Speed–Flow Curves for Freeways in Highway Capacity Manual 2010

2011 ◽  
Vol 2257 (1) ◽  
pp. 10-21
Author(s):  
Roger P. Roess
Keyword(s):  
Highway Capacity ◽  
Flow Curves ◽  
Highway Capacity Manual ◽  
Speed Flow

Study of Speed-Flow Relationships on Individual Freeway Lanes

1997 ◽  
Vol 1591 (1) ◽  
pp. 7-13 ◽  
Author(s):  
V. F. Hurdle ◽  
Mark I. Merlo ◽  
Doug Robertson
Keyword(s):  
Practical Interest ◽  
Linear Functions ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Speed Flow ◽  
High Flows ◽  
The Mean ◽  
The Individual ◽  
The Relationship ◽  
Very High

Many researchers have examined the form of the relationship between speed and flow on freeways. However, these researchers have concentrated on relationships for the freeway as a whole instead of on individual lanes. In this study, the relationship was examined for each of the three lanes at two locations on Highway 401 in metropolitan Toronto. It proved possible to accurately describe the mean speed in each lane with simple linear functions over the range of flows of most practical interest. Cubic functions provided comparable results over a wider range of flows, but it appears unlikely that the very high and very low flows are of sufficient interest to justify the added complexity. When an attempt was made to examine the relationship between speed and flow for the entire roadway, the linear functions were not adequate, but cubic functions performed reasonably well. However, the details of the full roadway curves are quite different from those of the curves described in the 1994 Highway Capacity Manual. In particular, the curves described in the manual are much steeper than the Highway 401 curves at high flows, implying a much more rapid loss of performance as flow approaches capacity than was observed. The full roadway curves are also surprisingly different from the curves for the individual lanes.

Lane-by-Lane Analysis Framework for Conducting Highway Capacity Analyses at Freeway Segments

2019 ◽  
Vol 2673 (8) ◽  
pp. 523-535
Author(s):  
Fabio Sasahara ◽  
Lily Elefteriadou ◽  
Shen Dong
Keyword(s):  
Flow Distribution ◽  
Time Of Day ◽  
Heavy Vehicles ◽  
Highway Capacity ◽  
Operational Conditions ◽  
Highway Capacity Manual ◽  
Loop Detectors ◽  
Speed Flow ◽  
Flow Speeds ◽  
The Usa

The Highway Capacity Manual (HCM) methodology for freeway systems yields average speed values for each segment and does not consider lane-by-lane flow and operational conditions. However, flows are not equally distributed between lanes. In congested conditions and particularly when spillback occurs, flows and traffic conditions vary widely. For example, the rightmost lane may be blocked while the leftmost lane is free-flowing. The purpose of this research is to develop a model for estimating lane-by-lane speeds and flows under various freeway designs and demands. Speed and flow data from loop detectors at several locations around the USA were collected, totaling 531,000 observations aggregated in 15-min intervals. The results show that lane flow distribution is highly dependent on the segment total flow, with different patterns for 4-, 6-, and 8-lane segments. The percentage of heavy vehicles, presence of nearby ramps, day of week, and time of day also affect the distribution of flow among freeway lanes. Theoretical lane-by-lane speed-flow curves were developed and the results were compared with field data. Results showed that lane-by-lane speeds can be estimated accurately, as long as inputs for capacity and free-flow speeds can be provided for each lane in the segment.

Improved Speed-Flow Relationships for Planning Applications

1997 ◽  
Vol 1572 (1) ◽  
pp. 18-23 ◽  
Author(s):  
Alexander Skabardonis ◽  
Richard Dowling
Keyword(s):  
Field Data ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Speed Estimation ◽  
Highway Capacity ◽  
Estimation Techniques ◽  
Highway Capacity Manual ◽  
Planning Models ◽  
Speed Flow ◽  
Simulation Results

Improved speed-estimation techniques for planning applications were developed and tested. Comparisons with field data and simulation results indicate that the recommended techniques provide better accuracy and consistency with the procedures contained in the 1994 update of the Highway Capacity Manual. These speed-estimation techniques will improve the accuracy of long-range transportation planning models for predicting travel time, delay, and air-pollutant emissions.

Development of an Oversaturated Speed–Flow Model Based on the Highway Capacity Manual

2013 ◽  
Vol 2395 (1) ◽  
pp. 41-48 ◽  
Author(s):  
Yilun Xu ◽  
Billy M. Williams ◽  
Nagui M. Rouphail ◽  
R. Thomas Chase
Keyword(s):  
Flow Model ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Model Based ◽  
Speed Flow

Speed–Flow–Geometry Relationships and Capacity for Two–Lane Single Carriageway Roads

2014 ◽  
Vol 70 (4) ◽  
Author(s):  
Othman Che Puan ◽  
Nur Syahriza Muhamad Nor ◽  
Zamri Bujang
Keyword(s):  
Simulation Model ◽  
Traffic Flow ◽  
Travel Speed ◽  
The United States ◽  
Highway Capacity ◽  
Microscopic Traffic Simulation ◽  
Highway Capacity Manual ◽  
Speed Flow ◽  
Potential Capacity ◽  
Road Geometry

The current Malaysian practice in road capacity analysis, Malaysian Highway Capacity Manual 2011 (MHCM) is based on a method adopted from the Highway Capacity Manual(HCM) of the United States. All the analysis elements appear to be taken directly from the manual. The rationale for using such a method for Malaysian conditions is not well defined. This paper deliberates the background of the methodology used in the development of speed, flow and geometry relationships and the capacity for single carriageway roads. A microscopic traffic simulation model which is capable of simulating traffic operations on single carriageway roads for a range of road geometry configurations and traffic flow conditions was developed and used to evaluate the potential capacity of a single carriageway road. The results of the analysis indicate that a two-lane single carriageway road is capable of accommodating traffic flow higher than the values derived from the previous HCM. The current version of the HCM also appears to underestimate the vehicles’ travel speed for a range of traffic flows when compared with the results of the simulation model. The MHCM 2011, on the other hand, estimated travel speeds higher than the travels speeds predicted by both the HCM 2010 and simulation model. It shows that there is a different interpretation of LOS F in term of speed between HCM 2010 and MHCM 2011.

Predicting Lane-by-Lane Flows and Speeds for Freeway Segments

2020 ◽  
Vol 2674 (9) ◽  
pp. 1052-1068
Author(s):  
Fabio Sasahara ◽  
Luan Guilherme Staichak Carvalho ◽  
Tanay Datta Chowdhury ◽  
Zachary Jerome ◽  
Lily Elefteriadou ◽  
...  
Keyword(s):  
Field Data ◽  
Performance Estimation ◽  
Free Flow ◽  
Highway Capacity ◽  
Distribution Models ◽  
Highway Capacity Manual ◽  
Speed Flow ◽  
Flow Speeds ◽  
The Relationship

The Highway Capacity Manual is a major reference for evaluating the capacity and quality of service of road facilities. However, it holds the assumption that lanes perform equally, which can result in inaccuracies in performance estimation. The main purpose of this research is to develop a series of models for estimating flows and speeds by lane for various types of freeway segments, including basic, merge, and diverge types. These models consider the demand-to-capacity ratio, the presence of trucks, grade, and the presence of upstream and downstream ramps. To predict lane performance effectively, it is critical that capacity and free-flow speeds are also determined for individual lanes. Therefore, this study also investigates the relationship between segment average values and lane values for free-flow speeds and capacities, and proposes a method to estimate these parameters for each lane as a function of the segment average. Observed field data has shown that free-flow speeds and capacities have lowest values on the shoulder lanes and highest values on the median lanes. Speed and flow data were collected from 48 segments throughout the U.S.A., including basic, merge, and diverge segments, to develop flow and speed distribution models. A case example is provided to illustrate the application of the developed model and the predicted speed–flow relationship is compared with field data, with satisfactory results.

Defining Freeway Design Capacity Based on Stochastic Observations

2018 ◽  
Vol 2672 (15) ◽  
pp. 131-141 ◽  
Author(s):  
Siavash Shojaat ◽  
Justin Geistefeldt ◽  
Scott A. Parr ◽  
Luis Escobar ◽  
Brian Wolshon
Keyword(s):  
Flow Index ◽  
Empirical Comparison ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
General Acceptance ◽  
Probability Of Survival ◽  
Speed Flow ◽  
Stochastic Capacity ◽  
Freeway Capacity ◽  
Capacity Estimates

The estimation of capacity as a parameter to assess traffic flow performance on freeway facilities has received considerable attention in the literature. Despite the general acceptance of the stochastic notion of capacity, limited research has been conducted on how to select a single representative design value from a capacity distribution function. This paper reports the results of an empirical comparison between conventional capacity estimates and those obtained by maximizing the sustained flow index (SFI) for 19 U.S. freeway sections. The SFI is defined as the product of the traffic volume and the probability of survival at this volume. The capacity of each cross-section was estimated by analyzing the speed–flow relationship and applying methods for stochastic capacity analysis. The results show that the optimum volumes obtained by maximizing the SFI estimated in 5-minute intervals correspond well to the 15% probability of breakdown proposed in the Highway Capacity Manual 6 th Edition to estimate the capacity from field data. From these results, it was concluded that maximizing the SFI can be considered a preferred approach to estimate a single, representative value of freeway capacity.

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.

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