Proposed Framework for Evaluating Spillback in the Highway Capacity Manual

2017 ◽  
Vol 2615 (1) ◽  
pp. 148-158
Author(s):  
Yinan Zheng ◽  
Michael Armstrong ◽  
Gustavo de Andrade ◽  
Lily Elefteriadou
Keyword(s):  
Signalized Intersection ◽  
Level Of Service ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Urban Streets ◽  
Facility Type ◽  
Street Intersection ◽  
Lane Utilization ◽  
New Procedures ◽  
Data Collection Effort

Procedures detailed in the Highway Capacity Manual 2010 (HCM 2010) estimate capacity and several operational measures dictating level of service for freeway facilities and surface streets. However, these methods do not consider cases in which spillback occurs from one facility type to another. The queuing effects in oversaturated conditions as they propagate upstream onto a freeway main line or a surface street intersection are not accounted for. The objective of this paper is to propose a series of modifications to enhance the HCM 2010 methods to address spillback conditions. These modifications consider lane utilization and lane blockage under spillback conditions and consist of restructuring existing equations and reference tables as well as developing new procedures. A four-regime method is proposed for evaluating spillback effects from urban streets to diverge and weaving segments. In addition, a method is proposed to account for the spillback effects from freeway on-ramps by reducing the effective green time as a proportion of the percent of time that the queue is expected to block the upstream signalized intersection. The framework developed uses assumptions that should be further explored through an extensive, nationwide data collection effort.

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.

Intersection Delay in Regionwide Traffic Assignment: Implications of 1994 Update of the Highway Capacity Manual

1997 ◽  
Vol 1572 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Alan J. Horowitz
Keyword(s):  
Traffic Assignment ◽  
Signalized Intersection ◽  
Multiple Equilibrium ◽  
Equilibrium Solutions ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Traffic Conditions ◽  
Traffic Delay ◽  
Transportation Research ◽  
New Procedures

The original 1985 Highway Capacity Manual (HCM85) described widely recognized relationships for traffic delay that could be incorporated into travel forecasts. Applications of the HCM85 procedures demonstrated that such delay relationships were both technically feasible and beneficial. In early 1995, the Transportation Research Board released the 1994 update to the HCM (HCM94), heavily revising the signalized and two-way stop intersection procedures and introducing a detailed all-way stop intersection procedure. These new procedures have the potential to improve the accuracy of forecasts and to make forecasts consistent with other design practices. Implementation of the HCM94 procedures into travel forecasts reveals that fewer adjustments are required to make them work within equilibrium traffic assignments. The two-way stop procedure can be used nearly intact. The signalized intersection procedure, although still requiring some adjustments, allows a greater range of traffic conditions and phasing options. The all-way stop procedure cannot be incorporated into travel forecasts because of its restrictions on allowable volumes and turning movements. Tests of the HCM94 procedures in traffic assignments indicate that they produce noticeably different results (both volumes and link delays) than the original HCM85 procedures. Multiple equilibrium solutions are possible, but the differences between these solutions are small and manageable.

scholarly journals Travel Time Estimation on Urban Street Segment

2018 ◽  
Vol 30 (1) ◽  
pp. 115-120 ◽  
Author(s):  
Jelena Kajalić ◽  
Nikola Čelar ◽  
Stamenka Stanković
Keyword(s):  
Travel Time ◽  
Time Estimation ◽  
Travel Speed ◽  
Degree Of Saturation ◽  
Level Of Service ◽  
Travel Time Estimation ◽  
Highway Capacity ◽  
Local Conditions ◽  
Highway Capacity Manual ◽  
Urban Streets

Level of service (LOS) is used as the main indicator of transport quality on urban roads and it is estimated based on the travel speed. The main objective of this study is to determine which of the existing models for travel speed calculation is most suitable for local conditions. The study uses actual data gathered in travel time survey on urban streets, recorded by applying second by second GPS data. The survey is limited to traffic flow in saturated conditions. The RMSE method (Root Mean Square Error) is used for research results comparison with relevant models: Akcelik, HCM (Highway Capacity Manual), Singapore model and modified BPR (the Bureau of Public Roads) function (Dowling - Skabardonis). The lowest deviation in local conditions for urban streets with standardized intersection distance (400-500 m) is demonstrated by Akcelik model. However, for streets with lower signal density (<1 signal/km) the correlation between speed and degree of saturation is best presented by HCM and Singapore model. According to test results, Akcelik model was adopted for travel speed estimation which can be the basis for determining the level of service in urban streets with standardized intersection distance and coordinated signal timing under local conditions.

scholarly journals Self-Organizing Tree Algorithm (SOTA) Clustering for Defining Level of Service (LOS) Criteria of Urban Streets

2018 ◽  
Vol 47 (4) ◽  
pp. 309-317
Author(s):  
Amit Kumar Das ◽  
Prasanta Kumar Bhuyan
Keyword(s):  
Travel Speed ◽  
Flow Speed ◽  
Free Flow ◽  
Level Of Service ◽  
Highway Capacity ◽  
Tree Algorithm ◽  
Highway Capacity Manual ◽  
Urban Streets ◽  
Flow Speeds ◽  
Self Organizing

This study is intended to define the Free Flow Speed (FFS) ranges of urban street classes and speed ranges of Level of Service (LOS) categories. In order to accomplish the study FFS data and average travel speed data were collected on five urban road corridors in the city of Mumbai, India. Mid-sized vehicle (car) mounted with Global Positioning System (GPS) device was used for the collection of large number of speed data. Self-Organizing Tree Algorithm (SOTA) clustering method and five cluster validation measures were used to classify the urban streets and LOS categories. The above study divulges that the speed ranges for different LOS categories are lower than that suggested by Highway Capacity Manual (HCM) 2000. Also it has been observed that average travel speed of LOS categories expressed in percentage of free flow speeds closely resembles the percentages mentioned in HCM 2010.

scholarly journals AFFINITY PROPAGATION CLUSTERING IN DEFINING LEVEL OF SERVICE CRITERIA OF URBAN STREETS

Transport ◽  
2014 ◽  
Vol 29 (4) ◽  
pp. 401-411 ◽  
Author(s):  
Prasanta Kumar Bhuyan ◽  
Smruti Sourava Mohapatra
Keyword(s):  
Traffic Flow ◽  
Heterogeneous Traffic ◽  
Level Of Service ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Urban Streets ◽  
Urban Street ◽  
Indian Context ◽  
Validation Parameters ◽  
Street Segments

Defining Level Of Service (LOS) criteria is very important as this is the first step of LOS analysis but this is not well defined in Indian context. The analysis followed in India is basically adaptation of Highway Capacity Manual (HCM 2000) methodology which is more suitable for developed countries having homogenous traffic pattern. An attempt has been made in this study to define LOS criteria of urban streets for developing countries having heterogeneous traffic flow condition. Defining LOS is basically a classification problem and to solve it Affinity Propagation (AP), a very recently developed cluster algorithm is used. Inventory details and the required speed data are collected from five major street corridors of Greater Mumbai Region in India through the application of Trimble GeoXT Global Positioning System (GPS) receiver. Six validation parameters are used on Free Flow Speed (FFS) data to find the optimal number of clusters, which is required for the classification of street segments into number of classes. After that speed data collected during both peak and off-peak hours are averaged over street segments and clustered into six groups to get the speed ranges of different LOS categories. Using validation parameters, considering the physical and surrounding environmental characteristics it is found that street segments can be classified into four classes in Indian context as mentioned in Highway Capacity Manual 2000. However, the FFS range for urban street class IV (urban design category) is significantly lower because of varying road geometric characteristics. The speed ranges of LOS categories under urban street classes are proportionately lower to that values mentioned in HCM 2000 because of highly heterogeneous traffic flow on urban Indian roads. The travel speed data collection procedure using GPS is simple and accurate. In addition, AP clustering is highly efficient in terms of time saving and provides a very accurate solution to classification problems. Hence, both GPS and AP techniques can be applied in other countries to define the speed ranges of LOS categories considering the local conditions.

Phase Time Prediction for Traffic-Actuated Intersections

1996 ◽  
Vol 1555 (1) ◽  
pp. 17-22 ◽  
Author(s):  
Pei-Sung Lin ◽  
Kenneth G. Courage
Keyword(s):  
Field Studies ◽  
Signalized Intersection ◽  
Level Of Service ◽  
Signal Timing ◽  
Highway Capacity ◽  
Traffic Demand ◽  
Highway Capacity Manual ◽  
Time Prediction ◽  
Traffic Characteristics ◽  
General Reliability

The Highway Capacity Manual (HCM) provides a methodology in Chapter 9 to estimate the capacity and level of service at a signalized intersection as a function of traffic characteristics and signal timing. At traffic-actuated intersections, the signal timing changes from cycle to cycle in response to traffic demand. An accurate prediction of average phase times and their corresponding cycle length is required to assess the performance of intersections controlled by traffic-actuated signals. The current technique suggested in Appendix II of HCM Chapter 9 for this purpose has not been well accepted. A more comprehensive methodology and a more satisfactory analytical model are described that predict traffic-actuated signal timing for both isolated and coordinated modes with actuated phases. The proposed methodology and model have been verified by simulation augmented by limited field studies. The results are encouraging with respect to their general reliability and their compatibility with the current HCM Chapter 9 structure.

Models for Lane Utilization Prediction for Lane Drop Intersections

2005 ◽  
Vol 1912 (1) ◽  
pp. 47-56 ◽  
Author(s):  
Jae-Joon Lee ◽  
Nagui M. Rouphail ◽  
Joseph E. Hummer
Keyword(s):  
North Carolina ◽  
Regression Models ◽  
Signalized Intersections ◽  
Level Of Service ◽  
Highway Capacity ◽  
Utilization Factor ◽  
Highway Capacity Manual ◽  
Multiple Regression Models ◽  
Geometric Variables ◽  
Lane Utilization

Lane drops downstream of signalized intersections can be found on many urban and suburban streets and highways. Because drivers tend to avoid using the short lane because of the potential for stressful merges downstream of the signal, the short lane is typically underused. Previous research indicates that the default lane utilization factors in the Highway Capacity Manual (HCM) appear to overestimate traffic in the short lane. The purpose of this research is to develop models to predict lane utilization factors for six intersection types and to assess how low lane utilization affects the observed intersection capacity and level of service. Traffic and signal data were collected at 47 sites in North Carolina. On the basis of 15 candidate factors, multiple regression models were developed for predicting the lane utilization factor. Field-measured delays were compared with delays estimated by the HCM with the use of regression models for lane utilization. It was found that even with the new models for lane utilization, the HCM consistently overestimated delay for all types of lane drop intersections with low lane utilization: a reassessment of the effect of lane utilization on capacity may be in order. This study also found that the downstream lane length and traffic intensity positively correlate with the lane utilization factor and that some geometric variables at the approach may also influence lane utilization.

Field Measurement of Signalized Intersection Delay for 1997 Update of the Highway Capacity Manual

1998 ◽  
Vol 1646 (1) ◽  
pp. 79-86 ◽  
Author(s):  
James L. Powell
Keyword(s):  
Field Measurement ◽  
Flow Speed ◽  
Signalized Intersection ◽  
Volume Control ◽  
Level Of Service ◽  
Highway Capacity ◽  
Total Delay ◽  
Highway Capacity Manual ◽  
Measuring Field ◽  
Vehicle Deceleration

The 1997 update of the Highway Capacity Manual changes the basis of delay for level-of-service determination at signalized intersections from stopped delay to conceptually more appealing total delay. Total delay is made up of components including volume, control, and geometric delay. Level of service is now defined in terms of control delay, which provides a more stable and tractable relation to total delay, but the issue of field measurement remains in any case. A combined theoretical and empirical approach to measuring field delay on the basis of typical vehicle deceleration and acceleration profiles is taken in this paper. The profiles are related to the relatively easily surveyed quantity of vehicles in queue, which is equivalent to estimating time in queue of all vehicles stopped by the traffic signal. The results indicate that after vehicles in queue are sampled, correction factors can account, in practical terms, for the unsurveyed deceleration and acceleration delay. The corrections are simple additive factors that are a function of free-flow speed and average number of vehicles stopped in queue. Another adjustment is included for the consistent tendency of human observers to overestimate vehicles in queue. All of these factors are included in the new 1997 HCM procedure for measuring signalized intersection delay in the field. Further identified work includes the need to fully develop the total delay concept to account for geometric delay consistently over a variety of interrupted- and uninterrupted-flow facilities. Such resolution should be included in HCM 2000 preparation currently in progress.

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.

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