Academic literature on the topic 'VEHICLES’ VOLUME'

In this thesis, the analysis of vehicles' determination of speed and volume in the traffic flow will be discussed by approach time. The analyzation of vehicles' speed and volume done by estimated on macroscopic term of traffic flow in the traffic jam with Extended Kalman Filter (EKF) method. The term of macroscopic views with measured the traffic variable by density the flow rate the flow rate of vehicle and also the vehicle speed's average. In the estimating process, forward difference scheme is implemented to the model and error are measured by Root Mean Square Error. The result showed that the estimation the average of the vehicle’s relative speed in a segment decreased when its volume of vehicle is increased and vice versa.

Emission around intersections has become an issue in the urban traffic network. This paper aims to investigate the impact of pedestrian and nonmotorized vehicle violations on emissions at mixed-traffic flow intersection based on the volumes of vehicles, nonmotor vehicles, and pedestrians. Also, it focuses on the arterial and collector intersections with high vehicle volume and limited space. Running red light and crossing intersection diagonally are two critical violations, accounting for 91.75% of effective violations (interference with vehicles’ operation). In this context, a violation blocking model is developed to estimate the blocking probability for each vehicle based on the volumes of pedestrians and nonmotor vehicles. The model includes two scenarios. (1) Through phase: the violation blocking model of running red light is developed based on the survival curve (the relationship between waiting time and running red light probability). (2) Left-turn phase: the violation blocking model at this phase includes two parts: (i) crossing the intersection diagonally model is developed for the first vehicle and (ii) running red light model is developed for subsequent vehicles. The existing emission model can estimate the emissions based on the blocking positions. In the case study, emissions increase with the vehicle volume approaching the saturated flow rate and the volumes of nonmotor vehicles and pedestrians increasing. Results show that the maximum emission increase of CO (carbon monoxide) for through phase and left-turn phase can reach 16.7% and 36.4%.

The lane-changing behavior is one of the important causes in traffic accident in congest traffic, and many behaviors of change lane affect volume of traffic. When autonomous driving vehicles are running on road with human-driven vehicles, the effects of change lane on traffic are different. In all human-driven vehicles traffic, the vehicle behaviors of changing lane are more competent. When autonomous driving vehicles are running in mixed traffic, the behaviors of changing lane decrease and the volume of traffic increases. However, a few studies have involved the relationship between traffic volume and lane-change behavior. In a sense, the study of this relationship is good for understanding the operation mechanism of mixed traffic. In this paper, we proposed the linear regression model to describe the relationship between traffic volume and lane-change behavior. The model can be used to establish the basic graph model. Here, we used empirical, simulation, and data-driven methods to obtain data and established a multiple linear regression model. First, we empirically study the continuous traffic with all human-driven vehicles. Then, the corresponding simulation model is established, and the availability of the simulation model is proved by data comparison with empirical study. Finally, 9 rounds of simulation experiments are carried out with the established simulation model. The number of autonomous driving vehicles in each round of simulation experiment increases by 10%. Then, we analyze the data of the behaviors of changing lane and the volume of traffic from simulation experiments. The following was found: (1) an increase in autonomous driving vehicle leads to an increase in traffic volume and a slight decrease in lane changing behaviors; (2) the influence of different proportions of autonomous vehicles on the traffic volume of lanes at different locations is slightly different; and (3) the relationships among the rate of vehicles entering lane, the rate of vehicles exiting lane together, and the volume of traffic show obvious linear relationships with the increase in autonomous driving vehicles. We used multiple linear regression models to carry out description, and the obtained parameter value intervals are close under different operating ratios of autonomous vehicles. To sum up, on multilane roads, especially 4-lane urban expressways, autonomous driving vehicles join in the traffic, which can effectively increase the volume of traffic of each lane while reducing vehicle behaviors of changing lane. The relationships between vehicle behaviors of changing lane and the traffic volume in mixed traffic show linear relationships with the increase in autonomous driving vehicles. In the future, we will further study whether this relationship model can be used in discrete traffic flow.

Along with the level of traffic density that crosses the Pinus road, there are several obstacles that cause damage, one of which is the damage that occurs in the road construction section, which is caused by the load of vehicles with excessive loads such as trucks, which further causes damage to the road, namely an increase in volume. heavy traffic every day. Asphalt pavement is generally used on roads that have a fairly dense traffic volume, with the increase in the number of vehicles resulting in damage in a relatively short time than planned. The purpose of this study is to determine the effect of the volume of vehicle types on road damage on asphalt pavement, it can be predicted earlier the value of road damage that will occur, the method used in this study is the method of analyzing vehicle volume on road damage with the regression method. Used to obtain the relationship function with the value of R² (coefficient of determination) which shows the magnitude of the effect of changes in the volume of vehicle types on changes in the value of road damage, this study was carried out on the Pinus road, Palangka Raya City. There is a relationship between the volume of vehicle types and the value of road damage, the results obtained are R² = 0.744 which shows that road damage is influenced by the volume of heavy vehicles, light vehicles and motorcycles with a percentage value of 74.4%. From the results of the equation between heavy vehicles (X1), light vehicles (X2), motorcycles (X3), and the value of road damage Y = 0.159 X1 + 0.034 X2 + 0.017 X3 + 14,189. From these equations it can be described as follows, the regression coefficient (X1) (a) = 0.159 means that a heavy vehicle of 100 vehicles/day will increase the level of road damage by 5.9, the regression coefficient (X2) (b) = 0.034 means a light vehicle of 100 vehicles/day will increase the level of road damage by 3.4, Regression coefficient (X3) (c) = 0.017 means that 100 motorbikes/day will increase the level of damage by 1.7, constant (c) = if there are no vehicles driving passing a road segment, the road will experience road damage of 14,189.

Along with the increase number of employees and pilgrims in Maulana Malik Ibrahim Graveyard from year to year, it certainly has an impact on the increasing volume of vehicles on its parking area. The avaibility of parking area that is not proportional to the volume of vehicles will certainly disrupt the orderliness and comfort of the parking users around Maulana Malik Ibrahim graveyard. The research method used for performance analysis is in the form of field survey by using the data of two wheels and four wheels vehicle parked in that area. In analyzing this parking performance surveyed on July 1st - 5th 2018, it is found that the highest volume of two wheels vehicles is 418 vehicles, with the highest accumulation of 43 vehicles on average the highest duration 209.50 minutes / vehicle, the highest turnover is 0.804, the highest level of parking used is 80.43% and the number of available parking capacity of motorcycles is 230 plots, while the highest number of parking requests is 185 plots. Therefore, the available parking capacity for two wheels vehicle is still quite accommodating the number of vehicles parked. Meanwhile, for four wheels vehicles, it obtained that the highest volume is 442 vehicles, with the highest accumulation of 50 vehicles on average the highest duration of 115.50 minutes / vehicle, the highest turnover is 1,171, the highest level of parking used is 117.14% and the number of available car parking capacity is 140 plots, with highest number of parking requests is 165 plots. Since the number of parking lots is the highest 25 plots, so that the available parking capacity is not enough to accommodate the number of vehicles parked.

When conventional vehicles (eg, methylcellulose and water) impart inadequate physical, chemical, and/or biological properties for proper toxicological assessment of test article formulations, nonconventional vehicles may be considered. Often toxicity data for nonconventional vehicle formulations are limited. Studies were conducted to collect toxicity data from a rodent and a non-rodent species given 2 nonconventional vehicles, Solutol HS15/polyethylene glycol (PEG) 400 and Cremophor RH40/PEG 400, with differing formulations and dose volumes (10 mL/kg for rats; 2 or 5 mL/kg for dogs). In rats, both vehicles caused increase in kidney weights (males only) and decrease in thymic weights (males only) without concurrent microscopic findings; altered urine electrolytes, minimally decreased serum electrolytes (males only), and increased serum total cholesterol (females only) were also present. The Cremophor formulation was also associated with increased serum urea (males only) and urine phosphorus: creatinine. For rats given the Solutol formulation, both genders had decreased urine glucose parameters and males had increased urine volume. In dogs, loose/watery feces and emesis were present given either vehicle, and mucus-cell hyperplasia of the ileum was present given the Solutol formulation. Increased red blood cell mass and decreased urine volume in dogs given 30% Solutol/70% PEG 400 (5 mL/kg/d) were likely due to subclinical dehydration and hemoconcentration. For the Cremophor formulations, dose volume-dependent increased incidence of minimal subepithelial gastric hemorrhage was noted in dogs, and dogs given 5 mL/kg/d showed increased serum urea nitrogen. Overall, regardless of the formulation or dose volume, neither vehicle produced overt toxicity in either species, but the Solutol formulation produced fewer effects in rats. Generally, lower dose volumes minimized the severity and/or incidence of findings.

The research work reported here investigates driving behavior under mixed traffic conditions on high-speed, multilane highways. With the involvement of multiple vehicle classes, high-resolution trajectory data is necessary for exploring vehicle-following, lateral movement, and seeping behavior under varying traffic flow states. An access-controlled, mid-block road section was selected for video data collection under varying traffic flow conditions. Using a semi-automated image processing tool, vehicular trajectory data was developed for three different traffic states. Micro-level behavior such as lateral placement of vehicles as a function of speed, instant responses, vehicle-following behavior, and hysteresis phenomenon were evaluated under different traffic flow states. It was found that lane-wise behavior degraded with increase in traffic volume and vehicles showed a propensity to move towards the median at low flow and towards the curb-side at moderate and heavy flows. Further, vehicle-following behavior was also investigated and it was found that with increase in flow level, vehicles are more inclined to mimic the leader vehicle’s behavior. In addition to following time, perceiving time of subject vehicle for different leading vehicles was also evaluated for different vehicle classes. From the analysis, it was inferred that smaller vehicles are switching their leader vehicles more often to escape from delay, resulting in less following and perceiving time and aggressive gap acceptance. The present research work reveals the need for high-quality, micro-level data for calibrating driving behavior models under mixed traffic conditions.

Since the factories began operating, they had an impact in the form of congestion that occurred on Jalan Sukabumi-Cianjur, precisely in front of the P.T. Glostar Indonesia (GSI) at the position of Km.13 until the new road access to PT. Pratama Abadi Industri. However, currently the world is in an uproar with a virus called Corona Virus or Covid-19 which has occurred in the last few months in Indonesia in 2020. Of course this will have an impact on all aspects including the level of road service, so a comparative study of road performance is made. around the GSI Sukalarang factory from Hatun 2017 to 2020. From the survey and calculation results, it can be concluded that the performance of roads with service levels in the current GSI factory area (2020) compared to the previous year (2017) at the same location has decreased which is indicated by reduced vehicle volume, vehicle speed. decreased, reduced vehicle density, and good service levels. From the data obtained, the Covid-19 Pandemic has an effect on traffic volume and road performance, resulting in a decrease in vehicle volume in 2020. In 2017 the traffic volume on Saturdays was 21684 vehicles and 8407.8 SMP / hour, for 2020 on Saturdays, namely 10471 vehicles and 5500.6 SMP / hour decreased by 48.3%. While in 2017 the traffic volume on Monday was 26430 vehicles and 9467.35 SMP / hour, for 2020 Monday, namely 23740 vehicles and 9623.85 SMP / hour decreased by 89.9%.

Abstract The congestion problem that occurs on the road is one of the indicators to determine the level of service. Approximately 20% of all traffic congestion is due to the existence of shockwave jams or phantom jams. One of the factors causing the shock wave phenomenon is the speed differences between heavy vehicles and light vehicles (Garber & Hoel, 2009). On the other hand, the Over Dimension and Over Loading (ODOL) Vehicle worsened the situation by reducing operational speed due to the exceeding load. Indonesia Traffic Police stated that throughout 2019 there were 136.470 vehicles out of 1.376.956 offences that were ODOL vehicles. This research aims to identify the effect of overloading vehicles and the volume of heavy vehicles on creating shock wave phenomenon that led to the lower level of service. Microsimulation modelling is carried out to obtain the resulting level of service from heavy vehicles volume using the primary data from the data collection. The result shows that the large volume of heavy vehicles exacerbated by the presence of ODOL vehicles can cause a temporary change in road speed and lead to a decreased level of service.

AbstractThe modeling of battery electric vehicles (BEVs) still represents a challenge for vehicle manufacturers. The installation of the new types of components needed for BEVs gives rise to uncertainties in the quantification of parameters like the vehicle's weight. Indeed, vehicle weight plays a key role, since it has a drastic effect on the vehicle's range, which is an important selling point for BEVs. Uncertainties in weight estimation create weight fluctuations during the early development phase and the need to resize components like the electric machine or battery. This in turn affects the components' volume and weight. However, such resizing can also lead to component collision and unfeasibility of the vehicle architecture. To solve this problem and to support concept engineers during the early development phase, an iterative approach is required that is capable of estimating weight and volume fluctuations in the relevant components. The approach should also consider the geometrical interdependencies of the components, to ensure that no collisions occur between them. Taking the gearbox as an example application, this paper presents a novel approach that satisfies these requirements.