Estimating Road Traffic Capacity (original) (raw)
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Journal of Advanced Transportation, 2020
Passenger Car Equivalent (PCE) is essential for transportation engineering to assess heavy vehicles’ (HV) impact on highway operations and capacity planning. Highway Capacity Manual 2010 (HCM 2010) used PCE values and percent of heavy vehicles to account the impacts on both highway planning and operation, however, PCE values in the latest version of HCM derived based on the steady and balanced two-lane-two-way (TLTW) traffic flows. The objective of the study is to identify PCE values for TLTW highway at various traffic volume with an emphasis on congestion conditions. This study introduces an analytical model, combining a headway-based and a delay-based algorithms, for estimating PCEs of HV on a TLTW highway. This study contributes to the literature by providing relationships among PCE, the traffic volume level (TVL) of both lanes, and the TVL duration on a TLTW highway. Traffic volume was categorized into five levels: TVL A (<250 pc/h), TVL B (250–375 pc/h), TVL C (375–600 pc/h)...
Estimation of Passenger Car Unit on urban roads: A literature review
International Journal of Transportation Science and Technology, 2020
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Developing Passenger Car Equivalency Factors for Heavy Vehicles during Congestion
The Highway capacity manual HCM utilizes passenger car equivalency PCE factors to estimate the effect of heavy vehicles on traffic stream behavior under free-flow conditions. However, these factors have been mistakenly used by professionals to conduct analyses for all traffic conditions, i.e., free-flow as well as forced-flow conditions. Recent empirical evidence suggests that the PCE factors for free-flow conditions largely underestimate the effect of heavy vehicles after the onset of congestion. The current study aims at developing PCE factors for heavy vehicles on freeways and multilane highways during congestion. The study utilizes empirical data and microscopic traffic simulation to develop a set of PCE factors on level terrain and specific upgrades during congestion. The format of the proposed PCE factors is very similar to that of the HCM PCE factors for free-flow conditions. It is believed that the use of the proposed PCE factors for oversaturated conditions will help to largely improve the estimate of heavy vehicles’ effect when congestion is present.
Selective Estimations of Empirical Roadway Capacity
Traffic theory is concerned with the movement of discrete objects in real time over a finite network in 2 dimensions. It is compatible with or dependent on fundamental diagram of traffic. Without question, traffic flow is an essential quantitative parameter that is used in planning, designs and roadway improvements. Road capacity is significant because it's an important indicator of road performance and can point road managers in the right road maintenance and traffic management direction. In this paper four direct empirical capacity measurement methods have been considered. To test the efficacy of each method data for peak period, off-peak and transition to peak have been used. The headway and the volumes methods lack predictive capability and are suitable only for current assessment of flow rates. The product limit method is weak in its predictive capability in view of the arbitrariness in the selection of the capacity value. It is also an extreme value method; hence not all volume data can be used with this method. The fundamental diagram method has good predictive capability and furnishes capacity values consistent with the standard of the facility. Unlike other methods, it does not rely on bottleneck conditions to deliver the capacity value. The paper concluded that each method is uniquely suited to prevailing conditions and can be so employed.
Transportation Research Record: Journal of the Transportation Research Board, 2016
This study demonstrates that passenger car unit (PCU) values for a vehicle are not static and vary with traffic volume and composition. Data collected at eight urban arterial roads in India were analyzed to explain the dynamic nature of the PCU factor. All vehicles in the traffic stream were divided into five categories, and simultaneous equations were developed to determine the speed of a vehicle type from information on traffic volume and composition. These equations were used to show the variation in PCU values with traffic volume and composition on a road. The change in PCU values was explained on the basis of the relative interaction of vehicle type in the traffic stream at different volume levels. A proposed range of PCU values for big vehicles was from 1.47 to 1.65 for big cars and for heavy vehicles from 5.51 to 6.54, respectively, when their proportions in the mix remained within an observed range in the field. Similarly, a range of PCU values for motorized three-wheelers o...
Passenger car units for heterogeneous traffic using a modified density method
… International symposium on …, 2000
The upcoming Highway Capacity Manual (HCM) 2000 will use density method to derive its new, passenger-car equivalences (PCEs) for trucks. These PCEs appear as "E T " in HCM tables. The density method assumes homogeneous traffic. Strict lane discipline characterizes homogeneous traffic. By adjusting the density method to handle heterogeneous traffic, one can derive more accurate passenger car units for Indian conditions. Very loose lane discipline describes heterogeneous traffic. Measuring the distribution of each Indian traffic type across the pavement width from different highway types allowed the adjustment. Motorized two-wheelers, cars, bicycles, farm tractors, trucks and other traffic types comprise Indian traffic. Data showed the 85th percentile distribution width of each traffic type can serve as a more accurate measure than the marked lane width when traffic is heterogeneous. The project team collected speed, flow and lateral placement data at 34 rural and suburban highway sites throughout India. These sites comprised six highway types. One can compare two "only passenger car" traffic streams with one being homogeneous and the other heterogeneous. This comparison occurs when the streams have equal average speed and demand. The area density of the heterogeneous traffic stream will be different from the homogeneous traffic stream area density because the pavement widths that each stream uses will be different. This difference results in a "passenger car unit" adjustment factor, f PCU , to convert a passenger car in heterogeneous traffic into its homogeneous traffic counterpart. The study also rendered passenger car units for each Indian traffic type in relation to an Indian passenger car. Preliminary results show the adjustment necessary to convert Indian passenger cars in heterogeneous traffic into U.S. passenger car equivalents for homogeneous traffic. Derivations of passenger-car-unit adjustment factors showed that a car is equivalent to 2 cars in homogeneous traffic on single-lane highways, two-lane highway types without paved shoulders, with 1.5 meter shoulders and with 2.5 meter shoulders. On 1.5 lane highways and four-lane divided highways f PCU value is 1, i.e., performance of heterogenous traffic and homogenous traffic are similar. These equivalents happen when the Indian cars move at the same space mean speed as cars in homogeneous traffic. The modified density method can be used to determine passenger car units for various traffic entity groups on rural and suburban roads in India.
Management of traffic-related effects of heavy vehicles on urban freight corridors
2006
Increasing demand for road freight has lead to a greater adoption of more-productive multi-combination vehicles on roads that are generally also used as major arterial corridors for non-freight traffic. This paper reports on a study into the effects that these vehicles, such as B-doubles, have on the traffic performance of urban traffic corridors and offers a number of strategies having the potential to minimize their impacts. A computer-based microsimulation traffic model was created of a multi-lane arterial corridor, including coordinated traffic signals. Individual vehicles progressed along the corridor, with each vehicle following its leader and changing lanes when advantageous and safe to do so. The longitudinal vehicle dynamic behavior of each vehicle was modeled in detail, with heavy vehicles accelerating at a lower rate that light vehicles. The model was calibrated with data collected from GPS-equipped chase car surveys conducted on an urban corridor in Brisbane, Australia. Corridor performance was reported in terms of intersection capacity and delays as well as travel speeds and stop rates for each vehicle type. The performance of the corridor was found to be sensitive to traffic control measures including the speed limit and traffic signal controller settings such as cycle time and progression design speed. A range of freight policy scenarios were examined, including the effects of increasing freight volumes, freight vehicle mode choice, and vehicle type-specific lane restrictions. Some policies having the potential to improve corridor traffic performance and freight efficiency were able to be identified. Advance detection of heavy vehicles approaching a traffic signal and extension of the green signal until their passage was found to offer benefits to all vehicles on the corridor.
Procedia - Social and Behavioral Sciences, 2011
The knowledge of roadway capacity is an important basic input required for planning, analysis and operation of roadway systems. Expressing capacity as number of vehicles passing a given section of road or traffic lane per unit time will be inappropriate when several types of vehicles with widely varying static and dynamic characteristics are comprised in the traffic. The problem of measuring volume of such heterogeneous traffic has been addressed by converting the different types of vehicles into equivalent passenger cars and expressing the volume in terms of Passenger Car Unit (PCU) per hour. The effect of variation of traffic volume, road width, magnitude of upgrade and its length on PCU value is studied. A recently developed heterogeneous traffic-flow simulation model, named, HETEROSIM is used for this study. Field data collected on traffic flow characteristics are used in calibration and validation of the simulation model. The validated simulation model is then used to derive PCU values for different types of vehicles. The PCU estimates, made through microscopic simulation, for the different types of vehicles of heterogeneous traffic, for a wide range of traffic volume and roadway conditions indicate that the PCU value of a vehicle significantly changes with change in traffic volume, width of roadway, magnitude of upgrade and its length. Using the derived PCU values, capacity guidelines are also developed for typical roadway and traffic conditions.
2020
This paper aims to estimate the road capacity based on the headway time to consider the road user behaviour which is the main element in microsystem of traffic analysis. The lane position is considered also in developing the capacity-headway model to reflect the driver behaviour in using each lane. Palestine Street in Baghdad City is chosen as the site study to simulate the urban multilane characteristics of roads. The data representing the roadway characteristics, vehicle volume, and headway time are collected at peak hours to reflect the high traffic flow level. The model is developed using regression analysis. The results show that the lane position affect the driver decision in choosing the lane of movement and affect significantly the capacity values especially the right lane position.
Transportation Research Record, 2017
This research was aimed at developing an area occupancy-based method for estimating passenger car unit (PCU) values for vehicle categories under heterogeneous traffic conditions on multilane urban roads for a wide range of traffic flow levels. First, PCU values of vehicle categories were determined according to the Transport and Road Research Laboratory definition and replaced the commonly considered measure of performance speed with area occupancy using simulation. The PCU values obtained were found to be significantly different for different volume-to-capacity ratios; this result shows that the PCU value is dynamic in nature. While the dynamic nature of PCU values is well appreciated, practitioners may prefer a single set of optimized PCU values (unique for each vehicle category). Hence, a new method with a matrix solution was proposed to estimate the optimized or unique set of PCU values with area occupancy as the performance measure. To check the credibility of the proposed method, the estimated PCU values were compared from existing guidelines regulated by the Indian Roads Congress (IRC) and values estimated with the widely accepted dynamic PCU concept of speed-area ratio. Results show that the PCU values suggested by IRC and the dynamic PCU concept using the speedarea ratio underestimate and overestimate the flows, respectively, at different traffic volumes. However, the values obtained with the areaoccupancy concept were found to be consistent with the traffic flow in a cars-only traffic situation at different flow conditions. The derived set of optimized PCU values proposed can be useful for traffic engineers, researchers, and practitioners for capacity and level-of-service analysis under heterogeneous traffic conditions.