Off-Road Fast Navigation Ground Vehicle Speed Planning Using Range Data

Federal highways and state roads in Malaysia are sites of most traffic accidents. One contributing factor is the lack of or low visibility of road signage at dangerous bends or road corners. It is very important to have safety warning signage at strategic locations to warn drivers on conditions or hazards ahead by cautioning maximum allowable vehicle speed limit. However, signage boards alone by themselves are not enough. The relevant authorities have added flashing beacons to enhance visibility but the availability of on-grid power supply often hinders their installation. This is now a non-issue with the advent of solar power. With emerging flashing beacon signage scattered over a wide area, there is an operational need to monitor their performance status remotely for timely effective maintenance and repair. This paper describes the development of a smart self-diagnostic algorithm for a wirelessly monitored autonomous solar powered highway flashing beacon.

Because of its nonlinear discharge characteristics, the residual electric energy of a battery remains an open problem. As a result, the reliability of electric scooters or electric vehicles is lacking. To alleviate this problem and enhance the capabilities of present electric scooters or vehicles, we propose a state-of-charge learning system that can provide more accurate information about the state-of-charge or residual capacity when a battery discharges under dynamic conditions. The proposed system is implemented by learning controllers, fuzzy neural networks, and cerebellar-model-articulation-controller networks, which can estimate and predict nonlinear characteristics of the energy consumption of a battery. With this learning system, not only could it give an estimate of how much residual battery power is available, but it also could provide users with more useful information such as an estimated traveling distance at a given speed and the maximum allowable speed to guarantee safe arrival at the destination

S the hydraulic motor, in most applications, absorbs only a small proportion of the available power for acceleration and the balance for controlling the load, it is well suited for automatic control systems requiring fast response and accurate control. The hydraulic motor is capable of delivering or absorbing a large amount of power within a small, light package, and can be readily adapted to a wide range of installations. Because of its light weight, it requires less mechanical support than other types of equal rating. As part of the control system, the speed of the motor can be easily regulated by variable displacement pumps or metering valves. Using these components in combination with lowpower electrical torque motors and pilot valves, remotecontrolled systems can be readily obtained with large power amplification. In addition, the high sensitivity in the lower power ranges affords a high degree of accuracy. The amount of torque that the hydraulic motor will develop is proportional to its displacement and the fluid pressure applied or developed. This torque is independent of the speed at which the motor is rotating. The limit on the torque available for a given size motor depends, in turn, upon the allowable pressure in the system. While the pressure limit is usually set by mechanical design, it is sometimes limited to control the maximum torque developed in the system. At present, hydraulic motors are manufactured to deliver from 15 to 24,000 in.-lb at 1000 psi. Motors in both aircraft and industrial designs are available for pressures up to 5000 psi. Some design information of particular interest to servo system design engineers is given in Table I. The ratings listed are theoretical and refer to the motors operated at no-load. Certain items such as acceleration and time constant will, of course, be modified by the characteristics of the load. Selection of the correct hydraulic motor for a particular application should be carefully made if optimum response is to be obtained. General rules can be followed, but the final choice must depend upon detailed calculations. The motor, however, must be capable of meeting these three basic conditions : (1) The speed range (ratio of the maximum to the minimum speed) that the motor is capable of must be greater than that required by the load. (2) The maximum allowable speed of the hydraulic motor must be greater than the maximum speed required of the load multiplied by the gear ratio. (3) The motor must supply more torque than the sum of that required by the load (as reflected through the gear train) and that required to accelerate the hydraulic motor. Speed range is the first operating characteristic that should be considered. Hydraulic motors have a minimum smooth speed of about 10 rpm, regardless of motor size. Hydraulic motor speed range is then the ratio of the maximum rated speed of the motor divided by 10 rpm. For standard production aircraft type motors, this ratio varies from 910:1 for the smallest to 312:1 for the largest. In many applications, components can be designed to reduce the minimum speed and thereby extend the speed range by a considerable margin over these figures. The speed range, therefore, determines the maximum motor sizes that can be used for a particular application. If the horsepower requirements are greater than that of the motor selected on the basis of speed range, then two or three motors must be used in parallel. The limiting 10 rpm speed also regulates the minimum gear ration that can be used. For example, if a slow speed of 0.36 deg/sec or 0.06 rev/min is required of the load, the gear ratio for this application is 10/0.06 or 167. Speed range and slow, smooth speed thus determine the maximum motor size and the minimum gear ratio. Actual r^draulic motor size will be determined from the horsepower, acceleration, and speed requirements of the load. Generally, the horsepower controls the minimum motor size while the speed determines the maximum that can be used. The selection of a hydraulic motor for a particular application can be made by the use of the graphs shown in Fig. 1. To use the graphs, the horsepower required by the load and the ratio of the required load acceleration to load velocity must be known. By entering the graph with the horsepower, the displacement can be determined where the horsepower line intersects with a point on the selected acceleration/ velocity curve. Anj^ motor which has a displacement greater than this amount is suitable for the application, providing it meets the speed range requirements of the load. Size of the hydraulic motor for a particular application can be selected by the use of the graphs and the speed range criteria. Where two or more motors are suitable, further calculation should be made to select the one which gives the best response. Experience has shown, however, that the smallest size motor will generally give the maximum response.

The location of highway signs has a significant impact on timely route-finding and also on avoiding potential driver confusion. This paper proposes an approach based on three-dimensional spatial analysis to determine the best attributes for signs and traffic flow concerning the visibility of signs. The position, height and perceived area of signs; maximum speed limit; and size of cars were utilized as indicators. Traffic flow was simulated using the Nagel-Schreckenberg model, while other vehicles were considered as dynamic obstacles. The performance of the proposed approach was evaluated in a case study by designing different scenarios. The results reveal that the proposed method can be used as an appropriate tool for evaluating the visibility of existing signs along highways and for determining the optimal place and height for new signs in three-dimensional, based on several parameters such as the maximum allowable speed, traffic flow, average density, and type of vehicles.

The establishment of speed limit zones on roads plays a role in ensuring driving safety, but speed limit zones are also a kind of traffic bottleneck, can also cause traffic congestion. In order to study the traffic flow characteristics of the speed limit area, based on the NaSch traffic flow model of the cellular automata, a traffic flow model suitable for the road section with double speed limit zone was established, and the influence of the maximum allowable speed and the length of the speed limit zone on the traffic flow was simulated and analyzed. It is concluded that the smaller the maximum speed allowed in the speed limit zone and the longer the speed limit zone, the smaller the traffic flow on the road and the smaller the average speed of vehicles, indicating that these two are important factors affecting road capacity.

The problem of analytical synthesis of the control acceleration of an unmanned aerial vehicle (UAV) of a multirotor type is being solved in relation to a light quadrocopter with a high flight duration. The optimal control is analytically determined for a given minimized quality functional in the form of the minimum time required to transfer the UAV from a given initial to a given final position in space. A mathematical model of the movement of the UAV mass center in a given plane relative to the earth's surface is considered. A feature of the proposed technique is the solution of the problem of maximum speed (forced control) based on the consideration of the laws of kinematics of uniformly accelerated motion of a rigid body. For given characteristics of the maximum allowable speed and control acceleration of the UAV, the moments of switching of the control signal are analytically calculated, which can be implemented in the UAV autopilot. This allows, in contrast to classical methods for solving the problem of forced control, to get rid of the need to solve a two-point boundary value problem and consider additional transversality conditions. The computer simulation of the obtained analytical results in the form of processes of changing the control acceleration, as well as the UAV motion parameters, has shown the efficiency of the proposed technique and the prospects for its use at the initial stage of the synthesis of the UAV control system.

In the research reported in this paper, we propose to overcome the unavailability of Global Positioning System (GPS) using combined information obtained from a scanning LADAR rangefinder on an Unmanned Ground Vehicle (UGV) and a LADAR mounted on an Unmanned Aerial Vehicle (UAV) that flies over the terrain being traversed. The approach to estimate and update the position of the UGV involves registering range data from the two LADARs using a combination of a feature-based registration method and a modified version of the well-known Iterative Closest Point (ICP) algorithm. Registration of range data thus guarantees an estimate of the vehicle's position even when only one of the vehicles has GPS information. Additionally, such registration over time (i.e., from sample to sample), enables position information to be maintained even when both vehicles can no longer maintain GPS contact. The approach has been validated by conducting systematic experiments on complex real-world data.

This paper presents the application of evolutionary learning techniques for improving performance of robot navigation. The goal is to build an intelligent control algorithm that drives the robot in an unknown environment at the maximum allowable speed, while avoiding obstacles and keeping its rate of turns to a minimum. The robot controller is based on an artificial neural network that takes inputs from range sensors and produces outputs to control the drive motors. The ANN is evolved using a simple genetic algorithm. Two different evolutionary learning approaches are evaluated. In the first approach synaptic weights of the network are evolved, while in the second one the adaptation rules of the synapses are evolved. At the end of the evolutionary processes, both solutions resulted in best performing controllers, that can avoid collisions while maximizing linear speed and minimizing turning.

Collaborative robotics relies on a safe physical interaction between robot and operator. However, even if compliance with safety standards is assured, other kind of dangers like psychological stress can be neglected or improperly considered. It has been proven that working and sharing workspace with robots can be psychologically stressing for the operator. Further, small and medium-sized enterprises inherently lack highly skilled workers in. These two factors are identified as risks to the acceptance and usage of collaborative robots. In order to overcome these issues, we developed, implemented and validated a new toolbox and graphical user interface for collaborative robots to allow unskilled workers to easily and automatically plan psychologically less-stressful trajectories. This method assures smooth movements and maximum allowable speeds. This work introduces the toolbox with collaborative robots of Universal Robots, though is general and applicable to other manufacturers .

Energy usage has been an important concern in recent research on online scheduling. In this paper we extend the study of the tradeoff between flow time and energy from the single-processor setting [8, 6] to the multi-processor setting. Our main result is an analysis of a simple non-migratory online algorithm called CRR (classified round robin) on m ≥ 2 processors, showing that its flow time plus energy is within O(1) times of the optimal non-migratory offline algorithm, when the maximum allowable speed is slightly relaxed. This result still holds even if the comparison is made against the optimal migratory offline algorithm (the competitive ratio increases by a factor of 2.5). As a special case, our work also contributes to the traditional online flow-time scheduling. Specifically, for minimizing flow time only, CRR can yield a competitive ratio one or even arbitrarily smaller than one, when using sufficiently faster processors. Prior to our work, similar result is only known for online algorithms that needs migration [21, 23], while the best non-migratory result can achieve an O(1) competitive ratio [14].The above result stems from an interesting observation that there always exists some optimal migratory schedule S that can be converted (in an offline sense) to a non-migratory schedule S' with a moderate increase in flow time plus energy. More importantly, this non-migratory schedule always dispatches jobs in the same way as CRR.

This paper presents SmartYatra, an intelligent road-safety framework that integrates driver-behaviour profiling and vehicle-condition monitoring to reduce the risk of accidents. Road accidents are a major concern worldwide, claiming countless lives and leaving countless others injured, and a significant number of them are due to unsafe and reckless driving behaviours combined with poor vehicle conditions. This paper introduces an intelligent road-safety system aimed at reducing such road accidents dynamically by profiling the driver’s behaviour and monitoring the vehicle's condition in real time, which are then used to regulate the maximum allowable speeds tailored to the vehicle in use, thereby ensuring safe driving on the roads. The system also provides instant alerts when there are unsafe driving events and generates weekly performance reports that summarise driver behaviour and vehicle-condition scores, thereby promoting safer driving habits and proactive vehicle maintenance. The results obtained from a simulated environment demonstrated the effectiveness of the system in reducing unsafe driving habits and events, as well as in enhancing road-safety metrics. The accuracies of around 90% were achieved in driver profiling, and experiments benchmarked against rule-based telematics and intelligent speed assistance (ISA) show up to a 78% reduction in overspeed exposure for aggressive profiles (≈52% for normal profiles), achieved using comfort-aware advisory limits, with an overall improvement of 17% in unsafe-event detection and 8% in adaptive-speed accuracy compared with these baseline methods; absolute cruising speeds remain unaffected when compliant. It employs a weighted-scoring algorithm that first computes a driver behaviour score (Bd) from sensors and a vehicle condition score (Vc) from simulated diagnostic parameters. These are fused into a safety score (Sc = αBd + βVc), which dynamically determines the maximum safe speed (Ms) for each trip segment. The design is edge-first, offline-capable, and low-bandwidth, enabling real-time advisory control on commodity devices with minimal back-haul. It establishes a foundation for further improvement and development of intelligent transport systems, such as driver fatigue detection and autonomous vehicle compatibility. This system therefore represents a significant step toward minimising fatal accidents on the road and in maximising and fostering a safer driving environment.

Maintenance of the rail track plays an important role in the policies that promote railway transport in the European Union. Each member state has its own railway infrastructure manager that is regulated by the standards set by the European Committee for Standardization (CEN). The standards define three levels for the track geometric quality: the alert limit (AL), the intervention limit (IL), and the immediate action limit (IAL). In the United States, the Federal Railroad Administration (FRA) manages the railroad safety and national rail transportation policy. They classify nine classes of tracks depending on the maximum allowable speed for freight and passenger trains; each classification has its own track geometric limits from nominal values. Usually, track-survey cars are used to measure the parameters of the geometric quality of the tracks in long sectors, whereas traditional surveying methods (TSMs) or an automated measuring system based on a track-surveying trolley assisted by a robotic total...

The results of the investigations of the dual-stage cathode positioning system with more than 150 mm motion range and ±1 μm positioning accuracy are presented. The maximum allowable speed of the second stage actuator, securing the integrity of the cathode surface, of 10 mm/s was determined experimentally. The dynamic model of the cathode-probe system allowed to explore the dynamics of the interaction force and the dependencies of their character on the viscous friction. Ill. 6, bibl. 6 (in English; summaries in English, Russian and Lithuanian).

<div>The power battery cooling system of a hybrid electric vehicle is composed of a fan and duct assembly with its inlet positioned inside the vehicle cabin. For the prototype vehicle considered in this work, the air inlet is positioned on the package tray due to limited feasible choices. When the battery temperature is over rated limit, the cooling fan starts to operate to cool the battery system. Propelled by the fan in the cooling system, the air in the passenger compartment enters the duct inlet, and rushes through the air duct to reach the battery pack to fulfill the intended cooling function. In this case, the rear seat occupants could clearly perceive the existence of an annoying whirring noise. In this paper, the characteristics of the battery air cooling system and its working principles are briefly described. The air inlet noise generation mechanism and its frequency characteristics are then analyzed. It is found that the fan noise is the prominent contributor to the inlet noise perceived by the occupants. To resolve the issue, the directionality of the inlet noise is modified by implementing a cap structure over the inlet opening, and the reduction of the inlet noise is achieved by placing sound-absorbing material in the duct. In addition, since the background noise inside the passenger cabin increases with the increase of the vehicle speed, based on the sound masking principle, the fan speed is controlled optimally such that the fan operates at its maximum allowable speed subject to the condition that the fan noise is being masked. Finally, the on-road subjective evaluations show that the inlet noise from the battery cooling system could hardly be perceived by rear seat occupants under all normal vehicle operating conditions.</div>

Autonomous unmanned ground vehicles (UGVs) are beginning to play a more critical role in military operations. As the size of the fighting forces continues to draw down, the U.S. and coalition partner Armed Forces will become increasingly reliant on UGVs to perform mission-critical roles. These roles range from squad-level manned-unmanned teaming to large-scale autonomous convoy operations. However, as more UGVs with increasing levels of autonomy are entering the field, tools for accurately predicting these UGVs performance and capabilities are lacking. In particular, the mobility of autonomous UGVs is a largely unsolved problem. While legacy tools for predicting ground vehicle mobility are available for both assessing performance and planning operations, in particular the NATO Reference Mobility Model, no such toolset exists for autonomous UGVs. Once autonomy comes into play, ground vehicle mechanical-mobility is no longer enough to characterize vehicle mobility performance. Not only will vehicle-terrain interactions and driver concerns impact mobility, but sensor-environment interactions will also affect mobility. UGV mobility will depend in a large part on the sensor data available to drive the UGVs autonomy algorithms. A limited amount of research has been focused on the concept of perception-based mobility to date. To that end, the presented work will provide a review of the tools and methods developed thus far for modeling, simulating, and assessing autonomous mobility for UGVs. This review will highlight both the modifications being made to current mobility modeling tools and new tools in development specifically for autonomous mobility modeling. In light of this review, areas of current need will also be highlighted, and recommended steps forward will be proposed.