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Efficient energy management in battery operated electric vehicle (EV) is important because of limited range caused by low energy density and inadequate energy storage capacity, insufficient charging stations, long charging time, etc. One of the ways to save energy without incurring any additional cost is to follow an optimal driving strategy by a driver because driving harshness consumes lots of energy...
Automated ground vehicles are becoming a reality for future deployment due to their potential improvement of safety, comfort or emission reductions. However, some challenges remain unsolved such as navigation in dynamic urban environments, where safety and comfort are paramount. In this paper, a novel speed profile generator, based on quintic Bézier curves, is presented. This approach permits to improve...
This article presents a path planning concept for automated driving. It builds upon existing approaches using quintic polynomials for path planning in structured environments. The contribution of this work are analytical solutions to evaluate selected properties of quintic polynomial based paths such as maximum acceleration and jerk or overshooting behavior. In addition, a concept for generating asymmetrical...
In many traffic situations there are times where interaction with other drivers is necessary and unavoidable in order to safely progress towards an intended destination. This is especially true for merge manoeuvres into dense traffic, where drivers sometimes must be somewhat aggressive and show the intention of merging in order to interact with the other driver and make the driver open the gap needed...
Automated driving is a safety critical process, which requires complex decision making. In order to validate driving decisions, it is possible to maintain at all times a contingency maneuver, which transfers the vehicle to a safe standstill, if other decision making processes fail. In this paper we present a motion planner, which computes contingency maneuvers for an automated vehicle in a 0.1[s]...
Examination of the control of a high-speed vehicle is essential to achieve autonomous navigation on high speed roads. Velocity profile generation is one of the challenging problems. In this paper we analyze the efficiency of an on-line velocity profiler algorithm. The presented method is based on a receding horizon implementation in which the vehicle executes part of the computed optimal trajectory,...
This paper presents a computational model capable of improving the action policies for a well-defined domain. Each action policy is represented as a driving plan P, which is composed of a number of actions {a1, ∶ an}. These actions can be used to move a train in a stretch of railroad Sti. The plans are elaborated using a CBR approach and reusing previous solutions and learning from plans. The CBR...
This paper considers the problem of path planning for autonomous ground vehicles on highways with regular traffic. The goal is to select a desired trajectory from a set of parameterized candidate trajectories such that some criterion is optimized. This selection is subject to avoiding collisions, respecting the traffic rules, and eliciting smooth behavior for passenger comfort. The desired trajectory...
This paper investigates two frameworks for interfacing trajectory tracking functions with a computationally tractable nonlinear model predictive trajectory guidance module for an autonomous road vehicle. In the first framework, the predictive trajectory guidance itself is configured in a tracking mode where the control inputs computed by the model predictive control act as targets for some lower-level...
This paper presents the design and simulation results of a vehicle path planning algorithm that takes into account traffic and other obstacles on a highway. The proposed algorithm is designed to require little computation in order to achieve a real time evaluation in an embedded environment such as an ECU. Hence, the trajectory planning is proposed as a two-step algorithm. The first step defines at...
This paper presents a new approach for kinodynamic online motion planning for Automated Guided Vehicles (AGVs) in industrial environments. AGVs normally transport large and heavy transport units such as Euro-pallets or mesh pallets. Nowadays just-in-time inventory management and lean production requires the transport of small transportation units. Thus a flexible material flow is needed that can not...
Growing interest in Cooperative Driving within the field of Intelligent Transport Systems (ITS) put forth novel concepts for both enhanced sensing and advanced solution making. Although various approaches deal with advanced solution making, none of the concepts consider the conflict situation as a holistic situation comprising defined end states and trajectories towards them. We propose a novel algorithm...
The V2V communication is a promising technology aiming at the growing demands on safety, comfort and efficiency. A variety of research projects demonstrate the expandability of the V2V communication across the boundaries of current industry standards. The authors divide the expandability into two key aspects: collective scene description and cooperative maneuvers. This article combines the expandability...
This paper proposes a novel method on dynamic trajectory planning for intelligent vehicle driving under traffic environment with uncertainties. The statistical characteristics of traffic vehicle motion are first analyzed with a traffic vehicle model, in which the inputs are considered to be random variables with certain probability distribution. Therefore the output of the model can be calculated...
We describe a variable-velocity trajectory planning algorithm for navigating car-like robots through unknown, unstructured environments along a series of possibly corrupted GPS waypoints. The trajectories are guaranteed to be kine-matically feasible, i.e., they respect the robot's acceleration and deceleration capabilities as well as its maximum steering angle and steering rate. Their costs are computed...
Prior autonomous navigation systems focused on the demonstration of the technological feasibility. But as the technology evolves, improving user experience through learning expert's or individual's driving pattern emerges as a promising research direction. As a first step toward this goal, we investigate methods to learn from human demonstrations in urban scenarios without any environmental disturbances...
Recently, Honda Eco Mileage Challenge, which is one of the most important contests in the world to encourage high-efficient car and environmental protection, mainly has been attracted by the communities of mechanism engineering, control system, vehicle engineering and computer science, etc. Generally speaking, the final score of HEMC contest is mainly related to the number of the firing in the whole...
A methodology to estimate the energy consumption of an electric vehicle is presented. An approach to create a driving cycle based on data extracted from road planning software is developped; it is used to forecast the total cycle energy consumption. Results are compared to the ones obtained from the corresponding actual driving cycle. The influence of road elevation is taken into. Results match with...
In this paper, a cooperative driver model for a multi-agent traffic simulation is proposed. The model combines maneuver-based trajectory planning of the vehicles with a cooperative conflict resolving. The proposed model is able to provide a safe drive in complex traffic situations at the highest possible speed. The idea of the model and its feasibility have been verified in complex scenarios such...
In this paper a generic framework for sampling-based partial motion planning along a reference path is presented. The sampling mechanism builds on the specification of a vehicle model and a control law, both of which are freely selectable. Via a closed-loop forward simulation, the vehicle model is regulated onto a carefully chosen set of terminal states aligned with the reference path, generating...
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