Speed Of Heavy Vehicles Research Articles

Exploring the impact of right-turn safety measures on E-bike-heavy vehicle conflicts at signalized intersections

A major safety hazard for e-bike riders crossing an intersection is encountering heavy vehicles turning right in the same direction, which often results in severe casualties. Recently, some cities in China have implemented right-turn safety improvement treatments (i.e., right-turn yielding rules and right-turn warning facilities) at intersections to reduce the occurrence of such accidents. However, the risk perception and behavior of e-bike riders and heavy vehicle drivers dynamically change during the right-turn interaction process, and the safety effects of different right-turn safety measures remain unclear. This study aims to investigate the safety effect of right-turn safety measures on E-Bike-Heavy Vehicle (EB-HV) right-turn conflicts at signalized intersections. The right-turn conflicts and potential influencing factors are extracted from aerial video data, including characteristics of right-turn warning facilities, characteristics and behavior of e-bike riders and heavy vehicle drivers, environmental factors, and traffic-related factors. Moreover, traffic conflict indicators such as the Time to Collision (TTC), Post Encroachment Time (PET), and Jerk are selected and calculated. Multinomial and binary logit models are used to estimate and analyze the EB-HV right-turn conflict severity and drivers yielding behavior. The results reveal that: (a) right-turn warning facilities can decrease the probability of slight and severe EB-HV right-turn conflicts, while the presence of law enforcement cameras could prompt heavy vehicle drivers to comply with the yielding rules and adopt more cautious behavior; (b) increased heavy vehicle speed and acceleration before turning right have strong correlation to illegitimate yielding behavior of the driver and higher EB-HV right-turn conflict severity; and (c) aggressive behavior of e-bike rider increases the severe conflict probability, especially at intersections without right-turn warning facilities. Based on the study findings, several practical implications are suggested to reduce the risk of EB-HV right-turn conflicts, enhance the effectiveness of right-turn safety measures, and improve crossing safety for e-bike riders.

Effect of traffic speed on noise generated by vehicles motorized in front of the Karya Bhakti Pratiwi Dramaga Bogor hospital

Noise is one of the environmental health problems in big cities. The 1988 WHO report as submitted by the Indonesian Health Service (1995), states that 8% - 12% of the world's population has suffered from the effects of noise. The activity of residents of the city of Bogor a suburb of the capital city of Jakarta in Indonesia is relatively high. Along with the economic development in the city of Bogor, the number of motorized vehicles operating both private and public vehicles has also increased. The purpose of this study was to determine the average speed of motorized vehicles that pass through the Dramaga highway, especially in front of the Karya Baki Pratiwi Hospital, and also to determine the level of noise generated due to the speed of motorized vehicles. The method used in this study is a quantitative method by calculating the number of vehicles and the average speed of vehicles and data analysis. The data taken is vehicle speed data every 15 minutes and noise levels using a Sound Level Meter (SLM). In this study, three SLMs were used which would be placed at three points. The results showed that the speed of the vehicle affects the noise level which is quite significant. The results of data analysis show that the effect of speed on noise is 24%, where the equation is as follows, y=69.505 – 0.395x1 +0, 148x2 + 0.535x3. This equation means that if there is no decrease in motorcycle speed, light vehicle speed, and heavy vehicle speed, the noise level in SLM1 is 69.505 dBA. However, if there is an increase in the number of light vehicles by 0.148, a decrease in the number of motorcycles and large vehicles is obtained by 0.14, the noise level will increase by 0.395 dBA.

Rollover Investigation of Two-Axle Heavy Vehicle Based on Load Transfer Ratio with Vehicle and Road Condition: A Simulation Approach

Commercial heavy vehicle is commonly used to transport goods and people efficiently and safely. A previous study has shown a number of gross vehicle weight (GVW) and speed violations recorded in selected areas in Malaysia, and two-axle single unit truck (SUT) is the most commercial heavy vehicle type that violated the weight and speed regulation. Moreover, accidents involving heavy vehicles result in severe traffic disruption and fatalities to other road users due to heavy vehicle size and capability to carry huge amounts of goods. Thus, the objective of this paper is to investigate the correlation and effect of the vehicle and road condition on the two-axle SUT rollover during cornering on the curved road using the simulation approach. The verified two-axle SUT model is simulated using IPG-TruckMaker® with different GVW, speed, and coefficient of friction values while the cornering radius, driver behaviour and load’s center of gravity remain constant. A correlation based on performance indices is established, and it is found that the heavy vehicle speed has a strong correlation to the lateral load transfer to cause a rollover followed by GVW and coefficient of friction, respectively.

Investigation of Factors Associated with Heavy Vehicle Crashes in Iran (Tehran–Qazvin Freeway)

With the growing demand for transportation and cargo between cities, the proportion of heavy vehicles in freeway traffic has been increasing in Iran and worldwide during the past decade. The impact of heavy vehicles on crash severity has long been a concern in the crash analysis literature for the prevalence of crashes in freeway traffic. The purpose of this study is to investigate the contribution of heavy vehicles to freeway crashes and uncover other causal factors. Using the comprehensive crash and traffic data from the Qazvin–Tehran freeway in Iran, from 2013 to 2018, 1350 crashes involving heavy vehicles were extracted regarding the weather conditions, weekday, main cause of the crash, driver gender, and culprit side. Considering crash severity calculation, the applied coefficient weights in this study for a person were considered as 3 for an accident resulting in injury and 5 for a fatal crash. A binary logit model was estimated using the data to determine if there was a significant correlation between recognized factors and the likelihood of the crash. The logit modeling results clearly illustrate important relationships between various risk factors and occupant injury, in which heavy vehicles were recognized as one of the most important factors in this study. Other variables associated with crash severity were weather conditions and driver attention. Results indicate that the number of crashes is simultaneously dependent on the total vehicle volume and average speed of heavy vehicles.

Effectiveness of Climbing Lanes for Slow-Moving Vehicles When Riding Uphill: A Microsimulation Study

Long uphill stretches of single-carriageway rural roads with one lane per travel direction may reduce the Level of Service (LoS), due to the decreased speed of heavy vehicles. In those circumstances, a slowdown of traffic, resulting in the formation of platoons, may be generated due to the difficulty of performing overtaking maneuvers safely. To solve this critical issue, an additional (climbing) lane for slow vehicles may be included in the road platform. This study aims to evaluate the effectiveness of such climbing lanes in a real case in Italy (National Road n. 4 “Via Salaria”—around 44+000 km). Using a microsimulation model implemented in VISSIM, the study analyzes speeds and travel times, delays, and queuing waiting times, comparing the Actual Scenario (AS) without climbing lanes, with two counterfactual scenarios: the first one (CS1) with three stretches of climbing lanes, and the second one (CS2), with just two stretches, in which the first two additional lanes of CS1 are merged together. The obtained results confirm the effectiveness of installing climbing lanes on road sections with the described characteristics, and the potential of microsimulation models also to carry out such kind of evaluations.

Applying Two-parameter Weibull Distribution to Model Stochastic Capacity of Arterial Roads During Peak Hours due to Changing Proportion of Heavy Vehicles

Despite the increasing number of heavy vehicles (HVs) on the road, little attention is paid to the impact of HVs on traffic flow. Due to their different physical characteristics (length and size) and operational characteristics (acceleration and deceleration) compared to other vehicles, HVs have a physical and psychological impact on the traffic around them. On the other hand, many studies done on changes in road capacity yield a single value of road capacity. In this study, however, the road capacity is analyzed with probability distributions. This study found that the road capacity increases since HV reduction has a constant value with 85% and 50% cumulative probabilities. On major roads, reducing HV by 10%, 20%, 30% increases road capacity by 3-4%, 8% and 11-12% respectively. Lower HVs ratios are less likely to reduce road capacity. However, the speed of HV and other modes does not directly affect the cumulative probabilities. In addition, as the ratio of HV increases, the speed difference between vehicle types decreases. This study is limited to rush hour traffic flows so that a further study can consider the total duration of mixed traffic conditions.

The Influence of Side Friction on Speed-Mixed Flow Behavior on Arterial Roads in Tourism Area in Bali

The arterial roads in tourism areas show a lack of control over activities that occur on the arterial roadsides. This study constructs a speed-flow behavior model to analyze the influence of side friction events under mixed traffic flows on arterial road performances in Bali. This event is dominated by the entry and exit of vehicles from road access points. The study results show that in friction conditions, the speed of the motorcycle is significantly affected by the presence and speed of other motorcycles and light vehicles, but in base conditions, it is significantly affected by the presence and speed of all types of vehicles. Meanwhile, the speed of light vehicles is significantly influenced by the presence and speed of motorcycles and other light vehicles. A further study is required to analyze the influence of motorized vehicles on the selection of heavy vehicle speed on arterial roads. Due to side frictions, a decrease in road capacity (pcu/hour) was found between 14.37% and 26.60% while a decrease in speed was between 13.79% and 76.19%. These show a significant side friction problem on arterial roads in tourism areas. The road control policy, particularly on roadside access is needed for these arterial roads.

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

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.

Speed violation analysis of heavy vehicles on highways using spatial analysis and machine learning algorithms

With the development of technology in the world, vehicles that reach high speeds are produced. In addition, with the increase of road width and quality, faster and more comfortable transportation can be provided. These developments also increase the speed violation rates of road vehicles. Drivers who violate speed limits can endanger both their own lives and the lives of others. Speed violations, of especially heavy vehicles, involve much greater risks than that of light vehicles. Heavy vehicles can cause more serious losses of lives and property in accidents, compared to the ones caused by light vehicles, as they can carry much more freight or passengers than light vehicles. In this study, data regarding the speed violations committed by heavy vehicles in Turkey, were used. Speed violations were divided into 10 classes according to the intensity of speed violation rates. After this process, all provinces were classified according to support vector machines (SVM), naive bayes (NB) and k-nearest neighbors (KNN) algorithms. When the accuracy values and error scales of all three algorithms are examined, it has been determined that the algorithm that gives the most accurate results is the NB algorithm. Based on the classification of this algorithm, speed violation density maps of types of heavy vehicles in Turkey were created by using spatial analysis. According to the density maps, the provinces with the highest speed violations were identified. In the results, it was determined that the rate of heavy vehicle speed violation was highest in the cities such as Erzurum, Konya, and Muğla. Later, these cities were examined in terms of heavy vehicle mobility. At the end of this study, measures were proposed to reduce these violations in cities where speeding violations are intense. Material and moral damages can be prevented, to a great extent, with the implementation of recommendations of policymakers which can reduce speed violations.

A self-calibrating model to estimate average speed from AADT

Transport practitioners need a universally applicable speed prediction model to estimate average speeds on any road. Average annual speed is a key input to the economic assessment of transport infrastructure where reliable estimates of future average speeds are necessary to calculate economic costs and benefits. The relationship between Annual Average Daily Traffic (AADT) and average annual speed was investigated on higher-order roads across South Africa, revealing a high level of variability in this correlation at different locations. This variation is influenced by road characteristics, such as alignment and cross-section, complicating the formulation of a universal speed prediction model. Two novel speed prediction models are proposed in this article that use AADT to forecast future average annual speed. The speeds of heavy vehicles and light vehicles can be estimated separately, as well as the average speed of all vehicles simultaneously. Both models are self-calibrating, accounting for the variation in the AADT-speed relationship. This calibration step is unique to speed prediction models and increases the reliability of these models to estimate future average speeds considerably. Furthermore, self-calibrating average annual speed prediction models are universally applicable and will simplify economic assessment of transport infrastructure.

Vehicle-bridge coupling dynamic response of a box bridge after reinforcement with prestressed CFRP

The dynamic response of vehicle bridge coupling before and after strengthening with post-tensioned carbon fiber reinforced polymer (CFRP) is analyzed. To obtain a better dynamic response of vehicle bridge coupling, the theory of vehicle moving load is deduced and transformed. To obtain the dynamic response of the vehicle bridge coupling before and after the post-tensioned CFRP reinforcement, a numerical model of the vehicle bridge coupling before and after the post-tensioned CFRP reinforcement is established, and the vertical acceleration time history curve and vertical displacement time history curve of the 1/4, 1/2, and 3/4 sections of the side span and the middle span of the bridge before and after post-tensioned CFRP reinforcement are obtained under different speeds of heavy vehicles. The results show that with the increase in vehicle speed, the vertical displacement of the bridge has almost no change, but the increase in the vertical acceleration peak value is obvious, which results in a faster arrival of the vertical displacement and the vertical acceleration peak value and also causes the amplitude of the vertical acceleration of the bridge to increase greatly, and the vertical acceleration increase in the side span is significantly larger than that in the middle span. Post-tensioned CFRP can effectively reduce the vertical displacement and acceleration of the bridge, but there are some deficiencies in reducing the vertical displacement of the bridge. With the increase in speed, the effect of the post-tensioned method is better.

HEAVY VEHICLE MULTI-BODY DYNAMIC SIMULATIONS TO ESTIMATE SKIDDING DISTANCE

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.

Determination of Sample Size for Speed Measurement on Urban Arterials

Estimation of speed is an important task for various traffic engineering analyses like crash analysis, establishing speed zones, evaluation of traffic signal locations and so on. Past research on the sample size estimation was focused on finding the number of GPS based probe vehicles required. However, there are limited studies on the sample size determination of speeds obtained using video-graphic survey. Large samples increases the chances of finding the significant difference but sometimes it leads to wastage of resources. Inadequate sample size may lead to inaccurate results. Hence sample size determination is often an important step in traffic engineering studies. This paper attempts to determine the sample size based on variability and traffic conditions. An evaluation of the sample size determination such as ITE and Hybrid methods were also carried out. From the data analysis, it was found that there was not much variation in speeds for given vehicle type and location. The mean and variance in speeds obtained from first ten speed measurements for a vehicle type are not statistically different from those obtained after one hour of data collection. For some locations, where the proportion of heavy vehicles and flow were low, statistically stable mean speeds of heavy vehicles could not be obtained even after hour of data collection.

Traffic Conflict Technique-Based Setting Method of Freeway Climbing Lane

Speed of heavy vehicles is greatly reduced on upgrade sections due to their insufficient climbing capability, thus having great impact on traffic safety. Setting climbing lanes can solve this problem effectively. Considering China’s traffic composition and operational status, this paper proposed the traffic conflict technique-based setting method of freeway climbing lanes in order to set foundations for climbing lanes with the goal of promoting traffic safety. Based on large freeway upgrade section data and actual traffic characteristics, the paper built simulation models with VISSIM. 220 schemes were simulated by setting different road and traffic conditions of models. The paper then used Surrogate Safety Assessment Model (SSAM) to calculate traffic conflict, analyzed the influence of slope, slope length and mixed rate of heavy vehicles on traffic safety on upgrade sections. Finally, taking the reduction extent of the collision rate after setting climbing lanes as an indicator, this paper used K-means to classify the effectiveness level of the climbing lanes. The paper found the setting position and basis of the climbing lanes. The findings of this paper can provide support to effective decision making with regards to constructing future climbing lanes.

Effects of Track Elasticity on Wheel-Rail Dynamic Performance of Heavy Haul Railway

Two vehicle-track dynamics models on heavy haul railway are established in two conditions of rigid track and elastic track. And the impact of track elasticity on the wheel-rail dynamics performance was analyzed using models. The results show that the critical speed of heavy vehicles and wheel-rail dynamic indexes, such as wheel-rail lateral force and wheel-rail vertical force decreased on elastic track compared with rigid track. However, other dynamic indexes, including derailment coefficient and lateral displacement of wheelsets increased on elastic track. And the wheel-rail wear indexes are some differences on two tracks.

Relationship between heavy vehicle speed limit and fleet fuel consumption on minor roads

This paper investigates the traffic-related effects of a proposal to increase the speed limit from 40 mile/h to 50 mile/h, for heavy goods vehicles greater than 7.5 tonnes, on single carriageway roads. A ‘microscopic’ single carriageway traffic simulation is developed by combining the ‘enhanced intelligent driver model’ with a single carriageway gap-acceptance passing model. Fuel consumption estimates are made using engine characteristic maps and a ‘fuel optimal’ gear selection scheme, where vehicle trajectories from the traffic simulations are taken as input drive-cycles. Traffic congestion and fleet fuel consumption are specifically addressed, though implications regarding passing behaviour and traffic safety are also noted. Results indicate that the proposed 50 mile/h heavy goods vehicles speed limit would reduce traffic congestion by over 37% and increase fleet fuel consumption by approximately 0.5 L/100 km.

Slip ramp design for dedicated truck lanes using microscopic traffic simulation

Dedicated Truck Lanes (DTL) are planned in the United States along freight-intensive corridors, namely Corridors of the Future. In rural areas along these corridors, slip ramps will provide access to heavy vehicles between the truck-only lanes (TOL) and the general purpose lanes (GPL) to subsequently enter and exit the facility using an interchange. This paper examines the distance between the slip ramp and an interchange required by heavy vehicles to enter and exit the facility using a microscopic traffic simulation program, VISSIM. This distance consists of a merge, link, and a diverge segment. The procedure for determining this distance included (a) examining the acceleration/deceleration characteristics of vehicles, (b) specifying the parameters in VISSIM based on vehicle characteristics and driver behavior, (c) coding and simulating the traffic on DTL in VISSIM, (d) analyzing the speed–flow relation for passenger and heavy vehicles for the various lengths of merge, link, and diverge segments on the GPL, slip ramps, merge, and diverge segments of TOL, and (e) determining the slip ramp distance to (and from) the interchange for level, upgrade, and downgrade. To determine the different segment lengths, a rotatable central composite design (RCCD) was used to generate a reasonable number of cases required for simulation. Simulation of peak period traffic on level grades indicated that the lengths of segments were directly proportional to the average speed of heavy vehicles. As the slip ramp distance from and to the interchange depended on the lane change behavior of drivers, a sensitivity analysis was performed for the safety distance reduction factor (SDRF), the main lane change parameter in VISSIM. This paper provides state departments of transportation with design recommendations for slip ramp design for the Corridors of the Future project. The paper also provides a unique application of microscopic simulation to highway facility design.

Highlighting Dynamically Loaded Pavement Sections with Profile Indices

The interaction between road surface roughness and heavy vehicles results in dynamic wheel loading (DWL), which increases pavement damage. The magnitude of DWL is dependent on the level of surface roughness and its characteristics and the properties and speeds of heavy vehicles. The measurement of DWL under normal operating conditions is costly, and the estimation of the resultant pavement damage is difficult because of the great variation in heavy vehicle fleet characteristics operating on the network. Additional damage caused by DWL is reflected in increased pavement deterioration over time. Deterioration is apparent in changes in the surface profile characteristics, which have a determining influence on dynamic loading and the degree of its spatial repeatability. The suitability of a number of profile indices as indicators of dynamically loaded pavement sections was assessed. Several regression models were developed with different profile indices used as predictors of different measures of pavement damage caused by DWL. The international roughness index and heavy articulated truck index were among the indices tested. The magnitudes of the simulated DWL were represented by such measures as dynamic load coefficient and dynamic aggregate force coefficient. This approach could help road authorities identify sections that are subject to high DWL and to take appropriate measures to reduce the impact. The heavy articulated truck index, measured with the dynamic aggregate force coefficient, proved to be the best predictor of pavement damage caused by DWL.

Empirical analysis of gross vehicle weight and free flow speed and consideration on its relation with differential speed limit

Most highly motorized countries in the world have implemented different speed limits for light weight and heavy weight vehicles. The heavy vehicle speed limit is usually chosen to be lower than that of passenger cars due to the difficulty for the drivers to safely maneuver the heavy vehicle at high speed and greater impact during a crash.However, in many cases, the speed limit for heavy vehicle is set by only considering the vehicle size or category, mostly due to simplicity in enforcement. In this study, traffic and vehicular data for all vehicle types were collected using a weigh-in-motion system installed at Federal Route 54 in Malaysia. The first finding from the data showed that the weight variation for each vehicle category is considerable. Therefore, the effect of gross vehicle weight (GVW) and category of heavy vehicle on free flow speed and their interaction were analyzed using statistical techniques.Empirical analysis results showed that statistically for each type of heavy vehicle, there was a significant relationship between free flow speed of a heavy vehicle and GVW. Specifically, the results suggest that the mean and variance of free flow speed decrease with an increase GVW by the amount unrelated to size and shape for all GVW range. Then, based on the 85th percentile principle, the study proposed a new concept for setting the speed limit for heavy vehicle by incorporating GVW where a different speed limit is imposed to the heavy vehicle, not only based on vehicle classification, but also according to its GVW.

Influence of Heavy Vehicles on Japan Two-Lane Highway Speed and Follower Flow Characteristics

The effects of heavy vehicles become more pronounced in two-lane highway facilities with passing restrictions since vehicles in a platoon do not have any other choice but to follow the leaders’ choice of speed, which is usually below their desired speed levels. Furthermore, platoon lengths are expected to be longer than usual, affecting level of service indicators such as follower density and average travel speed. This study aims to make a preliminary analysis of the influence of heavy vehicle on such facility types in Japan. Detector data were analyzed for two different time periods — peak and weekday. The speed of heavy vehicles has a direct effect on follower speed and follower density was found to become more sensitive to heavy vehicle percentage as flow rate increases. Average speed was also found to be more sensitive to heavy vehicle presence on upgrades, especially during the evening period.