References of "Sajadi Alamdari, Seyed Amin 50002972"
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See detailEvaluation of End-To-End Learning for Autonomous Driving: The Good, the Bad and the Ugly
Varisteas, Georgios UL; Frank, Raphaël UL; Sajadi Alamdari, Seyed Amin UL et al

in 2nd International Conference on Intelligent Autonomous Systems, Singapore, Feb. 28 to Mar. 2, 2019 (2019, March 01)

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See detailNonlinear Model Predictive Control for Ecological Driver Assistance Systems in Electric Vehicles
Sajadi Alamdari, Seyed Amin UL; Voos, Holger UL; Darouach, Mohamed

in Robotics and Autonomous Systems (2018)

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See detailEcological Advanced Driver Assistance System for Optimal Energy Management in Electric Vehicles
Sajadi Alamdari, Seyed Amin UL; Voos, Holger UL; Darouach, Mohamed

in IEEE Intelligent Transportation Systems Magazine (2018)

Battery Electric Vehicles have a high potential in modern transportation, however, they are facing limited cruising range. The driving style, the road geometries including slopes, curves, the static and ... [more ▼]

Battery Electric Vehicles have a high potential in modern transportation, however, they are facing limited cruising range. The driving style, the road geometries including slopes, curves, the static and dynamic traffic conditions such as speed limits and preceding vehicles have their share of energy consumption in the host electric vehicle. Optimal energy management based on a semi-autonomous ecological advanced driver assistance system can improve the longitudinal velocity regulation in a safe and energy-efficient driving strategy. The main contribution of this paper is the design of a real-time risk-sensitive nonlinear model predictive controller to plan the online cost-effective cruising velocity in a stochastic traffic environment. The basic idea is to measure the relevant states of the electric vehicle at runtime, and account for the road slopes, the upcoming curves, and the speed limit zones, as well as uncertainty in the preceding vehicle behavior to determine the energy-efficient velocity profile. Closed-loop Entropic Value-at-Risk as a coherent risk measure is introduced to quantify the risk involved in the system constraints violation. The obtained simulation and field experimental results demonstrate the effectiveness of the proposed method for a semi-autonomous electric vehicle in terms of safe and energy-efficient states regulation and constraints satisfaction. [less ▲]

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See detailStochastic Optimum Energy Management for Advanced Transportation Network
Sajadi Alamdari, Seyed Amin UL; Voos, Holger UL; Darouach, Mohamed

in 15th IFAC Symposium on Control in Transportation Systems CTS 2018 (2018, July 19)

Smart and optimal energy consumption in electric vehicles has high potential to improve the limited cruising range on a single battery charge. The proposed concept is a semi-autonomous ecological advanced ... [more ▼]

Smart and optimal energy consumption in electric vehicles has high potential to improve the limited cruising range on a single battery charge. The proposed concept is a semi-autonomous ecological advanced driver assistance system which predictively plans for a safe and energy-efficient cruising velocity profile autonomously for battery electric vehicles. However, high entropy in transportation network leads to a challenging task to derive a computationally efficient and tractable model to predict the traffic flow. Stochastic optimal control has been developed to systematically find an optimal decision with the aim of performance improvement. However, most of the developed methods are not real-time algorithms. Moreover, they are mainly risk-neutral for safety-critical systems. This paper investigates on the real-time risk-sensitive nonlinear optimal control design subject to safety and ecological constraints. This system improves the efficiency of the transportation network at the microscopic level. Obtained results demonstrate the effectiveness of the proposed method in terms of states regulation and constraints satisfaction. [less ▲]

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See detailModel Predictive Control for Aerial Collision Avoidance in Dynamic Environments
Castillo Lopez, Manuel UL; Sajadi Alamdari, Seyed Amin UL; Sanchez Lopez, Jose Luis UL et al

in 26th Mediterranean Conference on Control and Automation (MED), Zadar, Croatia, 19-22 June 2018 (2018, June)

Autonomous navigation in unknown environments populated by humans and other robots is one of the main challenges when working with mobile robots. In this paper, we present a new approach to dynamic ... [more ▼]

Autonomous navigation in unknown environments populated by humans and other robots is one of the main challenges when working with mobile robots. In this paper, we present a new approach to dynamic collision avoidance for multi-rotor unmanned aerial vehicles (UAVs). A new nonlinear model predictive control (NMPC) approach is proposed to safely navigate in a workspace populated by static and/or moving obstacles. The uniqueness of our approach lies in its ability to anticipate the dynamics of multiple obstacles, avoiding them in real-time. Exploiting active set algorithms, only the obstacles that affect to the UAV during the prediction horizon are considered at each sample time. We also improve the fluency of avoidance maneuvers by reformulating the obstacles as orientable ellipsoids, being less prone to local minima and allowing the definition of a preferred avoidance direction. Finally, we present two real-time implementations based on simulation. The former demonstrates that our approach outperforms its analog static formulation in terms of safety and efficiency. The latter shows its capability to avoid multiple dynamic obstacles. [less ▲]

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See detailStochastic Model Predictive Control for Eco-Driving Assistance Systems in Electric Vehicles
Sajadi Alamdari, Seyed Amin UL

Doctoral thesis (2018)

Electric vehicles are expected to become one of the key elements of future sustainable transportation systems. The first generation of electric cars are already commercially available but still, suffer ... [more ▼]

Electric vehicles are expected to become one of the key elements of future sustainable transportation systems. The first generation of electric cars are already commercially available but still, suffer from problems and constraints that have to be solved before a mass market might be created. Key aspects that will play an important role in modern electric vehicles are range extension, energy efficiency, safety, comfort as well as communication. An overall solution approach to integrating all these aspects is the development of advanced driver assistance systems to make electric vehicles more intelligent. Driver assistance systems are based on the integration of suitable sensors and actuators as well as electronic devices and software-enabled control functionality to automatically support the human driver. Driver assistance for electric vehicles will differ from the already used systems in fuel-powered cars such as electronic stability programs, adaptive cruise control etc. in a way that they must support energy efficiency while the system itself must also have a low power consumption. In this work, an eco-driving functionality as the first step towards those new driver assistance systems for electric vehicles will be investigated. Using information about the internal state of the car, navigation information as well as advanced information about the environment coming from sensors and network connections, an algorithm will be developed that will adapt the speed of the vehicle automatically to minimize energy consumption. From an algorithmic point of view, a stochastic model predictive control approach will be applied and adapted to the special constraints of the problem. Finally, the solution will be tested in simulations as well as in first experiments with a commercial electric vehicle in the SnT Automation & Robotics Research Group (SnT ARG). [less ▲]

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See detailDeadzone-Quadratic Penalty Function for Predictive Extended Cruise Control with Experimental Validation
Sajadi Alamdari, Seyed Amin UL; Voos, Holger UL; Darouach, Mohamed

in ROBOT 2017: Third Iberian Robotics Conference, Sevilla, Spain 22-24 November 2017 (2017, November)

Battery Electric Vehicles have high potentials for the modern transportations, however, they are facing limited cruising range. To address this limitation, we present a semi-autonomous ecological driver ... [more ▼]

Battery Electric Vehicles have high potentials for the modern transportations, however, they are facing limited cruising range. To address this limitation, we present a semi-autonomous ecological driver assistance system to regulate the velocity with energy-efficient techniques. The main contribution of this paper is the design of a real-time nonlinear receding horizon optimal controller to plan the online cost-effective cruising velocity. Instead of conventional L2-norms, a deadzone-quadratic penalty function for the nonlinear model predictive controller is proposed. Obtained field experimental results demonstrate the effectiveness of the proposed method for a semi-autonomous electric vehicle in terms of real-time energy-efficient velocity regulation and constraints satisfaction. [less ▲]

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See detailRisk-averse Stochastic Nonlinear Model Predictive Control for Real-time Safety-critical Systems
Sajadi Alamdari, Seyed Amin UL; Voos, Holger UL; Darouach, Mohamed

in The 20th World Congress of the International Federation of Automatic Control, IFAC 2017 World Congress, Toulouse, France, 9-14 July 2017 (2017, July 11)

Stochastic nonlinear model predictive control has been developed to systematically find an optimal decision with the aim of performance improvement in dynamical systems that involve uncertainties. However ... [more ▼]

Stochastic nonlinear model predictive control has been developed to systematically find an optimal decision with the aim of performance improvement in dynamical systems that involve uncertainties. However, most of the current methods are risk-neutral for safety-critical systems and depend on computationally expensive algorithms. This paper investigates on the risk-averse optimal stochastic nonlinear control subject to real-time safety-critical systems. In order to achieve a computationally tractable design and integrate knowledge about the uncertainties, bounded trajectories generated to quantify the uncertainties. The proposed controller considers these scenarios in a risk-sensitive manner. A certainty equivalent nonlinear model predictive control based on minimum principle is reformulated to optimise nominal cost and expected value of future recourse actions. The capability of proposed method in terms of states regulations, constraints fulfilment, and real-time implementation is demonstrated for a semi-autonomous ecological advanced driver assistance system specified for battery electric vehicles. This system plans for a safe and energy-efficient cruising velocity profile autonomously. [less ▲]

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See detailFast Stochastic Non-linear Model Predictive Control for Electric Vehicle Advanced Driver Assistance Systems
Sajadi Alamdari, Seyed Amin UL; Voos, Holger UL; Darouach, Mohamed

in 13th IEEE International Conference on Vehicular Electronics and Safety, Vienna, Austria 27-28 June 2017 (2017, June 27)

Semi-autonomous driving assistance systems have a high potential to improve the safety and efficiency of the battery electric vehicles that are enduring limited cruising range. This paper presents an ... [more ▼]

Semi-autonomous driving assistance systems have a high potential to improve the safety and efficiency of the battery electric vehicles that are enduring limited cruising range. This paper presents an ecologically advanced driver assistance system to extend the functionality of the adaptive cruise control system. A real-time stochastic non-linear model predictive controller with probabilistic constraints is presented to compute on-line the safe and energy-efficient cruising velocity profile. The individual chance-constraint is reformulated into a convex second-order cone constraint which is robust for a general class of probability distributions. Finally, the performance of proposed approach in terms of states regulation, constraints fulfilment, and energy efficiency is evaluated on a battery electric vehicle. [less ▲]

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See detailModel predictive control for cooperative control of space robots
Kannan, Somasundar UL; Sajadi Alamdari, Seyed Amin UL; Dentler, Jan Eric UL et al

in Model predictive control for cooperative control of space robots (2017, January)

The problem of Orbital Manipulation of Passive body is discussed here. Two scenarios including passive object rigidly attached to robotic servicers and passive body attached to servicers through ... [more ▼]

The problem of Orbital Manipulation of Passive body is discussed here. Two scenarios including passive object rigidly attached to robotic servicers and passive body attached to servicers through manipulators are discussed. The Model Predictive Control (MPC) technique is briefly presented and successfully tested through simulations on two cases of position control of passive body in the orbit. [less ▲]

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See detailAn Extended Cooperative Adaptive Cruise Control (CACC) Algorithm for Efficient Energy Consumption & Traffic Density Formulation
Bayar, Bilgehan; Sajadi Alamdari, Seyed Amin UL; Viti, Francesco UL et al

in Traffic Flow Theory and Characteristics Committee (AHB45) 2016 Summer Meeting, Sydney, Australia, 2016 (2016, July 02)

Electric transportation, one of the most promising technologies of the century, can contribute to a greener environment as it is emission-free and sustainable. Although this technology promises a clean ... [more ▼]

Electric transportation, one of the most promising technologies of the century, can contribute to a greener environment as it is emission-free and sustainable. Although this technology promises a clean transportation style, it also has some drawbacks. One of the most significant one is cruising range, which needs to be addressed sustainably. The most eco-friendly solution is decreasing energy consumption by addressing driving behaviour. This can be achieved by taking the advantage of implementing an advancing vehicle automation technology which controls vehicles using a driver-assistance system such as Eco-Cruise Control (Eco-CC). Variety of systems already exist in the literature and a little known advanced version Eco-Adaptive Cruise Control (Eco-ACC) systems are developed as well. The next step of the vehicle automation is vehicle cooperation and information sharing, so-called Cooperative Adaptive Cruise Control (CACC). It is already developed and tested by various researcher. However, the largest deal of existing studies focus on assessing the performance in terms of safety, possible contributions to the energy consumption is not taken into account. This study covers the extension of Cooperative Adaptive Cruise Control systems while aiming to provide an energy efficient extended control algorithm to increase the energy efficiency and battery usage for electric vehicles. An energy efficient control algorithm is aimed to be derived to decrease the consumption of the vehicle. Cruising velocities and vehicle positions are received from the leading vehicles and accordingly traction force is adjusted to achieve efficient energy consumption. By providing vehicle to vehicle (V2V) communication tighter spacing gaps, lower time headway, are aimed to obtain while traffic disturbances are damped, whereas in the cases ACC applications amplify the disturbance. Traffic density formula is introduced by using V2V communication which might be useful for ADAS and ITS framework. As a result, increase in traffic stability, density, and reduction in the total energy consumption is expected. Moreover, possible reductions in air drag with tighter spacing gaps may lead reduction in energy consumption. For the energy calculations and the validation of the proposed method, vehicle dynamics and energy consumption of an electric car is formulated, which has completely different characteristics and limitations than combustion engine cars. Hence the study aims to provide additional understanding of behaviour of a fleet of CACC-equipped electric vehicles. Even though the proposed control algorithm is developed for Electric Vehicles, it can be extended to other vehicle types based on their energy consumption characteristics and vehicle dynamics. [less ▲]

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See detailImpact of Different Spacing Policies for Adaptive Cruise Control on Traffic and Energy Consumption of Electric Vehicles
Bayar, Bilgehan; Sajadi Alamdari, Seyed Amin UL; Viti, Francesco UL et al

in 24th Mediterranean Conference on Control and Automation (MED), Athens, Greece, 2016 (2016, June 23)

This paper assesses the impact of different spacing policies for Adaptive Cruise Control (ACC) systems on traffic and environment. The largest deal of existing studies focus on assessing the performance ... [more ▼]

This paper assesses the impact of different spacing policies for Adaptive Cruise Control (ACC) systems on traffic and environment. The largest deal of existing studies focus on assessing the performance in terms of safety, while only few deal with the effect of ACC on the traffic flow and the environment. In particular, very little is know on traffic stability and energy consumption. In this study, the vehicles equipped with ACC are modelled and controlled by two different spacing policies. Besides, Human Driving Behavior (HDB) is modelled by using Gipps model for comparison and for simulating different penetration rates. As distinguished from other studies, vehicle dynamics and energy consumption of an electric car is formulated, which has completely different characteristics and limitations than combustion engine cars. Hence the study aims at providing additional understanding of how ACC-equipped electric vehicles will behave in dense traffic conditions. HDB and ACC vehicles are placed in a roundabout at different penetration rates. String stability and energy consumption are investigated by giving a shock wave to a stable traffic condition. It is found that ACC with quadratic spacing policy has significantly positive effects on string stability and energy consumption. [less ▲]

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See detailNonlinear Model Predictive Extended Eco-Cruise Control for Battery Electric Vehicles
Sajadi Alamdari, Seyed Amin UL; Voos, Holger UL; Darouach, Mohamed

in 24th Mediterranean Conference on Control and Automation (MED), Athens, Greece, 2016 (2016, June 22)

Battery Electric Vehicles are becoming a promising technology for road transportation. However, the main disadvantage is the limited cruising range they can travel on a single battery charge. This paper ... [more ▼]

Battery Electric Vehicles are becoming a promising technology for road transportation. However, the main disadvantage is the limited cruising range they can travel on a single battery charge. This paper presents a novel extended ecological cruise control system to increase the autonomy of an electric vehicle by using energy-efficient driving techniques. Driven velocity, acceleration profile, geometric and traffic characteristics of roads largely affect the energy consumption. An energy-efficient velocity profile should be derived based on anticipated optimal actions for future events by considering the electric vehicle dynamics, its energy consumption relations, traffic and road geometric information. A nonlinear model predictive control method with a fast numerical algorithm is adapted to determine proper velocity profile. In addition, a novel model to describe the energy consumption of a series- production electric vehicle is introduced. The hyperfunctions concept is used to model traffic and road geometry data in a new way. The proposed system is simulated on a test track scenario and obtained results reveal that the extended ecological cruise control can significantly reduce the energy consumption of an electric vehicle. [less ▲]

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See detailVision-Based Steering Control, Speed Assistance and Localization for Inner-CityVehicles
Olivares Mendez, Miguel Angel UL; Sanchez-Lopez, Jose Luis; Jimenez, Felipe et al

in Sensors (2016), 16(3), 362

Autonomous route following with road vehicles has gained popularity in the last few decades. In order to provide highly automated driver assistance systems, different types and combinations of sensors ... [more ▼]

Autonomous route following with road vehicles has gained popularity in the last few decades. In order to provide highly automated driver assistance systems, different types and combinations of sensors have been presented in the literature. However, most of these approaches apply quite sophisticated and expensive sensors, and hence, the development of a cost-efficient solution still remains a challenging problem. This work proposes the use of a single monocular camera sensor for an automatic steering control, speed assistance for the driver and localization of the vehicle on a road. Herein, we assume that the vehicle is mainly traveling along a predefined path, such as in public transport. A computer vision approach is presented to detect a line painted on the road, which defines the path to follow. Visual markers with a special design painted on the road provide information to localize the vehicle and to assist in its speed control. Furthermore, a vision-based control system, which keeps the vehicle on the predefined path under inner-city speed constraints, is also presented. Real driving tests with a commercial car on a closed circuit finally prove the applicability of the derived approach. In these tests, the car reached a maximum speed of 48 km/h and successfully traveled a distance of 7 km without the intervention of a human driver and any interruption. [less ▲]

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See detailModel Predictive Control for Spacecraft Rendezvous
Kannan, Somasundar UL; Sajadi Alamdari, Seyed Amin UL; Dentler, Jan Eric UL et al

in 4th International Conference on Control, Mechatronics and Automation ICCMA '16, Barcelona, Spain, 2016 (2016)

The current paper addresses the problem of Spacecraft Rendezvous using Model Predictive Control (MPC). The Clohessy-Wiltshire-Hill equations are used to model the spacecraft relative motion. Here the ... [more ▼]

The current paper addresses the problem of Spacecraft Rendezvous using Model Predictive Control (MPC). The Clohessy-Wiltshire-Hill equations are used to model the spacecraft relative motion. Here the rendezvous problem is discussed by trajectory control using MPC method. Two different scenarios are addressed in trajectory control. The first scenario consist of position control with fuel constraint, secondly the position control is performed in the presence of obstacles. Here the problem of fuel consumption and obstacle avoidance is addressed directly in the cost function. The proposed methods are successfully analysed through simulations. [less ▲]

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See detailLearnable Data-Oriented Controller for ABS in Brake By Wire Vehicles
Habibizad Navin, Ahmad; Sajadi Alamdari, Seyed Amin UL; Mirnia, Mir Kamal

in IEICE Electronics Express (2011), 8(6), 367-371

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See detailLearnable problem solution data structure ABS control for brake by wire vehicles
Habibizad Navin, Ahmad; Sajadi Alamdari, Seyed Amin UL; Mirnia, Mir Kamal

in Computer Design and Applications (ICCDA), 2010 International Conference on (2010)

Detailed reference viewed: 76 (9 UL)