Beyond the Highway Capacity Manual Framework for Selecting Simulation Models in Traffic Operational Analyses

1999 ◽  
Vol 1678 (1) ◽  
pp. 96-106 ◽  
Author(s):  
Lily Elefteriadou ◽  
John D. Leonard ◽  
George List ◽  
Henry Lieu ◽  
Michelle Thomas ◽  
...  
Keyword(s):  
Simulation Models ◽  
Highway Capacity ◽  
Highway Capacity Manual

Validation Results for Four Models of Oversaturated Freeway Facilities

2000 ◽  
Vol 1710 (1) ◽  
pp. 161-170 ◽  
Author(s):  
Fred L. Hall ◽  
Loren Bloomberg ◽  
Nagui M. Rouphail ◽  
Brian Eads ◽  
Adolf D. May
Keyword(s):  
Field Data ◽  
Simulation Models ◽  
Highway Capacity ◽  
Highway Capacity Manual

Some researchers have noted that the current procedures in the Highway Capacity Manual (HCM) may not be appropriate for analyzing complex or oversaturated freeway facilities. The results of a comparison of an HCM-based procedure with field data from six such freeway sites are reported. Because simulation has often been suggested as an alternative to the HCM for oversaturated freeway facilities, three simulation models (CORSIM, FREQ, and INTEGRATION) were also used to analyze these same six sites. The results suggest that the HCM-based procedures do as well as the three simulation models in reproducing the average speeds across the freeway facilities.

Freeway Facility Methodology in Highway Capacity Manual 2000

2000 ◽  
Vol 1710 (1) ◽  
pp. 171-180 ◽  
Author(s):  
Brian S. Eads ◽  
Nagui M. Rouphail ◽  
Adolf D. May ◽  
Fred Hall
Keyword(s):  
Intelligent Transportation System ◽  
Simulation Models ◽  
Companion Paper ◽  
Ramp Metering ◽  
Incident Management ◽  
Highway Capacity ◽  
Time Intervals ◽  
Highway Capacity Manual ◽  
Traffic Conditions ◽  
First Time

The next edition of the Highway Capacity Manual (HCM 2000) will contain for the first time an operational analysis procedure for directional freeway facilities up to 20 to 25 km long. At the simplest level, this procedure integrates the proposed HCM 2000 methods for the analysis of basic, ramp, and weaving segments to enable the analysis of an entire facility. But the proposed facility methodology goes much further. It allows the user to analyze multiple, contiguous time intervals with timevarying demands and capacities. It can handle both undersaturated and oversaturated traffic conditions (with some limitations). In the latter case, both the spatial and time extent of congestion are estimated. Finally, the method permits the investigation of the effect of many traditional and intelligent transportation system–based freeway improvement strategies such as full or auxiliary lane additions, ramp metering, incident management, and a limited set of high-occupancy-vehicle designs on facility performance. Described here is the conceptual model for and computational steps of the methodology, with emphasis on the components for analysis of oversaturated conditions. The scope and limitations of the methods are also highlighted. Reference is given to a companion paper that describes how the results of the method were validated in the field and how they compared with those obtained from widely used freeway simulation models.

scholarly journals Development and evaluation of a microscopic overtaking gap acceptance model for two-lane highways

2016 ◽  
Vol 43 (6) ◽  
pp. 573-582 ◽  
Author(s):  
Amir H. Ghods ◽  
Frank F. Saccomanno
Keyword(s):  
Field Data ◽  
Video Recording ◽  
Simulation Models ◽  
Gap Acceptance ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Time To Collision ◽  
Expected Time ◽  
Acceptance Model

A microscopic gap acceptance model is presented that simulates overtaking behavior on two-lane highways. The decision to initiate overtaking is expressed as a function of each driver’s perception of the expected time-to-collision (TTC) with the nearest opposing vehicle at the end of maneuver. The available gap is accepted if the driver’s perception of TTC exceeds a predetermined threshold for safe return (critical TTC). The gap acceptance model is calibrated and validated based on overtaking video-recording data for a two-lane highway. The overtaking gap acceptance model is then compared, for consistency and transferability, with independent aggregate field data, as well as with two other simulation models and values given in the Highway Capacity Manual for similar two-lane highways. The gap acceptance simulation demonstrated that the proposed overtaking model is able to provide reliable measures of traffic attributes for two-lane highway operation, as verified experimentally.

Development of Passenger Car Equivalents for Freeways, Two-Lane Highways, and Arterials

1997 ◽  
Vol 1572 (1) ◽  
pp. 51-58 ◽  
Author(s):  
Lily Elefteriadou ◽  
Darren Torbic ◽  
Nathan Webster
Keyword(s):  
Full Range ◽  
Simulation Models ◽  
Heavy Vehicles ◽  
Highway Capacity ◽  
Passenger Car ◽  
Highway Capacity Manual ◽  
Vehicle Type ◽  
Traffic Conditions ◽  
Recreational Vehicles ◽  
The Impact

Passenger car equivalents (PCEs) have been used extensively in the Highway Capacity Manual to establish the impact of trucks, buses, and recreational vehicles on traffic operations. PCEs are currently being used for studying freeways, multilane highways, and two-lane highways. A heavy-vehicle factor is directly given for the impact of heavy vehicles at signalized intersections (and indirectly along arterials). These PCE values are typically based on a limited number of simulations and on older simulation models. In addition, the impact of variables such as traffic flow, truck percentage, truck type (i.e., length and weight/horsepower ratio), grade, and length of grade on PCEs has not been evaluated in depth for all facility types. The methodology for developing PCEs for different truck types for the full range of traffic conditions on freeways, two-lane highways, and arterials is described. Given the scope of this research and the variability of traffic conditions to be examined, simulation was selected as the most appropriate tool. The resulting PCE values for freeways, two-lane highways, and arterials indicated that some variables, such as percentage of trucks, do not always have the expected effect on PCEs, whereas other variables, such as vehicle type, are crucial in the calculations. Generally, major differences in PCEs occurred for the longer and steeper grades. There was great variability in PCE values as a function of the weight/horsepower ratio as well as of vehicle length.

Modeling Capacity of Through Movement at Signalized Intersection Affected by Short Left-Turn Bay under Different Signal Settings

2021 ◽  
pp. 036119812110064
Author(s):  
Zihang Wei ◽  
Yunlong Zhang ◽  
Xiaoyu Guo ◽  
Xin Zhang
Keyword(s):  
Cycle Length ◽  
Signalized Intersections ◽  
Signalized Intersection ◽  
Essential Factor ◽  
Highway Capacity ◽  
Left Turn ◽  
Highway Capacity Manual ◽  
Proposed Model ◽  
Vehicle Demand ◽  
The One

Through movement capacity is an essential factor used to reflect intersection performance, especially for signalized intersections, where a large proportion of vehicle demand is making through movements. Generally, left-turn spillback is considered a key contributor to affect through movement capacity, and blockage to the left-turn bay is known to decrease left-turn capacity. Previous studies have focused primarily on estimating the through movement capacity under a lagging protected only left-turn (lagging POLT) signal setting, as a left-turn spillback is more likely to happen under such a condition. However, previous studies contained assumptions (e.g., omit spillback), or were dedicated to one specific signal setting. Therefore, in this study, through movement capacity models based on probabilistic modeling of spillback and blockage scenarios are established under four different signal settings (i.e., leading protected only left-turn [leading POLT], lagging left-turn, protected plus permitted left-turn, and permitted plus protected left-turn). Through microscopic simulations, the proposed models are validated, and compared with existing capacity models and the one in the Highway Capacity Manual (HCM). The results of the comparisons demonstrate that the proposed models achieved significant advantages over all the other models and obtained high accuracies in all signal settings. Each proposed model for a given signal setting maintains consistent accuracy across various left-turn bay lengths. The proposed models of this study have the potential to serve as useful tools, for practicing transportation engineers, when determining the appropriate length of a left-turn bay with the consideration of spillback and blockage, and the adequate cycle length with a given bay length.

Assessment of Arterial Signal Timings Based on Various Operational Policies and Optimization Tools

2021 ◽  
pp. 036119812110111
Author(s):  
Suhaib Al Shayeb ◽  
Nemanja Dobrota ◽  
Aleksandar Stevanovic ◽  
Nikola Mitrovic
Keyword(s):  
Travel Time ◽  
Heavy Traffic ◽  
Future Research ◽  
Signal Timing ◽  
Highway Capacity ◽  
Average Delay ◽  
Highway Capacity Manual ◽  
Simulation And Optimization ◽  
Fort Lauderdale ◽  
Design Engineers

Traffic simulation and optimization tools are classified, according to their practical applicability, into two main categories: theoretical and practical. The performance of the optimized signal timing derived by any tool is influenced by how calculations are executed in the particular tool. Highway Capacity Software (HCS) and Vistro implement the procedures defined in the Highway Capacity Manual, thus they are essentially utilized by traffic operations and design engineers. Considering its capability of timing diagram drafting and travel time collection studies, Tru-Traffic is more commonly used by practitioners. All these programs have different built-in objective function(s) to develop optimized signal plans for intersections. In this study, the performance of the optimal signal timing plans developed by HCS, Tru-Traffic, and Vistro are evaluated and compared by using the microsimulation software Vissim. A real-world urban arterial with 20 intersections and heavy traffic in Fort Lauderdale, Florida served as the testbed. To eliminate any bias in the comparisons, all experiments were performed under identical geometric and traffic conditions, coded in each tool. The evaluation of the optimized plans was conducted based on average delay, number of stops, performance index, travel time, and percentage of arrivals on green. Results indicated that although timings developed in HCS reduced delay, they drastically increased number of stops. Tru-Traffic signal timings, when only offsets are optimized, performed better than timings developed by all of the other tools. Finally, Vistro increased arrivals on green, but it also increased delay. Optimized signal plans were transferred manually from optimization tools to Vissim. Therefore, future research should find methods for automatically transferring optimized plans to Vissim.

Estimating the Effects of Urban Street Incidents on Capacity

2017 ◽  
Vol 2615 (1) ◽  
pp. 55-61 ◽  
Author(s):  
Aidin Massahi ◽  
Mohammed Hadi ◽  
Maria Adriana Cutillo ◽  
Yan Xiao
Keyword(s):  
Network Performance ◽  
Field Measurements ◽  
Signalized Intersection ◽  
Limited Information ◽  
Microscopic Simulation ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Urban Streets ◽  
Urban Street ◽  
Incident Duration

The effect of incidents on capacity is the most critical parameter in estimating the influence of incidents on network performance. The Highway Capacity Manual 2010 (HCM 2010) provides estimates of the drop in capacity resulting from incidents as a function of the number of blocked lanes and the total number of lanes in the freeway section. However, there is limited information on the effects of incidents on the capacity of urban streets. This study investigated the effects on capacity of the interaction between the drop in capacity below demand at a midblock urban street segment location and upstream and downstream of signalized intersection operations. A model was developed to estimate the drop in capacity at the incident location as a function of the number of blocked lanes, the distance from the downstream intersection, and the green time–to–cycle length (g:C) ratio of the downstream signal. A second model was developed to estimate the reduction in the upstream intersection capacity resulting from the drop in capacity at the midblock incident location as estimated by the first model. The second model estimated the drop in capacity of the upstream links feeding the incident locations as a function of incident duration time, the volume-to-capacity (V/C) ratio at the incident location, and distance from an upstream signalized intersection. The models were developed on the basis of data generated with the use of a microscopic simulation model calibrated by comparison with parameters suggested in HCM 2010 for incident and no-incident conditions and by comparison with field measurements.

Application of Moving Car Observer Method for Measuring Free Flow Speed on Two-lane Highways

2014 ◽  
Vol 69 (6) ◽  
Author(s):  
Othman Che Puan ◽  
Muttaka Na’iya Ibrahim ◽  
Usman Tasiu Abdurrahman
Keyword(s):  
Field Measurement ◽  
Flow Speed ◽  
Operating Conditions ◽  
Free Flow ◽  
Geometric Features ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Free Flow Speed ◽  
The Subject ◽  
Low Traffic

There exists a need to evaluate the performance indicator that reflects the current level of service (LOS) of the subject facility to justify any decision making on expenditures to be made for improving the performance level of a road facility. Free-flow speed (FFS) is one of the key parameters associated with LOS assessment for two-lane highways. Application of a more realistic approach for assessing road’s performance indicators would result in better estimates which could in turn suggest the most appropriate decision to be made (for situations where upgrading is needed); especially, in terms of finance, materials and human resources. FFS is the driver’s desired speed at low traffic volume condition and in the absence of traffic control devices. Its estimation is significant in the analysis of two-lane highways through which average travel speed (ATS); an LOS indicator for the subject road class is determined. The Highway Capacity Manual (HCM) 2010 offers an indirect method for field estimation of FSS based on the highway operating conditions in terms of base-free-flow-speed (BFFS). It is however, recommended by the same manual that direct field FSS measurement approach is most preferred. The Malaysian Highway Capacity Manual (MHCM) established a model for estimating FFS based on BFFS, the geometric features of the highway and proportion of motorcycles in the traffic stream. Estimating FFS based on BFFS is regarded as an indirect approach which is only resorted to, if direct field measurement proved difficult or not feasible. This paper presents the application of moving car observer (MCO) method for direct field measurement of FFS. Data for the study were collected on six segments of two-lane highways with varying geometric features. FFS estimates from MCO method were compared with those based on MHCM model. Findings from the study revealed that FFS values from MCO method seem to be consistently lower than those based on MHCM model. To ascertain the extent of the difference between the FFS values from the two approaches, student t-statistics was used. The t-statistics revealed a P–value of less than 0.05 (P < 0.05) which implies that there is a statistically significant difference between the two sets of data. Since MCO method was conducted under low traffic flow (most desired condition for field observation), it can be suggested that MCO estimates of FFS represent the actual scenario. A relationship was therefore developed between the estimates from the two methods. Thus, if the MHCM model is to be applied, the measured value needs to be adjusted based on the relationship developed between the two approaches.

Uncertainty in Operational Analysis of Two-Lane Highways

2002 ◽  
Vol 1802 (1) ◽  
pp. 105-114 ◽  
Author(s):  
R. Tapio Luttinen
Keyword(s):  
Input Data ◽  
Travel Speed ◽  
Level Of Service ◽  
Model Parameters ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Operational Analysis ◽  
Percent Time ◽  
Different Types ◽  
Percent Time Spent Following

The Highway Capacity Manual (HCM) 2000 provides methods to estimate performance measures and the level of service for different types of traffic facilities. Because neither the input data nor the model parameters are totally accurate, there is an element of uncertainty in the results. An analytical method was used to estimate the uncertainty in the service measures of two-lane highways. The input data and the model parameters were considered as random variables. The propagation of error through the arithmetic operations in the HCM 2000 methodology was estimated. Finally, the uncertainty in the average travel speed and percent time spent following was analyzed, and four approaches were considered to deal with uncertainty in the level of service.

Validation of Generalized Delay Model for Vehicle-Actuated Traffic Signals

1997 ◽  
Vol 1572 (1) ◽  
pp. 105-111 ◽  
Author(s):  
Nagui M. Rouphail ◽  
Mohammad Anwar ◽  
Daniel B. Fambro ◽  
Paul Sloup ◽  
Cesar E. Perez
Keyword(s):  
North Carolina ◽  
Field Data ◽  
Traffic Signals ◽  
Signalized Intersections ◽  
Delay Model ◽  
Highway Capacity ◽  
Generalized Model ◽  
Highway Capacity Manual ◽  
Traffic Volumes ◽  
Isolated Intersection

One limitation of the Highway Capacity Manual (HCM) model for estimating delay at signalized intersections is its inadequate treatment of vehicle-actuated traffic signals. For example, the current delay model uses a single adjustment for all types of actuated control and is not sensitive to changes in actuated controller settings. The objective in this paper was to use TRAF-NETSIM and field data to evaluate a generalized delay model developed to overcome some of these deficiencies. NETSIM was used to estimate delay at an isolated intersection under actuated control, and the delay values obtained from NETSIM were then compared with those estimated by the generalized delay model. In addition, field data were collected from sites in North Carolina, and delays observed in the field were compared with those estimated by the generalized delay model. The delays estimated by the generalized model were comparable with the delays estimated by NETSIM. The data compared favorably for degrees of saturation of less than 0.8. However, at higher degrees of saturation, the generalized model produced delays that were higher than NETSIM’s. Some possible explanations for this discrepancy are discussed. The delays estimated by the generalized model were comparable with delays observed in the field. Researchers have concluded that the generalized delay model is sensitive to changes in traffic volumes and vehicle-actuated controller settings and that the generalized delay model is much improved over the current HCM model in estimating delay at vehicle-actuated traffic signals.

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