Varying Vehicle Speed Research Articles

Dense-graded asphalt pavement macrotexture measurement using tire/road noise monitoring

Data collection and the associated automated methods are one of the main building blocks of pavement management systems. One of the main problems associated with automated data collection methods is the high cost of the equipment involved. The aim of this research is to develop a cost-effective system for dense-graded asphalt pavement macrotexture monitoring. To this end, a system based on the tire/road noise, utilizing microphones and employing cepstral signal processing has been developed. The proposed method is compared with the current state of the art PCA based method and is shown that the precision error of the proposed method is about 7%, which outperforms the previous state of the art. To enhance the precision of the cepstral method for the vehicle speed variation amongst the collected dataset, the combination of the cepstral signal processing with Gaussian mixture models is proposed which results in the final precision error of 8%.

Lane departure avoidance by man-machine cooperative control based on EPS and ESP systems

The ability to avoid lane departure has become an important feature for development of driving assistance technology, and the design of lane departure avoidance system (LDAS) which can achieve cooperative control with human driver is still a challenge. This paper presented a new lane departure decision algorithm along with main parameters of the electric power steering (EPS) and electronic stability program (ESP) system’s sensor. During normal situations, steering control based on EPS system was involved to avoid lane departure. However, when the vehicle reached the handling limits, both steering and braking control collaborated together to avoid lane departure based on EPS and ESP systems. Due to the time varying vehicle speed and the uncertainty of tire cornering stiffness, a gain scheduling brake controller was designed based on the energy-to-peak performance indicator, and an upper monitor was designed for activation the braking controller to ensure comfortable ride. Because the relationship between the lane departure degree with a lateral offset in the single- point preview and the driver torque could not be accurately described, a man-machine cooperative control fuzzy observer for the LDAS was designed. In order to accomplish smooth switching for driving mode to ensure ride comfort, a switching criterion was proposed. The proposed method was evaluated via numerical simulation by CarSim/Simulink. A hardware-in-the-loop test platform was set up, and the effectiveness of the proposed control strategy was compared via the driver-in-the-loop experiment. The obtained results show that the proposed man-machine cooperative control strategy not only can return the vehicle to the normal lane effectively, but also realize smooth switching from man-machine cooperative control to driver control.

An Explicit Nonlinear Model Predictive ABS Controller for Electro-Hydraulic Braking Systems

This paper addresses the development and Hardware-in-the-Loop (HiL) testing of an explicit nonlinear model predictive controller (eNMPC) for an antilock braking system (ABS) for passenger cars, actuated using an electro-hydraulic braking unit. The control structure includes a compensation strategy to guard against the performance degradation due to actuation dead times, identified by experimental tests. The eNMPC is run on an automotive rapid control prototyping unit, which shows its real-time capability with comfortable margin. A validated high-fidelity vehicle simulation model is used for the assessment of the ABS on a HiL rig equipped with the braking system hardware. The eNMPC is tested in seven emergency braking scenarios, and its performance is benchmarked against a proportional-integral-derivative (PID) controller. The eNMPC results show: 1) the control system robustness with respect to the variations in tire-road friction condition and initial vehicle speed; and 2) consistent and significant improvement of the stopping distance and wheel slip reference tracking, with respect to the vehicle with the PID ABS.

A data-driven method for estimating wheel flat length

ABSTRACT Wheel flat is one of the most common defects occurring to railway wheels. The relevant standards have specified the operational limits for wheel flats in terms of the length. Therefore, the information on the flat length is required for maintenance decision. In this sense, this paper proposes a data-driven method not only for detecting wheel-flats but also for estimating the flat length, which can be implemented for onboard condition monitoring. Firstly, A multibody dynamics model of a Y25-tank-wagon with a wheel flat of a variable length is established to generate the axlebox acceleration data at variable vehicle speeds. Then, based on the selected simulation data points, a Kriging surrogate model (KSM) is constructed to model the axlebox acceleration response to different lengths of wheel flats and different vehicle speeds. Finally, a particle swarm optimisation (PSO) based algorithm is applied to calculate the exact wheel-flat length by feeding the measured vehicle speed and the acceleration signal into the KSM model. The proposed method is validated by a field test, for which a wheel flat with a length of 20 mm was artificially produced. Simulation and experimental results have demonstrated that this method can estimate the length of wheel flats.

Passenger Car Equivalency Factors Under Platooning Conditions

Heterogeneous traffic existing in developing countries such as in India is characterized by vehicles with very diverse static and dynamic characteristics. The various types of vehicles, other than cars in the heterogeneous traffic stream can be converted into equivalent passenger cars so as to express the heterogeneous traffic volume in terms of corresponding passenger car units (PCU). The subject of PCU has been studied on intercity, urban roads and at intersections controlled by traffic signals quite extensively. But studies on PCU values of vehicles on the downstream of signalized intersections have not been explored so far. The arterial links existing at downstream of traffic signals are designed to progress traffic with varying acceleration and deceleration. Vehicular interactions which take place within platoons and between platoons along such arterials are the predominant factors affecting vehicular progression. Hence there is a need to derive PCU values of vehicles along signalized corridors. The present study analyzes traffic flow data collected at the downstream of a signalized urban arterial to determine PCU values for various types of vehicles based on three methods. One method is the homogenisation coefficient method whereas the other one is the speed-area ratio method. The third one is a new method based on speed differential and area ratio is proposed in this paper which considers the effect of speed variation of vehicles for estimating PCU values. In this study, PCU values estimated based on speed differential-area ratio concept are found to be more logical compared to other methods as this method could incorporate the considerable variation in static and dynamic characteristics of various vehicles which progress along the downstream of intersections.

Prediction of plastic deformation and wear in railway crossings – Comparing the performance of two rail steel grades

Railway crossings are subjected to a severe load environment leading to damage and degradation of rail profiles. The damage is the result of the high magnitudes of contact pressure and slip generated in the wheel–rail contacts during each wheel transition between wing rail and crossing nose. In this paper, numerical predictions of the long-term accumulation of plastic deformation and wear are presented and compared for two rail grades used in crossings. The comparison is performed using a framework that includes simulations of dynamic vehicle–track interaction, wheel–rail contact and rail damage. A load sequence generated by means of Latin hypercube sampling, taking into account variations in worn wheel profile, vehicle speed and wheel–rail friction coefficient, is considered. A Hertzian-based metamodel for wheel–rail normal contact accounting for inelastic material response is used for the simulation of wheel–rail contact. The methodology is demonstrated by calculating the plastic deformation for one cross-section of the crossing nose using an Ohno-Wang cyclic plasticity model, while wear is predicted by means of the Archard model for sliding wear. For the studied conditions and after the simulation of 41400 load cycles, representing an accumulated traffic load of 0.8 MGT, it is concluded that the fine-pearlitic rail grade R350HT experiences half of the ratchetting strain compared to the austenitic hot-rolled manganese steel Mn13. Based on a wear model calibrated for Mn13, the maximum wear of the studied cross-section is about 2% of the maximum plastic deformation.

Research on Local Dynamic Path Planning Method for Intelligent Vehicle Lane-Changing

A local dynamic path planning method is proposed to compensate for the lack of consideration of the movement state of surrounding vehicles, the poor comfort, and the low traffic efficiency when the existing vehicle changes lanes automatically. Firstly, the cubic polynomial is predefined, and the optimal track path is solved. According to the real-time information of environment perception, the model is continuously modified by acquiring real-time information in the course of path planning, and the regional safety of the vehicle is realized. The Carsim and simulink simulation results and actual vehicle verification show that, compared with the traditional nondynamic research method, this method can effectively solve the problem that the vehicle speed variation and the sudden intrusions of the vehicle leading to the compulsory operation of the vehicle during the course of lane-changing. The safety is also improved. In order to ensure the vehicle comfort and stability, the lane-changing time is shortened by 20%, and the efficiency of lane-changing is improved obviously.

Intelligent PD controller design for active suspension system based on robust model-free control strategy

A novel active suspension control design method is proposed for attenuating vibrations caused by road disturbance inputs in vehicle suspension systems. For the control algorithm, we propose an intelligent PD controller structure that effectively rejects online estimated disturbances. The main theoretical techniques used in this paper consist of an ultra-local model which replaces the mathematical model of quarter car system and a new algebraic estimator of unknown information. The measurement of only input and output variables of the plant is required for achieving the reference tracking task and the cancellation of unmodeled exogenous and endogenous perturbations such as roughness road variation, unpredictable variation of vehicle speed and load variation. The performance and robustness of the proposed active suspension algorithm are compared with ADRC control and LQR control. Numerical results are provided for showing the improvement of passenger comfort criteria with model-free control.

Effect of rail pad stiffness on the wheel/rail force intensity in a railway slab track with short-wave irregularity

In this paper, a two-dimensional numerical model is developed to investigate the effect of rail pad stiffness on the wheel/rail force in a slab track with harmonic irregularity. The model consists of a vehicle, nonlinear Hertz spring, rail, rail pad, concrete slab, resilient layer, concrete base, and subgrade. The rail is simulated using the Timoshenko beam element for considering the effects of high-frequency excitation produced by short-wave irregularity. The results obtained from the model are compared with those available in the literature and from the field to prove the validity of the model. Through a parametric study, the effect of variations in rail pad stiffness, vehicle speed, and harmonic irregularity on the wheel/rail force is investigated. For the slab track without any irregularity, the wheel/rail force is at maximum when the vehicle speed reaches the critical speed. As the rail pad stiffness increases, the critical speed increases. When the amplitude of irregularity is high, wheel jumping phenomenon may occur. In this situation, as the vehicle speed and rail pad stiffness are increased, the dynamic wheel/rail force is increased. In the low-frequency range, the wheel/rail force increases as the rail pad stiffness increases. In the high-frequency range, the wheel/rail force increases as the rail pad stiffness is decreased.

Characterization of Dispersion and Ultrafine-particle Emission Factors Based on Near-roadway Monitoring Part I: Light Duty Vehicles

ABSTRACT This paper presents a comprehensive set of ultrafine particles (UFPs) emission factors (EFs) for heavy duty vehicles (HDVs) as a function of vehicle flow rate, speed, and mode of operation (free flow and congestion) using 664 measurements of UFPs, carbon dioxide (CO2), meteorology and traffic conditions near a major roadway (average daily traffic 300,000 day–1). 5-min samples were collected for 2 to 3 hour time period on 60 days between 2015 and 2018. The average traffic-induced concentration of UFPs was 11,300 pt cm–3 for free flow and 12,400 pt cm–3 for congestion. Results demonstrate that HDVs produce significantly more dispersion (30x) than light duty vehicles (LDVs). The additional dispersion from HDVs results in the minimum pollutant concentrations occurring at the highest vehicle flow rate. EFs for UFPs are determined using inverse modeling based on the calculated CO2 dispersion. This eliminates the need to rely on air-quality models to estimate dispersion. The EFs for HDVs range from 4 × 1014 to 20 × 1014 (pt km–1 veh–1). The variations in EFs are correlated with variations in vehicle flow rate and speed. The average UFP EFs for HDVs are significantly higher (3x) for congestion compared to free flow. UFP EFs for HDVs are more sensitive to speed in congestion compare to in free flow conditions. Thus, even a moderate increase in HDVs speed or mitigation of congestion will have a significant impact on lowering UFP concentrations.

Robust active steering control for vehicle rollover prevention

This paper presents a dynamic vehicle rollover model and robust controller for rollover prevention by using a steer-by-wire (SbW) system. Firstly, a linear vehicle dynamic model is derived whose behaviours vary as a function of the time-varying vehicle speed. Next, a load transfer ratio (LTR) model is proposed for measuring the rollover conditions in a vehicle. In particular, the LTR model is generalised based on the conventional one by explicitly considering the rolling motion of sprung mass. Moreover, the relationship of LTR between steering angle and vehicle speed is analysed. To prevent the undesired rollovers, a sliding mode control (SMC) approach is then utilised to design the robust controller for rollover prevention. Finally, simulation results are shown to verify the efficiency of rollover prevention under the proposed controller and its robustness against the vehicle speed and vehicle parameter variations.

Estimating Acceleration and Deceleration Lane Lengths by Analyzing Vehicle Speed Variation of Rest Areas for Drowsy Drivers

Estimating Acceleration and Deceleration Lane Lengths by Analyzing Vehicle Speed Variation of Rest Areas for Drowsy Drivers

An investigation into the effect of parabolic speed hump profiles on ride comfort and driving safety under variable vehicle speeds: A campus experience

This study aims to investigate the effect of parabolic speed hump profiles on ride comfort and driving safety under variable vehicle speeds. To this end, in-situ and simulation tests were carried out in which root-mean-square values were evaluated. Field tests were performed on seven parabolic speed humps within the boundaries of Istanbul Technical University Ayazaga Campus Area. These tests were conducted twice with different loads. Five vehicle speeds were taken into account within the range of 15 km/h to 35 km/h with 5 km/h increments. As in-situ tests focused on the measurement of the vertical acceleration when crossing the speed humps, maximum vertical accelerations and root-mean-square values were recorded by means of an accelerometer and a software. Two sets of parabolic speed hump profiles were considered for the simulation stage and then the results of the field tests and the simulation tests were compared.The results have yielded vehicle speed and parabolic speed hump height as the most important parameters affecting ride comfort and driving safety. It has also been demonstrated that the weight of the vehicle is negatively associated with motorists’ sense of discomfort and an increase in the length of speed humps results in slightly better ride comfort.

Voice Control Tasks on Cognitive Workload and Driving Performance: Implications of Modality, Difficulty, and Duration

The effects of an in-vehicle voice control system (VCS) on cognitive workload and driving performance were evaluated using a driving simulator study with 24 participants. Participants were asked to perform two types of in-vehicle tasks while driving: voice-command based radio and navigation tasks. The tasks were of two difficulty levels (easy, hard) with half of the tasks audio only and the other half audio with a visual display. Cognitive workload was measured using a tactile detection response task (TDRT) and a revised remote detection response task (RDRT). Driving performance was measured using standard deviation of lateral position (SDLP) and standard deviation of vehicle speed. An analysis of covariance for standard deviation of speed was used to examine the effects of VCS display with task duration as the covariate. Three separate mixed models were used to evaluate the variation in SDLP, response time, and misses given VCS tasks and detection response task (DRT) type. No significant differences were observed between TDRT and RDRT, suggesting both methods capture congruent measures of workload and that neither interfere with driving performance. Engagement with each hybrid VCS task was significantly associated with an increase in DRT misses above baseline driving. Additionally, hybrid display tasks had larger variations in vehicle speed and were completed more quickly than equivalent audio only tasks. Increasing values of task duration were associated with greater variation in lateral vehicle position. The results of this study suggest that design of VCSs should consider the modality, temporal components, and difficulty of tasks to reduce cognitive load.

Contact-Point Response for Modal Identification of Bridges by a Moving Test Vehicle

The response of the contact point of the vehicle with the bridge, rather than the vehicle itself, is proposed for modal identification of bridges by a moving test vehicle. To begin, approximate closed-form solutions were derived for the vehicle and contact-point responses, and they were verified by finite element solutions. The contact-point acceleration is born to be free of the vehicle frequency, an annoying effect that may overshadow the bridge frequencies in case of rough surface. From the frequency response function (FRF) of the vehicle with respect to the contact point, it was shown that the contact-point response generally outperforms the vehicle response in extracting the bridge frequencies because it could identify more frequencies. In the numerical simulations, the contact-point response was compared with the vehicle response for various scenarios. It is concluded that in each case, say, for varying vehicle speeds or frequencies, for smooth or rough road surfaces, with or without existing traffic, the contact-point response outperforms the vehicle response in extracting either the frequencies or mode shapes of the bridge.

Microsimulating Heterogeneous Traffic: An Implementation of the Porous Flow Approach

Modelling of traffic flow lacking lane-adherence, with variable vehicle sizes and speeds, is a pressing issue in the simulation field. Commercially available software is not designed for modelling such traffic, which is characteristic of developing countries. A recently developed method is to model traffic as grains of sand moving through a porous medium. This approach is explored and expanded in this work to consider multiple vehicle classes and potential uses in microsimulation. A microsimulation model is developed using an object-oriented approach and compared with existing work in the field. The developed approach, found to fit with the porous flow approach, is shown to properly reflect the traffic flow impacts associated with introducing additional vehicle classes. Fundamental flow diagrams are presented for heterogeneous traffic, which fit a Daganzo approximation. It is determined that several changes are required to the theoretical framework to accurately represent traffic characteristics before viable commercial application.

Toward a M2M-Based Internet of Vehicles Framework for Wireless Monitoring Applications

The Internet of Vehicles (IoV) has become an attractive research topic in the fields of communication networks and information processing due to its wide range of potential applications, including public transportation management, road traffic predication and control, environmental monitoring, and autonomous driving. Most research analyze the IoV’s data collected by dedicated machine-to-machine (M2M)-based platforms. Moreover, due to the lack of field experimental data, data transmission mechanisms from mobile vehicle terminals to the M2M-based platform rarely consider the proper transmission timing according to network performance and traffic conditions. To solve these problems, we propose an open M2M-based framework of wireless monitoring system for IoV. In the proposed framework, we design and implement a prototype of the mobile vehicle terminal. We also define the procedure of data transmission between the mobile vehicle terminal and the M2M-based platform. To prolong the lifetime of the mobile vehicle terminal, energy-efficient data transmission schemes for stopped and running vehicles are proposed, respectively, which reduce the unnecessary data transmission by jointly considering the variation of vehicle speed and received signal strength. We conduct a field experiment to verify the basic functions of the proposed M2M-based IoV monitoring system and the mobile vehicle terminal. Furthermore, the experimental results show that the proposed M2M-based platform with the mobile vehicle terminal enables customized and energy-efficient data delivery.

The influence of vehicle speed changes at mechanistic performance of asphalt mixture

Asphalt mixture is a viscoelastic material. Several factors affect the behavior of a viscoelastic material. Temperature and loading time are the most critical of these parameters. Vehicle speed affects time loading, therefore it’s very important to know the influence of vehicle speed changes in mechanistic performance of bitumen and asphalt mixture with different aggregate gradation types, namely dense graded and gap graded. Based on data of bitumen penetration, bitumen softening point, volume of bitumen, volume of aggregate and volume of voids, mechanistic performance of bitumen and asphalt mixture influenced by vehicle speed changes can be predicted using the software BANDS 2.0. The variation of vehicle speed will be carried out to see its significance. The results of the BANDS 2.0 simulation show that vehicle speed changes influence bitumen stiffness, asphalt mix stiffness and fatigue life asphalt mix. The higher the vehicle speed is, the higher bitumen stiffness and asphalt mix stiffness will be, but fatigue life asphalt mix will be lower. At the same vehicle speed, asphalt mix stiffness of dense graded mixture will be higher than gap graded mixture. The other way for fatigue life asphalt mix.

Shared intelligent optimum route selection through traffic management system in VANET– SIRS

A Vehicular Ad-hoc Network (VANET) consists of the vehicle to vehicle and vehicle to roadside communication. Growing the density of the vehicles on the road causes flooding while transferring packets from a source to one or multiple destinations over a VANET. However, increasing vehicles on road may causes a problem such as redundancy, congestion, collision and increasing delay though receiving emergency warnings. As long as reliable and proficient multi-hop broadcast in vehicular ad hoc networks is challenging one. In the proposed system commence a new protocol which uses the character of elegant route establishment and selection method for transfer information to the destination (dst) with minimum redundancy, delay and highest bits per second delivery. In some environment vehicles are deployed in a dense manner, and it can move at a high speed. Adjacent Access Points (APs) on the road find out route information from their past report gatherings which use a fuzzy logic to select routing conclusion. This approach consists of isolating the whole network area into clusters. Based on which an optimized route is chosen using the input parameters as vehicle density, distance from the adjacent AP, vehicle mobility, receiving signal strength and delay should be jointly measured in the relay node selection. Though, these computation conflicts with each other depend on vehicle mobility. Hence, we employ fuzzy logic to handle this imprecise information to select forwarding vehicles by mutually taking into account of vehicle distance (d), mobility (v) and Receiving Signal Strength (RSS). The selected vehicle can provide an assure data forwarding with a high competence. The performance of the proposed scheme is evaluated on the metrics such as end-to-end delay, packet delivery ratio by varying vehicle speed, and density of vehicles.

On the mathematical modeling of green one-to-one pickup and delivery problem with road segmentation

This paper presents a green one-to-one pickup and delivery problem including a set of new features in the domain of green vehicle routing. The objective here is to enhance the traditional models for the one-to-one pickup and delivery problem by considering several important factors, such as explicit fuel consumption (which can be translated into emissions), variable vehicle speed and road categorization (i.e., urban, non-urban). Accordingly, the paper proposes a mixed integer programming model for the problem. A case study from the Netherlands shows the applicability of the model in practice. The numerical analyses show that the investigated factors has a significant impact on operational-level logistics decisions and the selected key performance indicators. The results suggest that the proposed green model can achieve significant savings in terms of total transportation cost. The total cost reduction is found to be (i) 3.03% by the use of explicit fuel consumption estimation, (ii) up to 10.7% by accounting for variable vehicle speed and (iii) up to 10.5% by considering road categorization. As total cost involves explicit energy usage estimation, the proposed model has potential to offer a better support to aid sustainable logistics decision-making process.