Guidance Scenario Research Articles

Fixed Time Cooperative Scheme Design for Missiles Salvo Attack

This paper proposes a fixed-time cooperative control strategy for multiple missiles with impact angle constraints to accomplish the salvo attack guidance scenario on maneuvering targets. A fixed-time extended state observer (ESO) is proposed to estimate the target accelerations. In order to execute the salvo attack, along the line of sight (LOS) direction guidance law and the LOS normal direction guidance law are the two components of the proposed fixed time guidance scheme. The efficiency of the designed method is demonstrated through simulation results.

Distributed fuzzy learning sliding mode cooperative control for non-affine nonlinear multi-missile guidance systems via a prescribed performance observer

This paper focuses on the distributed fuzzy learning sliding mode cooperative control issue for non-affine nonlinear multi-missile guidance systems. The dynamics of each follower is non-affine form with unknown lumped factor. To estimate the unknown lumped factor, a generalized fuzzy hyperbolic model (GFHM) based prescribed performance observer (PPO) is proposed. Different from the traditional disturbance observers, a residual set of error transient behavior is incorporated additionally so that the peak phenomenon can be avoided. Meanwhile, an auxiliary system is employed to convert the system of each follower to augmented affine form. Then, a distributed fuzzy learning sliding mode cooperative control approach is designed which consists of two parts. The adaptive sliding mode control (SMC) part is designed to force the states to move along the predefined integral sliding surface. For the equivalent sliding dynamics, the distributed optimal control part with GFHM is developed to minimize the cooperative performance function. Thus, the stability and the optimality of the closed-loop system are guaranteed synchronously. Finally, all signals of closed-loop system are rigorously proved bounded and the multi-missile cooperative guidance scenario is applied to verify the effectiveness of proposed method.

Proactive Control for Online Individual User Adaptation in a Welfare Robot Guidance Scenario: Toward Supporting Elderly People

Due to demographic change, health and elderly care systems are facing a shortage of qualified caregivers. This issue can be addressed by introducing welfare robots into people’s homes, hospitals, and care institutions. To provide useful support, such robots must adapt to individual users and smoothly interact with them. From this perspective, we present advances on the development of proactive control for online individual user adaptation in a welfare robot guidance scenario, with the integration of three main modules: 1) navigation control; 2) visual human detection; and 3) temporal error correlation-based neural learning. The proposed control approach can drive a mobile robot to autonomously navigate in relevant indoor environments. At the same time, it can predict human walking speed based on visual information without prior knowledge of personality and preferences (i.e., walking speed). The robot then uses this prediction to continuously adapt its speed to individual users in a proactive online manner. We validate the performance of the proposed proactive robot control in different real-world environments with various users, including an elderly resident of a Danish elderly care center. The results show that the robot successfully and smoothly guided various users of different ages and average walking speeds (e.g., 0.2 m/s, 0.7 m/s, and 1.1 m/s) to target locations over distances of 25–60 m. All in all, this study captures a wide range of research from robot control technology development to technological validity in a relevant environment and system prototype demonstration in an operational environment (i.e., an elderly care center).

Varying-Gain Proportional Navigation Guidance for Precise Impact Time Control

This paper proposes a varying-gain proportional navigation guidance (PNG) law that can serve as the baseline for precise control of impact time. First, a varying-gain PNG law is developed by an inverse design strategy from the explicit time-to-go estimation of the conventional PNG law, which leads to high control efficiency and accurate time-to-go prediction. Next, to show its potential significance, the varying-gain PNG law is augmented with a biased feedback command to obtain an impact time control guidance (ITCG) law. As a step forward in more practical applications considering missile speed variation induced by thrust, drag, and gravity, another ITCG law is derived from an efficient time-to-go prediction method by taking the exact trajectory-to-go as the independent variable. Further, the varying-gain PNG law and the planar ITCG laws are extended to the three-dimensional guidance scenario by steering the missile to fly on an engagement plane. Compared with similar existing results, the proposed ITCG laws based on the varying-gain PNG law do not involve any linearized approximations in the derivation, and thus possess higher impact precision, wider feasible region, and less energy consumption. Finally, several numerical simulations are performed to support the analytical findings.

Spatial Simulation of Land-Use Development of Feixi County, China, Based on Optimized Productive–Living–Ecological Functions

Rural revitalization places higher demands on the productive–living–ecological (P-L-E) spaces of towns and cities. It is necessary, therefore, to identify, evaluate, and optimize P-L-E spaces to better guide spatial planning. Existing studies typically evaluate a single space, lacking a comprehensive consideration of whole-area integration. This study, therefore, developed a coupled spatial/developmental suitability evaluation system for Feixi County, Anhui Province, China, combining spatial quality evaluation, a coupled coordination model, and future land-use simulation (FLUS) model. The spatial quality of Feixi County in 2010, 2015, and 2020 was obtained by applying the evaluation system to the spatial development pattern. The results were analyzed and verified using the landscape pattern index and development suitability evaluation. The results showed the following: (1) The coupling coordination degree of the region increased from 0.131 to 0.372, changing from low to moderate coordination. (2) Based on the FLUS model to better capture the uncertainty and stochastic basis of the development in the study area. The kappa coefficient and Figure of Merit (FoM) index of the land-use simulation accuracy verification index were 0.7647 and 0.0508, respectively, and the logistic regression ROC values were above 0.75, thus meeting accuracy requirements. This demonstrated that the simulation model—based on a factor library of the evaluation of resource and environmental carrying capacity and suitability for development and construction—could better reflect future land-use changes. (3) The simulation showed that under the baseline development scenario, the area’s spatial layout is too concentrated in terms of construction land, ignoring P-L-E coordination. Under the ecological optimization scenario, high-quality ecological space is ensured, but other types of spaces are lacking. Under the comprehensive guidance scenario, lagging ecological space is optimized and P-L-E spatial development is enhanced through aggregation, clustering, concentration and integration. This way, the spatial quantity structure and distribution form can meet P-L-E spatial development needs in Feixi County. In this study, on the basis of scientific assessment of the current P-L-E space, the FLUS model was applied to carry out a scenario simulation according to different objectives. Moreover, based on the construction of the coupling system of human–nature system, the driving factors were improved to enhance the prediction accuracy of the FLUS model. This study’s findings can help improve the scientificity, flexibility and management efficiency of Feixi County’s P-L-E spatial layout, thereby supporting its sustainable development.

Fixed-Time Terminal Angle-Constrained Cooperative Guidance Law Against Maneuvering Target

In this article, fixed-time cooperative guidance laws are designed for multiple missiles to simultaneously attack a maneuvering target at desired terminal angles. The 3-D guidance commands consist of tangential acceleration along line-of-sight (LOS) direction to achieve a salvo attack and normal acceleration perpendicular to the LOS direction to realize a terminal angle-constrained interception. First, the tangential acceleration is derived from a distributed cooperative protocol to guarantee the fixed-time consensus of impact times for multiple missiles. Second, based on the integral sliding manifold and fixed-time reaching law, the normal acceleration is developed for each missile to converge the LOS angle to the desired value within a fixed time. In particular, the unknown target acceleration components are estimated by fixed-time observers and compensated in the guidance commands. The fixed-time stability of the proposed cooperative guidance law is rigorously proved and the explicit estimate for the convergence time is theoretically provided. Then, the proposed methods are utilized to realize the cooperative mission in the planar guidance scenario. Finally, the effectiveness and advantages of the proposed cooperative guidance laws are demonstrated through numerical simulations with comparative studies.

Toward Augmented Reality in Museums: Evaluation of Design Choices for 3D Object Pose Estimation

The solutions to many computer vision problems, including that of 6D object pose estimation, are dominated nowadays by the explosion of the learning-based paradigm. In this paper, we investigate 6D object pose estimation in a practical, real-word setting in which a mobile device (smartphone/tablet) needs to be localized in front of a museum exhibit, in support of an augmented-reality application scenario. In view of the constraints and the priorities set by this particular setting, we consider an appropriately tailored classical as well as a learning-based method. Moreover, we develop a hybrid method that consists of both classical and learning based components. All three methods are evaluated quantitatively on a standard, benchmark dataset, but also on a new dataset that is specific to the museum guidance scenario of interest.

Control system design for steering and depth subsystems of autonomous underwater vehicle

This work seeks to propose the development of a classical-optimized control design scheme for the steering and depth subsystems of autonomous underwater vehicle. Linearization methodological approach is carried out for acquiring the transfer functions to design the convenient P/PD/PID controllers where the gains are optimally adjusted utilizing a graphical tuning technique in LabVIEW. A low pass filter with additional alpha tuning parameter is combined with the derivative action to suppress the expected oscillations entirely. Furthermore, a comparative analysis study with linear quadratic regulator optimal control is established for testing and evaluating the suggested design approach. The effectiveness of the addressed controller strategy is appraised for compensating and rejection of several uncertainties such as fin saturation, angle limitation and sensor measurements noise as they are potentially affecting the system response. The validity of the linearized classical-optimized control design is substantiated with the nonlinear underwater vehicle model through a waypoint guidance scenario under LabVIEW simulation platform. The results revealed a significant improvement in transient and steady state responses and a remarkable enhanced stability for tracking the desired path to different designated waypoints.

Impact of IGRT Frequency Upon Errors in Head and Neck Radiation: A Retrospective Analysis of Different Schedules.

The relationship between image guided radiation therapy (IGRT) frequency and errors remains unclear. We present this data obtained from various IGRT frequencies in head and neck cancer patients. All consecutive head and neck cancer patients receiving radiation with curative intent and daily IGRT using kV cone beam CT (CBCT) scans, between June and December 2018, were included in the study. Translational displacements in medial-lateral (ML), superior-inferior (SI) and anterior-posterior (AP) direction were documented daily. Four IGRT scenarios were simulated retrospectively with reducing frequency, namely, 50% (Displacement data of every alternate fraction), 30% (Displacement data of 1st 3 fractions followed by once weekly), 20% (Displacement data of once weekly fraction) and 10% (Displacement data of 1st 3 fractions). Displacement data for once weekly was documented from shifts acquired on treatment day 1, 6,11, 16 and so on. Mean Displacements (MD), Systematic Errors (Σ), Random Errors (σ) and Planning Target Volume (PTV) margins were calculated for daily and simulated scenarios (Table 1). Thirty-one patients were analyzed with a median age of 54.5 years (Inter-Quartile Range - 42.75 - 67), predominantly males (77.4%), commonly involving oral cavity (54.8%) and oropharynx (25.8%) and treated post-operatively (64.5%). A total of 831 CBCT scans were analyzed, demonstrating MD in ML, SI and AP were normally distributed across all the image guidance scenarios, except in SI direction for daily format (Kolmogorov-Smirnov test of normality; Skewness - 3.32, p = .05). MD in the three directions were <0.1cm, reflected in Σ (< 0.2cm) for daily and simulated IGRT scenarios; σ for different formats revealed that in SI direction, for daily format was 0.7cm, whereas it was around 0.2cm for simulated scenarios and these differences were demonstrated in PTV margin calculation, 1cm in SI direction based upon daily IGRT data and around 0.5cm based upon simulated IGRT scenarios; margin estimation was similar in ML and AP direction for daily and simulated IGRT scenarios (Table 1). MD >0.5cm were around 2-3% in ML and SI direction, and 5% in AP direction; whereas MD >0.3cm were ranging between 10-20%. Systematic and random errors were similar across all simulated IGRT scenarios, inconclusive for superiority of one schedule over another, however higher random errors were observed with daily format in SI direction. This further validates the need for more data in determining the optimum IGRT frequency.Tabled 1Abstract 2565; TableIGRT FrequencyMLSIAPErrors (Σ = standard deviation (SD) from values of mean displacement for all patients; σ = root mean square of SD of all patients)ΣσΣσΣσDaily0.110.200.210.700.120.2250%0.110.210.120.210.140.2230%0.130.220.140.200.120.2520%0.150.240.150.200.130.2710%0.150.250.140.200.140.28PTV Margin (Van Herk’s Formula) (2.5Σ + 0.7σ) (cm)MLSIAPDaily0.421.000.4650%0.430.440.5030%0.490.480.4820%0.540.510.5010%0.560.490.56 Open table in a new tab

Finite‐time bounded stabilisation for linear systems with finite‐time H 2 ‐gain constraint

This study discusses the finite-time boundedness (FTB) of the state of linear systems with a finite-time H 2-gain performance constraint. With time-varying exogenous disturbances, the sufficient conditions for linear time-invariant and linear time-varying systems to satisfy both the FTB constraint and the finite-time H 2-gain performance constraint are developed. On the basis of the matrix inequality theory, a method for designing a controller by using state feedback is derived for each of the two classes of linear systems. These methods can effectively keep the state from reaching an unacceptable value and modulate the output performance within a specified finite-time interval. Two application examples of the terminal guidance scenario verify the effectiveness of the proposed methods.

The Development Simulation of Urban Green Space System Layout Based on the Land Use Scenario: A Case Study of Xuchang City, China

The development and evolution of an urban green space system is affected by both natural effects and human intervention. The simulation and prediction of an urban green space system can enhance the foresight of urban planning. In this study, several land use change scenarios of the main urban area of Xuchang City were simulated from 2014 to 2030 based on high-resolution land use data. The layout of each scenario was evaluated using landscape indexes. A Cellular Automata–based method (i.e., future land use simulation, FLUS) was applied to develop the urban green space system, which we combined with urban land use evolution. Using recent data, the FLUS model effectively dealt with the uncertainty and complexity of various land use types under natural and human effects and solved the dependence and error transmission of multiperiod data in the traditional land use simulation process. The root mean square error (RMSE) of probability of the suitability occurrence module and the Kappa coefficient of the overall model simulation accuracy verification index both met accuracy requirements. It was feasible to combine the evolution of the urban green space system with urban land development. Moreover, under the Baseline Scenario, the urban land use layout was relatively scattered, and the urban green space system showed a disordered development trend. The Master Plan Scenario had a compact urban land use layout, and the green space system was characterized by networking and systematization, but it did not consider the service capacity of the green space. The Planning Guidance Scenario introduced constraint conditions (i.e., a spatial development strategy, green space accessibility, and ecological sensitivity), which provided a more intensive and efficient urban space and improved the service function of the green space system layout. Managers and planners can evaluate the urban future land use development mode under different constraints. Moreover, they would be able to adjust the urban planning in the implementation process. This work has transformed the technical nature of the planning work from “static results” to a “dynamic process”.

Imaging and Dosimetry Study of Inter-fraction Setup Error in a Murine Xenograft Flank Tumor Radiation Model.

Modern small animal irradiation platforms provide for accurate delivery of radiation under 3D image guidance. However, leveraging these improvements currently comes at the cost of lower-throughput experimentation. Herein, we characterized setup accuracy and dosimetric robustness for mock/sham irradiation of a murine xenograft flank tumor model using the X-RAD SmART+ with the vendor-supplied Monte Carlo (MC) treatment planning system (SmART ATP). The chosen beam arrangement was parallel-opposing using a 20 mm square collimator, aligned off-axis for ipsilateral lung sparing. Using a cohort of five mice imaged with cone beam computed tomography (CBCT) over five consecutive mock-irradiation fractions, we compared inter-fraction setup variability resulting from a vendor-supplied multi-purpose bed with anesthesia nose cone with a more complicated immobilization solution with an integrated bite block with nose cone and Styrofoam platform. A hypothetical "high-throughput" image-guidance scenario was investigated, wherein the day 1 stage coordinates (resulting from CBCT guidance) were applied on days 2-5. Daily inter-fraction setup errors were evaluated per specimen (days 2-5) using CBCT-derived offsets from day 1 stage coordinates. Using the CBCT images and Monte Carlo dose calculation, 3D dosimetric plan robustness was evaluated for the vendor-supplied immobilization solution, for both the high-throughput guidance scenario as well as for use of daily CBCT-based alignment. Inter-fraction setup offset magnitude was 3.6 (±1.5) mm for the vendor-supplied immobilization compared to 3.3 (±1.8) mm for the more complicated solution. For the vendor-supplied immobilization, we found that daily CBCT was needed to adequately cover the flank tumors dosimetrically, given our chosen treatment approach.

Cooperative Guidance of Seeker-Less Missiles for Precise Hit

A novel cooperative guidance scenario is proposed that implements fire-and-forget attacks for seeker-less missiles with a cheap finder for stationary targets and without requiring real-time communication among missiles or precise position information. Within the proposed cooperative scenario, the classic leader-follower framework is utilized, and a two-stage cooperative guidance law is derived for the seeker-less missile. Linear-quadratic optimal control and biased proportional navigation guidance (PNG) are employed to develop this two-stage cooperative guidance law to minimize the control cost in the first stage and to reduce the maximum acceleration command in the second stage when the acceleration command is continuous. Simulations and comparisons are conducted that demonstrate the effectiveness and advantages of the proposed guidance law.

Image guidance and positioning accuracy in clinical practice: influence of positioning errors and imaging dose on the real dose distribution for head and neck cancer treatment

BackgroundModern radiotherapy offers the possibility of highly accurate tumor treatment. To benefit from this precision at its best, regular positioning verification is necessary. By the use of image-guided radiotherapy and the application of safety margins the influence of positioning inaccuracies can be counteracted. In this study the effect of additional imaging dose by set-up verification is compared with the effect of dose smearing by positioning inaccuracies for a collective of head-and-neck cancer patients.MethodsThis study is based on treatment plans of 40 head-and-neck cancer patients. To evaluate the imaging dose several image guidance scenarios with different energies, techniques and frequencies were simulated and added to the original plan. The influence of the positioning inaccuracies was assessed by the use of real applied table shifts for positioning. The isocenters were shifted back appropriately to these values to simulate that no positioning correction had been performed. For the single fractions the shifted plans were summed considering three different scenarios: The summation of only shifted plans, the consideration of the original plan for the fractions with set-up verification, and the addition of the extra imaging dose to the latter. For both effects (additional imaging dose and dose smearing), plans were analyzed and compared considering target coverage, sparing of organs at risk (OAR) and normal tissue complication probability (NTCP).ResultsDaily verification of the patient positioning using 3D imaging with MV energies result in non-negligible high doses. kV imaging has only marginal influence on plan quality, primarily related to sparing of organs at risk, even with daily 3D imaging. For this collective, sparing of organs at risk and NTCP are worse due to potential positioning errors.ConclusionRegular set-up verification is essential for precise radiation treatment. Relating to the additional dose, the use of kV modalities is uncritical for any frequency and technique. Dose smearing due to positioning errors for this collective mainly resulted in a decrease of OAR sparing. Target coverage also suffered from the positioning inaccuracies, especially for individual patients. Taking into account both examined effects the relevance of an extensive IGRT is clearly present, even at the expense of additional imaging dose and time expenditure.

Effect of imaging frequency on PTV margins and geographical miss during image guided radiation therapy for prostate cancer

BackgroundThe relationship between frequency of imaging during image guided radiation therapy (IGRT) and planning target volume (PTV) margin remains unclear. This issue is of practical significance given resource and time intensive nature of IGRT. The purpose of this study was to evaluate PTV margins with predefined and commonly used less-than-daily IGRT schedules using data obtained from patients treated with daily IGRT for prostate cancer. Methods and materialsDaily setup error and 3-dimensional daily alignment data for a total of 108 consecutive patients with prostate cancer treated with 2700 fractions of daily image guidance on tomotherapy were retrospectively analyzed. Five IGRT scenarios were simulated: alternate day, twice weekly, once weekly, first 3 days only, and no image guidance. The daily alignment data were modeled to simulate the 5 predefined scenarios by applying appropriate corrections to determine the PTV margin for each image guidance scenario. The data were also analyzed to predict possible geographical miss in any direction using 2 frequently used PTV margins of 7 and 5 mm for all the scenarios. ResultsDecreasing the frequency of image guidance increased the mean systematic error and the standard deviation of the systematic error. With decreased image guidance frequency, an increase in PTV margins was required to achieve adequate coverage of the clinical target volume. With reduction in image guidance from 50% to 12%, a gradual increase in percentage of fractions with predicted geographical miss using an isotropic PTV margin of 7 or 5 mm was seen. With every 15% decrease in imaging, a 5% increased risk of geographical miss was estimated. ConclusionsThe use of less-than-daily IGRT requires larger PTV margins for patients treated with intensity modulated radiation therapy for prostate cancer. With every 15% reduction, a 5% increased risk of geographical miss was estimated.

Modeling Travel Time Reliability of Road Network Considering Connected Vehicle Guidance Characteristics Indexes

Travel time reliability (TTR) is one of the important indexes for effectively evaluating the performance of road network, and TTR can effectively be improved using the real-time traffic guidance information. Compared with traditional traffic guidance, connected vehicle (CV) guidance can provide travelers with more timely and accurate travel information, which can further improve the travel efficiency of road network. Five CV characteristics indexes are selected as explanatory variables including the Congestion Level (CL), Penetration Rate (PR), Compliance Rate (CR), release Delay Time (DT), and Following Rate (FR). Based on the five explanatory variables, a TTR model is proposed using the multilogistic regression method, and the prediction accuracy and the impact of characteristics indexes on TTR are analyzed using a CV guidance scenario. The simulation results indicate that 80% of the RMSE is concentrated within the interval of 0 to 0.0412. The correlation analysis of characteristics indexes shows that the influence of CL, PR, CR, and DT on the TTR is significant. PR and CR have a positive effect on TTR, and the average improvement rate is about 77.03% and 73.20% with the increase of PR and CR, respectively, while CL and DT have a negative effect on TTR, and TTR decreases by 31.21% with the increase of DT from 0 to 180 s.

Impact of connected vehicle guidance information on network-wide average travel time

With the emergence of connected vehicle technologies, the potential positive impact of connected vehicle guidance on mobility has become a research hotspot by data exchange among vehicles, infrastructure, and mobile devices. This study is focused on micro-modeling and quantitatively evaluating the impact of connected vehicle guidance on network-wide travel time by introducing various affecting factors. To evaluate the benefits of connected vehicle guidance, a simulation architecture based on one engine is proposed representing the connected vehicle–enabled virtual world, and connected vehicle route guidance scenario is established through the development of communication agent and intelligent transportation systems agents using connected vehicle application programming interface considering the communication properties, such as path loss and transmission power. The impact of connected vehicle guidance on network-wide travel time is analyzed by comparing with non-connected vehicle guidance in response to different market penetration rate, following rate, and congestion level. The simulation results explore that average network-wide travel time in connected vehicle guidance shows a significant reduction versus that in non–connected vehicle guidance. Average network-wide travel time in connected vehicle guidance have an increase of 42.23% comparing to that in non-connected vehicle guidance, and average travel time variability (represented by the coefficient of variance) increases as the travel time increases. Other vital findings include that higher penetration rate and following rate generate bigger savings of average network-wide travel time. The savings of average network-wide travel time increase from 17% to 38% according to different congestion levels, and savings of average travel time in more serious congestion have a more obvious improvement for the same penetration rate or following rate.

Estimation-Guided Guidance and Its Implementation via Sequential Monte Carlo Computation

Existing missile guidance strategies are traditionally based on the separation theorem, which has never been proven valid in realistic guidance scenarios. In such cases, only the general separation theorem may be applied, implying a separately designed estimator and a guidance law accounting for the conditional probability density function. A new general-separation-theorem-compliant geometry-based approach is proposed to fusion of estimation and guidance. The conventional notion of reachability sets is extended, facilitating the introduction of miss-sets. A stochastic guidance strategy is proposed that aims at maximizing the pursuer’s single-shot kill probability by driving its own miss-set to optimally cover the evader’s miss-set (in a probabilistic sense). Information-based trajectory shaping is employed, when applicable, to enhance the scenario’s observability, thereby reducing the evader’s miss-set uncertainty. Computationally efficient sequential Monte Carlo methods are employed to estimate the evader’s miss-set and implement the guidance scheme. A numerical simulation study is used to demonstrate the proposed methodology’s robustness and accuracy in a realistic stochastic engagement. The performance of the proposed strategy is compared with that of an advanced perfect-information guidance law, addressing (in particular) real-time implementation issues and constraints. Proof-of-concept simulations demonstrate that the method is real-time amenable using present-day technology.

The evolution of high complexity companion testing for targeted and immuno-oncology.

The evolution of high complexity companion testing for targeted and immuno-oncology.

Online Optimizing Plug-In Hybrid Energy Management Strategy for Autonomous Guidance and Drive-aware Scenarios

Recent advances in autonomous driving and vehicle connectivity help to ensure safety and comfort in various driving conditions. These trends have widenened the system boundary conditions for hybrid powertrain operation with driving trajectory planning hence offering potential to improve powertrain operational efficiency. This paper presents an energy management (EM) controller for a plug-in hybrid vehicle exploiting predicted velocity trajectory together with its integration in both autonomous longitudinal guidance and driver-aware scenarios. The driver-aware scenario uses Markov chain based stochastic modelling of driving characteristics. The proposed EM controller solves online, a discretized version of the fuel consumption minimization problem using direct methods transcribing the problem into a finite dimensional mixed boolean quadratic problem with polytopic constraints. The convex part of the resulting problem is solved using an active set method. Simulation results from different driving situations based on standard driving cycle and real world driving scenarios demonstrate the functionality of the controller and its flexbility to handle varying control objectives.