scholarly journals The Effect of Vehicle and Road Conditions on Rollover of Commercial Heavy Vehicles during Cornering: A Simulation Approach

2021 ◽  
Vol 13 (11) ◽  
pp. 6337
Author(s):  
Nurzaki Ikhsan ◽  
Ahmad Saifizul ◽  
Rahizar Ramli
Keyword(s):  
Coefficient Of Friction ◽  
Weight Coefficient ◽  
Lateral Acceleration ◽  
Heavy Vehicle ◽  
Vehicle Speed ◽  
Simulation Approach ◽  
Heavy Vehicles ◽  
Vehicle Class ◽  
Vehicle Weight ◽  
Gross Vehicle Weight

Heavy vehicles make up a relatively small percentage of traffic volume on Malaysian roads compared to other vehicle types. However, heavy vehicles have been reported to be involved in 30,000–40,000 accidents yearly and caused significantly more fatalities. Rollover accidents may also incur cargo damages and cause environmental or human disasters for vehicles that carry hazardous cargos if these contents are spilled. Thus, in this paper, a comprehensive study was conducted to investigate the effects of vehicle and road conditions on rollover of commercial heavy vehicles during cornering at curved road sections. Vehicle conditions include the heavy vehicle class (based on the axle number and vehicle type), speed and gross vehicle weight, while road conditions include the cornering radius and coefficient of friction values. In order to reduce the risks involved in usage of actual heavy vehicles in crash experiments, a simulation approach using a multi-body vehicle dynamic software was applied in this study, where the verified virtual heavy vehicle model was simulated and the output results were extracted and analyzed. The results showed that a maximum of 40% and a minimum of 23% from the total number of simulations resulted in an unsafe condition (indicated as failed) during the simulations. From the unsafe conditions, two types of rollover accidents could be identified, which were un-tripped and tripped rollovers. The heavy vehicle speed was also found to have a strong correlation to the lateral acceleration (to cause a rollover), followed by gross vehicle weight, coefficient of friction and cornering radius, respectively.

scholarly journals HEAVY VEHICLE MULTI-BODY DYNAMIC SIMULATIONS TO ESTIMATE SKIDDING DISTANCE

2018 ◽  
Vol 13 (1) ◽  
pp. 23-33 ◽  
Author(s):  
Mahdieh ZAMZAMZADEH ◽  
Ahmad Abdullah SAIFIZUL ◽  
Rahizar RAMLI ◽  
Ming Foong SOONG
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Coefficient Of Friction ◽  
Heavy Vehicle ◽  
Accident Reconstruction ◽  
Heavy Vehicles ◽  
The Road ◽  
Gross Vehicle Weight ◽  
Multi Body ◽  
Body Dynamic

The skid mark is valuable for accident reconstruction as it provides information about the drivers’ braking behaviour and the speed of heavy vehicles. However, despite its importance, there is currently no mathematical model available to estimate skidding distance (SD) as a function of vehicle characteristics and road conditions. This paper attempts to develop a non-linear regression model that is capable of reliably predicting the skidding distance of heavy vehicles under various road conditions and vehicle characteristics. To develop the regression model, huge data sets were derived from complex heavy vehicle multi-body dynamic simulation. An emergency braking simulation was conducted to examine the skidding distance of a heavy vehicle model subject to various Gross Vehicle Weight (GVW) and vehicle speeds, as well as the coefficient of friction of the road under wet and dry conditions. The results suggested that the skidding distance is significantly affected by Gross Vehicle Weight, speeds, and coefficient of friction of the road. The improved non-linear regression model provides a better prediction of the skidding distance than that of the conventional approach thus suitable to be employed as an alternative model for skidding distance of heavy vehicles in accident reconstruction.

Simulation and Analysis on the Effect of Gross Vehicle Weight on Braking Distance of Heavy Vehicle

2014 ◽  
Vol 564 ◽  
pp. 77-82 ◽  
Author(s):  
Airul Sharizli ◽  
Rahizar Ramli ◽  
Mohamed Rehan Karim ◽  
Ahmad Saifizul Abdullah
Keyword(s):  
Vehicle Dynamics ◽  
Travel Speed ◽  
Heavy Vehicle ◽  
Road Accidents ◽  
Heavy Vehicles ◽  
Braking Performance ◽  
Vehicle Weight ◽  
Gross Vehicle Weight ◽  
Braking Distance ◽  
Distance Data

Increasing number of fatalities caused by road accidents involving heavy vehicles every year has raised the level of concern and awareness on road safety situation in developing countries like Malaysia. This study attempts to explore the influences of vehicle dynamics characteristics such as vehicle weight and travel speed on its safety braking distance. This study uses a kind of complex virtual prototyping software to simulate vehicle dynamics and its braking performance characteristics. The software was used to generate braking distance data for various vehicle types under various loads and speed condition. The generated data was grouped according to GVW and then analyzed by two-way ANOVA to evaluate its relationship to braking distance. The finding of this study implies that the speed and GVW of various vehicle classifications has a significant effect to the heavy vehicle braking distance.

scholarly journals Rollover Warning for Articulated Heavy Vehicles Based on a Time-to-Rollover Metric

2004 ◽  
Vol 127 (3) ◽  
pp. 406-414 ◽  
Author(s):  
Bo-Chiuan Chen ◽  
Huei Peng
Keyword(s):  
Neural Network ◽  
Simple Model ◽  
Design Process ◽  
The Other ◽  
Roll Angle ◽  
Heavy Vehicle ◽  
Vehicle Speed ◽  
Heavy Vehicles ◽  
The One ◽  
Accuracy Problem

A Time-To-Rollover (TTR) metric is proposed as the basis to assess rollover threat for an articulated heavy vehicle. The TTR metric accurately “counts-down” toward rollover regardless of vehicle speed and steering patterns, so that the level of rollover threat is accurately assessed. There are two conflicting requirements in the implementation of TTR. On the one hand, a model significantly faster than real-time is needed. On the other hand, the TTR predicted by this model needs to be accurate enough under all driving scenarios. An innovative approach is proposed in this paper to solve this dilemma and the design process is illustrated in an example. First, a simple yet reasonably accurate yaw∕roll model is identified. A Neural Network (NN) is then developed to mitigate the accuracy problem of this simple model. The NN takes the TTR generated by the simple model, vehicle roll angle, and change of roll angle to generate an enhanced NN-TTR index. The NN was trained and verified under a variety of driving patterns. It was found that an accurate TTR is achieved across all the driving scenarios we tested.

Effects of Heavy Vehicle Speeds on the Structure and Vibration of Bridges

1999 ◽  
Author(s):  
Giuseppe Sammartino ◽  
Farid Amirouche ◽  
Zhen L. Chen ◽  
Ming L. Wang
Keyword(s):  
Dynamic Load ◽  
Structural Damage ◽  
Linear Time ◽  
Active Suspension ◽  
Random Excitation ◽  
Dynamic Loads ◽  
Load Force ◽  
Heavy Vehicle ◽  
Vehicle Speed ◽  
Heavy Vehicles

Abstract Heavy Vehicles speeds and dynamic loads are critical factors to bridge’s structure fatigue and rapid deterioration. The proposed paper addresses the modeling and simulation of dynamic loads of heavy vehicles, such as trucks and buses, on bridges and the effects of their speed on frequency response. In light of the above analysis, this paper proposes a method on how to minimize the structural vibrational of the combined vehicle and bridge system using semi-active suspension control. The vehicle dynamic load is minimized through an optimization scheme to yield an impact force with negligible bridge lateral deflection. The dynamic coupling between the vehicle and bridge are studied by examining the modes that are most likely to be excited by the vehicle speed and the roughness of the bridge surface. The models consist of a bridge and a heavy vehicle. The bridge is modeled as continuos, lightly damped beam with different supports defined by the boundary conditions. The vehicle is a multi-degree of freedom (MDOF) system undergoing motion in one plane. The methods of solution consist of a simple supported beam that closely simulates the first three beam modes of the Kishwaukee Bridge in Rockford, Illinois. The surface of the bridge generates some random excitation that serves as input to the vehicle, this is commonly known as the roughness of the bridge surface. The heavy vehicle is moving from left to right of the simply supported beam. The system is analyzed and optimized by semi-active control algorithms. Close form numerical solution is obtained by a set of second order differential equations for the bridge-vehicle system. Experimental data obtained from the vibration testing of Kishwaukee Bridge (Illinois) were collected and validated with a FEM model. Only the first three beam modes were used due to the experimental limitations and the actual structural condition of the bridge. Using MATLAB a simulation is obtained by inputting the linear time-variant equations and optimizing the system. Simulations of bridge vertical motion under different dynamic load conditions were examined and the results of bridge structure response were analyzed by comparing the effects of passive versus semi-active suspension controls. The method shows effectively how we can reduce the dynamic load force magnitude and its frequency of impact. The latter is usually associated with structural damage caused to the bridge.

Parameters Identification for Simplified Yaw Model of Articulated Heavy Vehicle

2013 ◽  
Vol 765-767 ◽  
pp. 387-391 ◽  
Author(s):  
Zhi Gen Nie ◽  
Chang Fu Zong
Keyword(s):  
Genetic Algorithm ◽  
Dynamic Characteristics ◽  
Simulation Study ◽  
Dynamic State ◽  
Steering Wheel ◽  
Actual State ◽  
Heavy Vehicle ◽  
Vehicle Speed ◽  
Heavy Vehicles ◽  
Independent Variables

In order to accurately characterize the lateral dynamic characteristics of articulated heavy vehicle, 3-dof simplified yaw model of articulated heavy vehicles is established and key parameters of models are identified by genetic algorithm. MAPs of key parameters, which the vehicle speed and steering wheel angle are independent variables for, are formed using the key identification parameters. Simulation study of dynamic state is carried out by the MAPs of key identification parameters and 3-dof simplified yaw model. That simulation result compared with Trucksim data indicates that key parameters can be accurately identified and the MAPs of key identification parameters satisfies the need of characterizing the actual state of vehicle.

scholarly journals The effect of vehicle weight on the sound produced by transverse rumble strips

2019 ◽  
Vol 13 (2) ◽  
pp. 5031-5047
Author(s):  
Z. Haron ◽  
N. Darus ◽  
K. Yahya ◽  
N. Mashros ◽  
Z. Jahya ◽  
...  
Keyword(s):  
Sound Pressure Level ◽  
Sound Pressure ◽  
Sound Level ◽  
Pressure Level ◽  
Heavy Vehicles ◽  
Vehicle Type ◽  
Vehicle Weight ◽  
Traffic Calming ◽  
Noise Data ◽  
Gross Vehicle Weight

Transverse rumble strips (TRS) are commonly used as traffic calming measure in the vicinity of premises. So far research have been extensively concentrated on the effect of vehicle type and speed on the noise produced by TRS, and very little research focused on the effect of vehicle weight.  Do these vehicles produce extremely higher sound level parallel to their heavier weight? This is important as in reality, traffic flow consist of light, medium and heavy vehicles, which are also important sources of noise. This study investigated the effect of vehicle weight, such as gross vehicle weight (GVW) when transited on TRS, particularly with emphasis on impulsivity content. The objectives of this research were to: (1) determine the effect of GVW on noise generation when a vehicle transits on TRS and (2) assess the effect of GVW on the impulsivity of noise. Data from vehicles with weight between 800 kg - 8000 kg were collected based on previous research where these vehicles were tested on speed values of 30km/h and 50km/h. It was found that when the vehicles transited on TRS, the generated noise was strongly related with the vehicle weights (R2=0.71) higher than those normal road surface (R2=0.49). However, the changes of noise were not well represented by direct relation. It was found that TRS can increase and decrease the sound pressure level, depending on GVW, but on average, TRS can increase the sound pressure level by 1 dBA. Despite that, TRS was found to have an impulsive characteristic within the tested speed range. This finding can facilitate the authority to evaluate the environmental noise produced by TRS.

scholarly journals Research on Model Predictive Control for Automobile Active Tilt Based on Active Suspension

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 671
Author(s):  
Jialing Yao ◽  
Meng Wang ◽  
Zhihong Li ◽  
Yunyi Jia
Keyword(s):  
Load Transfer ◽  
Ride Comfort ◽  
Active Suspension ◽  
Path Tracking ◽  
Roll Angle ◽  
Lateral Acceleration ◽  
Vehicle Speed ◽  
Model Predictive Controller ◽  
Advantages And Disadvantages ◽  
Predictive Controller

To improve the handling stability of automobiles and reduce the odds of rollover, active or semi-active suspension systems are usually used to control the roll of a vehicle. However, these kinds of control systems often take a zero-roll-angle as the control target and have a limited effect on improving the performance of the vehicle when turning. Tilt control, which actively controls the vehicle to tilt inward during a curve, greatly benefits the comprehensive performance of a vehicle when it is cornering. After analyzing the advantages and disadvantages of the tilt control strategies for narrow commuter vehicles by combining the structure and dynamic characteristics of automobiles, a direct tilt control (DTC) strategy was determined to be more suitable for automobiles. A model predictive controller for the DTC strategy was designed based on an active suspension. This allowed the reverse tilt to cause the moment generated by gravity to offset that generated by the centrifugal force, thereby significantly improving the handling stability, ride comfort, vehicle speed, and rollover prevention. The model predictive controller simultaneously tracked the desired tilt angle and yaw rate, achieving path tracking while improving the anti-rollover capability of the vehicle. Simulations of step-steering input and double-lane change maneuvers were performed. The results showed that, compared with traditional zero-roll-angle control, the proposed tilt control greatly reduced the occupant’s perceived lateral acceleration and the lateral load transfer ratio when the vehicle turned and exhibited a good path-tracking performance.

Perceptions of Log Truck Weight Regulations Among Loggers and Forest Industry in Georgia, USA

2021 ◽  
Author(s):  
Joseph L Conrad
Keyword(s):  
The State ◽  
Transportation Costs ◽  
Forest Industry ◽  
Public Infrastructure ◽  
Truck Traffic ◽  
Telephone Surveys ◽  
Southern States ◽  
Vehicle Weight ◽  
Gross Vehicle Weight ◽  
Truck Weight

Abstract Georgia and other southern states have far lower gross vehicle weight (GVW) limits for log trucks than other US regions and other countries. Low GVW limits result in high hauling costs and truck traffic. In 2020, including tolerances, five-axle log tractor-trailers were allowed 38,102 kg (84,000 lb) GVW in Georgia. Telephone surveys of 30 loggers and 32 forest industry representatives from the state of Georgia were conducted to measure perceptions of weight regulations and assess support for alternative weights and configurations. The four alternatives included five axles, 39,916 kg (88,000 lb); six axles, 41,277 kg (91,000 lb); six axles, 45,359 kg (100,000 lb); and seven axles, 45,359 kg (100,000 lb) GVW. The majority of loggers and forest industry representatives stated that GVW limits for log trucks were too low. The average preferred GVW limits were 39,621 kg (87,350 lb) and 40,545 kg (89,387 lb) for loggers and forest industry, respectively. Loggers and forest industry supported the five-axle 39,916 kg (88,000 lb) configuration whereas many loggers opposed both 45,359 kg (100,000 lb) configurations. Loggers, forest industry, and policymakers should work to modernize weight laws to reduce hauling costs, maintain or improve safety, and protect public infrastructure. Study Implications Increasing gross vehicle weight (GVW) limits in combination with adding axles to tractor-trailers has been demonstrated to reduce both timber transportation costs and damage to public roads. This study found that loggers and forest industry supported additional GVW but were hesitant to support configurations that would necessitate upgrading log truck fleets. If Georgia is to make its weight limits competitive regionally and internationally, it will be necessary to clearly communicate the benefits of heavier trucks with more axles to skeptical loggers.

scholarly journals EVALUATING THE EFFECT OF HEAVY VEHICLES ON TRAFFIC PARAMETERS BY USING HEAVY VEHICLE FACTOR

2018 ◽  
Vol 6 (4) ◽  
pp. 95-104
Author(s):  
Parthkumar Patel ◽  
H.R. Varia
Keyword(s):  
Travel Time ◽  
Traffic Flow ◽  
Road Traffic ◽  
Freight Transport ◽  
Heavy Vehicle ◽  
Mixed Traffic ◽  
Heavy Vehicles ◽  
Highway Traffic ◽  
Ideal Situation ◽  
The Impact

Safe, convenient and timely transportation of goods and passengers is necessary for development of nation. After independence road traffic is increased manifold in India. Modal share of freight transport is shifted from Railway to roadways in India. Road infrastructures continuously increased from past few decades but there is still need for new roads to be build and more than three forth of the roads having mixed traffic plying on it. The impact of freight vehicles on highway traffic is enormous as they are moving with slow speeds. Nature of traffic flow is dependent on various traffic parameters such as speed, density, volume and travel time etc. As per ideal situation these traffic parameters should remain intact, but it is greatly affected by presence of heavy vehicle in mixed traffic due to Svehicles plying on two lane roads. Heavy vehicles affect the traffic flow because of their length and size and acceleration/deceleration characteristics.  This study is aimed to analyse the impact of heavy vehicles on traffic parameters.

scholarly journals Comparative Analysis of Effects of Heavy Vehicles on Roads in Southern and Northern Nigeria

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
C. C. Osadebe ◽  
H. A. Quadri
Keyword(s):  
Northern Region ◽  
Design Guidelines ◽  
Traffic Volume ◽  
Southern Region ◽  
Heavy Vehicle ◽  
Heavy Vehicles ◽  
Passenger Cars ◽  
The Road ◽  
Equivalency Factors ◽  
On The Road

The prevalence of flexible pavement deterioration in the country has been adduced largely by highway researchers to trucks or heavy vehicles carrying much in excess of permitted legal limits. This study investigated levels of deterioration of Abuja-Kaduna-Kano road (Northern region) and Port Harcourt-Enugu road (Southern region) caused by heavy vehicles through a 14 day traffic counts conducted at 5 strategic points each in the Northern and Southern regions. Traffic data generated were analyzed with AASHTO Design Guidelines (1993) to evaluate Equivalent Single Axle Loads (ESALs) and Vehicle Damage effects on the road. The Traffic Volume, Average Daily Traffic (ADT), and Heavy Vehicle per day (HV/day) were estimated to be 2,063,977; 147,427; and 12,246 respectively in the Northern region, while in the Southern region they were estimated to be 750,381; 53,670; and 20,951 respectively. Motorcycles, Passenger cars, Mini-buses/Pick-ups, and Heavy vehicles constitute 18.7%, 49.7%, 23.3% and 8.31% of the total traffic volume respectively in the Northern region while in the South they constitute 4.6%, 30.1%, 26.2% and 39.1% respectively. ESALs were estimated according to AASHTO Design Guidelines in the Northern and Southern regions as 547,730 and 836,208 respectively. An average Load Equivalency Factors (LEFs) of 3.43 and 3.02 were estimated for each heavy vehicle plying the Northern and Southern roads respectively and this could explain some failures (alligator cracks, potholes, depressions, linear or longitudinal cracks along the centre line amongst others) inherent on the road.

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