Highway Capacity Manual 7th Edition

2022 ◽  
Author(s):  
◽  
Keyword(s):  
Highway Capacity ◽  
Highway Capacity Manual ◽  
7Th Edition

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.

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.

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.

Traffic Responsive Signal Timing Plan Generation based on Neural Network

2011 ◽  
pp. 229-240
Author(s):  
Azzam-ul-Asar ◽  
M. Sadeeq Ullah ◽  
Mudasser F. Wyne ◽  
Jamal Ahmed ◽  
Riaz-ul-Hasnain
Keyword(s):  
Neural Network ◽  
Closed Loop ◽  
Learning Rule ◽  
Loop System ◽  
Closed Loop System ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Real Time Traffic ◽  
Plan Selection ◽  
Artificial Neural Network Ann

This paper proposes a neural network based traffic signal controller, which eliminates most of the problems associated with the Traffic Responsive Plan Selection (TRPS) mode of the closed loop system. Instead of storing timing plans for different traffic scenarios, which requires clustering and threshold calculations, the proposed approach uses an Artificial Neural Network (ANN) model that produces optimal plans based on optimized weights obtained through its learning phase. Clustering in a closed loop system is root of the problems and therefore has been eliminated in the proposed approach. The Particle Swarm Optimization (PSO) technique has been used both in the learning rule of ANN as well as generating training cases for ANN in terms of optimized timing plans, based on Highway Capacity Manual (HCM) delay for all traffic demands found in historical data. The ANN generates optimal plans online to address real time traffic demands and thus is more responsive to varying traffic conditions.

scholarly journals Capacity of Advance Right-Turn Motorized Vehicles at Signalized Intersections for Mixed Traffic Conditions

2019 ◽  
Vol 2019 ◽  
pp. 1-13
Author(s):  
Bing Li ◽  
Wei Cheng ◽  
Yiming Bie ◽  
Bin Sun
Keyword(s):  
Arrival Rate ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Traffic Conditions ◽  
Capacity Model ◽  
Conflict Zone ◽  
Traffic Conflict ◽  
Motorized Vehicles ◽  
The Relationship ◽  
Gap Acceptance Theory

Right-turn motorized vehicles turn right using channelized islands, which are used to improve the capacity of intersections. For ease of description, these kinds of right-turn motorized vehicles are called advance right-turn motorized vehicles (ARTMVs) in this paper. The authors analyzed four aspects of traffic conflict involving ARTMVs with other forms of traffic flow. A capacity model of ARTMVs is presented here using shockwave theory and gap acceptance theory. The proposed capacity model was validated by comparison to the results of the observations based on data collected at a single intersection with channelized islands in Kunming, the Highway Capacity Manual (HCM) model and the VISSIM simulation model. To facilitate engineering applications, the relationship describing the capacity of the ARTMVs with reference to the distance between the conflict zone and the stop line and the relationship describing the capacity of the ARTMVs with reference to the effective red time of the nonmotorized vehicles moving in the same direction were analyzed. The authors compared these results to the capacity of no advance right-turn motorized vehicles (NARTMVs). The results show that the capacity of the ARTMVs is more sensitive to the changes in the arrival rate of nonmotorized vehicles when the arrival rate of the nonmotorized vehicles is 500  (veh/h)~2000  (veh/h) than when the arrival rate is some other value. In addition, the capacity of NARTMVs is greater than the capacity of ARTMVs when the nonmotorized vehicles have a higher arrival rate.

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