Limitations of the effectiveness of Weigh in Motion systems

Ryguła, Artur; Brzozowski, Krzysztof; Maczyński, Andrzej

doi:10.1515/eng-2020-0020

Cited by 9 publications

(8 citation statements)

References 19 publications

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“…The practical use of WIM systems for direct enforcement will require them to be highly reliable in terms of the data they record. It is worth noting that currently even the most modern WIM stations do not achieve 100% efficiency [ 27 ]. In this paper, attention has been paid to the influence of both the trajectory and the dynamics of driving through a WIM station on the signals generated by the sensors.…”

Section: Discussionmentioning

confidence: 99%

Influence of Trajectory and Dynamics of Vehicle Motion on Signal Patterns in the WIM System

Ryguła

Maczyński

Brzozowski

et al. 2021

Sensors

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This paper presents the analyses of the signals recorded by the main sensors of a WIM test station in the cases of abnormal runs (i.e., runs with the changes of trajectory or the dynamics of vehicle motion). The research involved strain gauges which are used for measuring the weight of vehicles, inductive loops, as well as piezoelectric sensors used, inter alia, to detect twin wheels and to determine where a vehicle passes through a station. Since the designers intend the station to be able to implement the direct enforcement function, the selection of runs deviating from the normative ones constitutes an important issue for the assessment of the measurement reliability. The study considered the location of the trajectory of the runs, the dynamics (acceleration/braking) and the trajectory changes. The change in the amplitude and the value of the signal recorded by the strain gauges as a function of the location (position) of the contact between sensor and tires is a noteworthy observation which indicates the need to monitor this parameter in automatic WIM systems. Other tests also demonstrated the influence of the analysed driving parameters on the recorded results. However, by equipping the WIM station with a set of duplicate strain gauges, the measurement errors of the gross weight and axle loads are normally within the accuracy limits of class A(5) stations. Only in the case of accelerating/decelerating, does the error in measuring the load of a single axle reach several per cent.

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Section: Discussionmentioning

confidence: 99%

Influence of Trajectory and Dynamics of Vehicle Motion on Signal Patterns in the WIM System

Ryguła

Maczyński

Brzozowski

et al. 2021

Sensors

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“…The works [9] revealed violations related to oversized vehicle dimensions in line with the overloading of vehicles by business actors. This significantly contributes to the road surface's deterioration and threatens road safety [10]. Besides that, [11] suggested limiting vehicle overloading, especially on low-speed road sections in high-temperature regions.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

“…IRI -pavement smoothness (in/mile); v -average speed (mph); V -local roughness variances. Furthermore, the percentage change in fuel consumption against the roughness level and average vehicle speed can be calculated using equation (10):…”

Section: Table 1 Maximum Allowable Loadmentioning

confidence: 99%

Revealing the impact of losses on flexible pavement due to vehicle overloading

Miftahulkhair,

Arifin,

Sutikno

2024

EEJET

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Pavement overload has become a significant concern in Indonesia due to its damaging effects on the pavement system, where most roads use flexible pavements. Meanwhile, overloading is also typical in other developing countries, causing everything from damage to accidents to the detriment of road users and operators. The current problem is that there is no definite knowledge of handling these overloaded vehicles, which has adverse effects. Therefore, this study aims to reveal the impact of losses caused by overloaded vehicles on flexible pavement. This research uses vehicle traffic load data to examine actual conditions in the field, which are converted to axle load values for each vehicle and used to determine pavement condition using the truck factor approach, mechanistic-empirical design, pavement smoothness level, and the impact of overloading due to fuel consumption by vehicles on flexible pavement. The results show that overloaded vehicles harm the flexible pavement. The increase in truck factor values for all vehicles in overloaded vehicles beyond the maximum allowable load results in more damage to the flexible pavement with an increase in truck factor values up to 83 %. The effect of overloading can be mitigated by increasing the thickness of the asphalt layer and the modulus of asphalt, so it is essential to pay attention to the quality of asphalt in anticipation of this overloading. To anticipate the overload phenomenon, it was found that the thickness of the asphalt overlay in the range of 170–205 mm could mitigate this detrimental effect. In addition, overloading affects the flexible pavement roughness and vehicle fuel consumption. Increased roughness and fuel consumption will increase road maintenance costs and affect driving comfort and safety. In addition, excessive fuel consumption can pollute the surrounding environment

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“…The impact of ODOL vehicles, in addition to causing road damage (Ryguła et al, 2020), also causes damage to other infrastructure such as bridges, ship damage in cases of crossings and causes traffic accidents (Ghisolfi et al, 2019;Alkhoori & Maghelal, 2021). Accident cases involving ODOL vehicles have also occurred a lot.…”

Section: Introductionmentioning

confidence: 99%

Operational Data Analytics of Over Dimensional and Overloaded Truck in Indonesia

Budiharjo¹,

Andika²,

Fitriani³

et al. 2022

cset

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Over Dimension and Overload (ODOL) vehicles are one of the factors that cause road conditions to be easily damaged and potholes and can cause the risk of traffic accidents. ODOL vehicles are considered very detrimental to road infrastructure and increase the risk of accidents, inefficiency due to damaged road conditions, and air pollution because of excess exhaust gases. Road damage due to ODOL also triggered an increase in the budget for the maintenance of national roads, toll roads, and provincial roads, with an average of Rp 43.45 T per year. Based on data from the National Police Corps from the Integrated Road Safety Management System (IRSMS) regarding accidents in 2018, ODOL trucks are one of the biggest contributors to traffic accidents. This study aims to determine the causes of vehicle overload and over dimension. The method used is to use the triangulation method. Triangulation of techniques means that researchers use different data collection techniques to obtain data from the same source. The results showed a relationship between vehicle modification and ODOL violations which were proven using Chi-square analysis. The chi-square value is 55,259 with a p-value of 0.000 at a significance level of 1%. This shows a significant relationship between vehicle modification and Over Dimension and Overload (ODOL) vehicle violations.

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Limitations of the effectiveness of Weigh in Motion systems

Cited by 9 publications

References 19 publications

Influence of Trajectory and Dynamics of Vehicle Motion on Signal Patterns in the WIM System

Influence of Trajectory and Dynamics of Vehicle Motion on Signal Patterns in the WIM System

Revealing the impact of losses on flexible pavement due to vehicle overloading

Operational Data Analytics of Over Dimensional and Overloaded Truck in Indonesia

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