in study 2, data of two online surveys was analyzed (NStudy2.1 = 207, NStudy2.2 = 539). The analyses indicate that high autonomous motivations for eco-driving can buffer the negative effect of behavioral costs on eco-driving. Furthermore, the results indicate that high autonomous motivations predicted eco-driving behaviors better when these behaviors are associated with moderate than with very low behavioral costs. Therefore, eco-driving interventions should focus on how autonomous motivations can be influenced. However, changing (perceived) behavioral costs of eco-driving may also be a promising intervention technique. Study 3 examined the interactive influence of contextual factors (i.e., charging delay, walking distance, price saving) and behavioral interventions (i.e., CO2 emission cues, collecting points, information about others’ behavior) on pro-environmental charging decisions in an online experiment with current and potential future electric vehicle owners (N = 286). The results show that the interventions influenced the decision to choose a pro-environmental charging station over a convenient non-sustainable alternative when behavioral costs were small to moderate. In situations with no or only negligible extra costs, participants did not need additional persuasion, whereas in high-cost situations, behavioral interventions were insufficient to influence pro-environmental behavior. To extend these insights, study 4 aimed at investigating if eco-driving behaviors could be motivated by symbolically and/or monetarily framed benefits (i.e., framing interventions). Hence, to investigate if and how eco-driving tips with framed behavioral consequences promote eco-driving motivations and behaviors in everyday life, a longitudinal online experiment with German vehicle owners over the course of one month (NT1 = 281; NT2 = 228) was conducted. Participants were randomly assigned to a framing group, in which either CO2, pollutant (e.g., NOx), or monetary savings of eco-driving were highlighted, or the control group. The findings indicate that participants rated the CO2/pollutant savings (i.e., symbolical benefits) as worthier than the monetary savings. However, individuals who were exposed to framed eco-driving information independent of framing content reported an increase of eco-driving behavior, compared to the control group. Therefore, differently framed eco-driving tips motivated self-reported eco-driving behaviors that are associated with low to moderate behavioral costs. Because psychological and contextual factors were identified as relevant impact factors of eco-driving behaviors, study 5 set out to explore if a combined intervention addressing multiple motives could influence actual eco-driving behavior change. Therefore, an experimental driving study with 94 German drivers was conducted to analyze how combined interventions affect pro-environmental charging and eco-driving behavior with an electric vehicle. The findings suggest that a combined intervention with informational cues (i.e., CO2 emission savings) as well as gamified (i.e., a competitive task) and monetary incentives did not significantly motivate individuals to choose a charging station that provides renewable electricity but requires a walking detour. However, the intervention did motivate individuals to seek eco-driving information (e.g., use eco mode). Being interested in eco-driving behaviors helped to improve (i.e., reduce) energy consumption during a real-world drive. To summarize, the present dissertation contributes valuable empirical results that broaden and deepen the understanding of various eco-driving behaviors (e.g., charging an electric vehicle with renewable electricity, driving at moderate speed). First, the findings indicate that environmental and autonomous motivations as well as behavioral costs are important determinants of eco-driving behaviors and that these two factors have interactive instead of additive effects on pro-environmental driver behaviors (studies 1, 2, 3). Second, the findings of the dissertation indicate that interventions that inform individuals why and how to behave pro-environmentally and stimulate environmental and autonomous motivations provide promising results for low- and moderate-cost eco-driving behaviors (studies 3, 4, 5). However, for high-cost driver behaviors, informational interventions are not sufficient but should be combined with hard measures instead, e.g., structural changes or financial incentives. Hence, researchers and policy makers should consider that eco-driving interventions need to a) address environmental and autonomous motivations and b) be tailored to the contextual factors (i.e., behavioral costs) of the behavior that is aimed at being changed or tailored to the situation in which the behavior arises.:Acknowledgement Statement Contents List of tables and figures Abstract 1 General introduction 2 Pro-environmental behavior and eco-driving 2.1 Definition of pro-environmental behavior 2.2 Definition of eco-driving 2.2.1 Strategic decisions 2.2.2 Tactical decisions 2.2.3 Operational decisions 3 Impact factors – Drivers and barriers of pro-environmental (driver) behavior change 3.1 Psychological factors 3.1.1 Self-determined (autonomous) motivation and self-concordance 3.2 Contextual factors (behavioral costs) 3.3 Relationship between psychological and contextual factors 3.3.1 Campbell Paradigm 3.3.2 Low-Cost Hypothesis 3.3.3 A-B-C Model 3.3.4 Effort Hypothesis 3.3.5 Summary 4 Behavioral interventions for pro-environmental (driver) behavior change 4.1 Effectiveness of behavioral interventions 4.2 Strategies for implementing effective behavioral interventions 5 Summary and research questions 5.1 Do autonomous and self-concordant motivations predict pro-environmental driver decisions and behavior (studies 1, 2)? 5.2 What is the relationship between behavioral costs and psychological factors/interventions for pro-environmental driver decisions and behavior (studies 2, 3)? 5.3 Which interventions are effective for promoting pro-environmental driver decisions and behavior (studies 3, 4, 5)? 6 Study 1: The role of self-concordance for self-reported strategic, tactical, and operational eco-driving 6.1 Introduction 6.2 Method 6.3 Results 6.4 Discussion 7 Study 2: Behavioral costs moderate the relationship between environmental motivations and eco-driving 7.1 Introduction 7.2 Study 2.1 7.2.1 Method 7.2.2 Results 7.3 Study 2.2 7.3.1 Method 7.3.2 Results 7.4 Discussion 8 Study 3: A matter of behavioral cost: Contextual factors and behavioral interventions interactively influence pro-environmental charging decisions 8.1 Introduction 8.2 Method 8.3 Results 8.4 Discussion 9 Study 4: Environmental, altruistic, or monetary benefits? A longitudinal online experiment on how framed behavioral consequences affect self-reported eco-driving of German vehicle owners 9.1 Introduction 9.2 Method 9.3 Results 9.4 Discussion 10 Study 5: Carbon savings, fun, and money: The effectiveness of multiple motives for eco-driving and green charging with electric vehicles in Germany 10.1 Introduction 10.2 Method 10.3 Results 10.4 Discussion 11 General discussion 11.1 Summary of empirical research findings 11.2 Discussion of research questions 11.3 Implications of research findings 11.4 Open questions and outlook 11.5 Conclusion References Appendix A. Full intervention material of study 4 B. Questionnaire material of study 4 C. Eco-driving behaviors and intervention material of study 5 Consent

The operation of groups of heavy-duty vehicles at small inter-vehicular distances, known as platoons, lowers the overall aerodynamic drag and, therefore, reduces fuel consumption and greenhouse gas emissions. Experimental tests conducted on a flat road and without traffic have shown that platooning has the potential to reduce the fuel consumption up to 10%. However, platoons are expected to drive on public highways with varying topography and traffic. Due to the large mass and limited engine power of heavy-duty vehicles, road slopes can have a significant impact on feasible and optimal speed profiles. Therefore, maintaining a short inter-vehicular distance without coordination can result in inefficient or even infeasible speed trajectories. Furthermore, external traffic can interfere by affecting fuel-efficiency and threatening the safety of the platooning vehicles. This thesis addresses the problem of safe and fuel-efficient control for heavy-duty vehicle platooning. We propose a hierarchical control architecture that splits this complex control problem into two layers. The layers are responsible for the fuel-optimal control based on look-ahead information on road topography and the real-time vehicle control, respectively. The top layer, denoted the platoon coordinator, relies on a dynamic programming framework that computes the fuel-optimal speed profile for the entire platoon. The bottom layer, denoted the vehicle control layer, uses a distributed model predictive controller to track the optimal speed profile and the desired inter-vehicular spacing policy. Within this layer, constraints on the vehicles' states guarantee the safety of the platoon. The effectiveness of the proposed controller is analyzed by means of simulations of several realistic scenarios. They suggest a possible fuel saving of up to 12% for the follower vehicles compared to the use of existing platoon controllers. Analysis of the simulation results shows how the majority of the fuel saving comes from a reduced usage of vehicles brakes. A second problem addressed in the thesis is model predictive control for obstacle avoidance and lane keeping for a passenger car. We propose a control framework that allows to control the nonlinear vehicle dynamics with linear model predictive control. The controller decouples the longitudinal and lateral vehicle dynamics into two successive stages. First, plausible braking and throttle profiles are generated. Second, for each profile, linear time-varying models of the lateral dynamics are derived and used to formulate a collection of linear model predictive control problems. Their solution provides the optimal control input for the steering and braking actuators. The performance of the proposed controller has been evaluated by means of simulations and real experiments. / <p>QC 20150911</p>

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Traffic signals are used at intersections to manage the flow of vehicles by allocating right-of-way in a timely manner for different users of the intersection. Traffic signals are therefore installed at an intersection to improve overall safety and to decrease vehicular average delay. However, the variation of driving speed in response to these signals causes an increase in fuel consumption and air emission levels. One solution to this problem is Eco-Cooperative Adaptive Cruise Control (Eco-CACC), which attempts to reduce vehicle fuel consumption and emission levels by optimizing driver behavior in the vicinity of a signalized intersection. Various Eco-CACC algorithms have been proposed by researchers to address this issue. With the help of vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication, algorithms are being developed that utilize signal phasing and timing (SPaT) data together with queue information to optimize vehicle trajectories in the vicinity of signalized intersections. The research presented in this thesis constitutes the third phase of a project that entailed developing and evaluating an Eco-CACC system. Its main objective is to evaluate the benefits of the newly developed Eco-CACC algorithm that was proposed by the Center for Sustainable Mobility at the Virginia Tech Transportation Institute. This algorithm uses advanced signal information (SPaT) to compute the fuel-optimal trajectory of vehicles, and, then, send recommended speeds to drivers as an audio message or implement them directly into the subject vehicle. The objective of this study is to quantitatively quantify the fuel-efficiency of the Eco-CACC system in a real field environment. In addition, another goal of this study is to address the implementation issues and challenges with the field application of the Eco-CACC system. A dataset of 2112 trips were collected as part of this research effort using a 2014 Cadillac SRX equipped with a vehicle onboard unit for (V2V) and (V2I) communication. A total of 32 participants between the ages of 18 and 30 were randomly selected from one age group (18-30) with an equal number of males and females. The controlled experiment was conducted on the Virginia Smart Road facility during daylight hours for dry pavement conditions. The controlled field experiment included four different scenarios: normal driving, driving with red indication countdown information provided to drivers, driving with recommended speed information computed by the Eco-CACC system and delivered to drivers, and finally automated driving (automated Eco-CACC system). The controlled field experiment was conducted for four values of red indication offsets along an uphill and downhill approach. The collected data were compared with regard to fuel economy and travel time over a fixed distance upstream and downstream of the intersection (820 ft (250 m) upstream of the intersection to 590 ft (180 m) downstream for a total length of 1410 ft (430 m)). The results demonstrate that the Eco-CACC system is very efficient in reducing fuel consumption levels especially when driving downhill. The field data indicates that the automated scenario could produce fuel and travel time savings of 31% and 9% on average, respectively. In addition, the study demonstrates that driving with a red indication countdown and recommended speed information can produce fuel savings ranging from 4 to 21 percent with decreases in travel times ranging between 1 and 10 percent depending on the value of red indication offset and the direction. Split-split-plot design was used to analyze the data and test significant differences between the four scenarios with regards to fuel consumption and travel time. The analysis shows that the differences between normal driving and driving with either the manual or automated Eco-CACC systems are statistically significant for all the red indication offset values. / Master of Science

Vehicle stops and speed variations account for a large percentage of vehicle fuel losses especially at signalized intersections. Recently, researchers have attempted to develop tools that reduce these losses by capitalizing on traffic signal information received via vehicle connectivity with traffic signal controllers. Existing state-of-the-art approaches, however, only consider surrogate measures (e.g. number of vehicle stops, time spent accelerating and decelerating, and/or acceleration or deceleration levels) in the objective function and fail to explicitly optimize vehicle fuel consumption levels. Furthermore, the majority of these models do not capture vehicle acceleration and deceleration limitations in addition to vehicle-to-vehicle interactions as constraints within the mathematical program. The connectivity between vehicles and infrastructure, as achieved through Connected Vehicles technology, can provide a vehicle with information that was not possible before. For example, information on traffic signal changes, traffic slow-downs and even headway and speed of lead vehicles can be shared. The research proposed in this dissertation uses this information and advanced computational models to develop fuel-efficient vehicle trajectories, which can either be used as guidance for drivers or can be attached to an electronic throttle controlled cruise control system. This fuel-efficient cruise control system is known as an Eco-Cooperative Adaptive Cruise Control (ECACC) system. In addition to the ECACC presented here, the research also expands on some of the key eco-driving concepts such as fuel-optimizing acceleration models, which could be used in conjunction with conventional vehicles and even autonomous vehicles, or assistive systems that are being implemented in vehicles. The dissertation first presents the results from an on-line survey soliciting driver input on public perceptions of in-vehicle assistive devices. The results of the survey indicate that user-acceptance to systems that enhance safety and efficiency is ranked high. Driver–willingness to use advanced in-vehicle technology and cellphone applications is also found to be subjective on what benefits it has to offer and safety and efficiency are found to be in the top list. The dissertation then presents the algorithmic development of an Eco-Cooperative Adaptive Cruise Control system. The modeling of the system constitutes a modified state-of-the-art path-finding algorithm within a dynamic programming framework to find near-optimal and near-real-time solutions to a complex non-linear programming problem that involves minimizing vehicle fuel consumption in the vicinity of signalized intersections. The results demonstrated savings of up to 30 percent in fuel consumption within the traffic signalized intersection vicinity. The proposed system was tested in an agent-based environment developed in MATLAB using the RPA car-following model as well as the Society of Automobile Engineers (SAE) J2735 message set standards for vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication. The results showed how multi-vehicle interaction enhances usability of the system. Simulation of a calibrated real intersection showed average fuel savings of nearly 30 percent for peak volumes. The fuel reduction was high for low volumes and decreased as the traffic volumes increased. The final testing of the algorithm was done in an enhanced Traffic Experimental Simulation tool (eTEXAS) that incorporates the conventional TEXAS model with a new web-service interface as well as connected vehicle message set dictionary. This testing was able to demonstrate model corrections required to negate the effect of system latencies as well as a demonstration of using SAE message set parsing in a connected vehicle application. Finally, the dissertation develops an integrated framework for the control of autonomous vehicle movements through intersections using a multi-objective optimization algorithm. The algorithm integrated within an existing framework that minimizes vehicle delay while ensuring vehicles do not collide. A lower-level of control is introduced that minimizes vehicle fuel consumption subject to the arrival times assigned by the upper-level controller. Results show that the eco-speed control algorithm was able to reduce the overall fuel-consumption of autonomous vehicles passing through an intersection by 15 percent while maintaining the 80 percent saving in delay when compared to a traditional signalized intersection control. / Ph. D.

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.