Free-flow Speed Research Articles

Application of genetic programming clustering in defining LOS criteria of urban street in Indian context

India is a highly populated country having second largest road network in the world. Owing to boastfully population, the congestion is growing rapidly on the urban road networks. The level of service (LOS) is not substantially defined for heterogeneous traffic flow with different operational characteristics. Defining LOS is essentially a classification problem. The application of cluster analysis is the worthiest proficiency to solve such problem for which genetic programming (GP) clustering, an evolutionary algorithm is used in this study. Five cluster validation parameters are utilized to examine the optimal number of clusters. The cluster validation parameters are used to obtain the number of categories of urban street classes. After acquiring optimal number of clusters, GP clustering is implemented to the free flow speed (FFS) data to get ranges of different urban street classes. Again, GP clustering is enforced on average travel speeds of street segments to specify the ranges of different LOS categories. Speed data used in this study are collected using Trimble GeoXT GPS receivers fitted on mid-sized vehicles for five major urban corridors comprising of 100 street segments of Greater Mumbai region. Result shows that FFS of urban street classes and average travel speed of LOS categories are lower than that mentioned in Highway Capacity Manual (HCM 2000) on account of physical and surrounding environmental characteristics. Also, average travel speed of LOS categories expressed in terms percentage of FFS of urban street classes found to be different from that mentioned in HCM 2010.

A modified Cell Transmission Model with realistic queue discharge features at signalized intersections

Modeling realistic discharge flow-rate and headway features at signalized intersections is critical to the design of traffic signals, since they play a critical role in determining the startup lost times and intersection capacity. Traditional queue discharge models are either microscopic or stochastic, and macroscopic traffic flow models for signalized intersections are based on overly simplistic assumptions. They are incapable of modeling traffic dynamics at signalized intersections as well as capturing realistic queue discharge features.In this study we propose a modified Cell Transmission Model (CTM) by substituting the traditional demand function, which is constant under over-saturated conditions, with a linearly decreasing function. The new demand function is defined through a combination of conventional macroscopic parameters, including critical density, free-flow speed, jam density, and an additional parameter, jam demand. Analytically we show that the new model reproduces observed features in the discharge flow-rate and headway. We further present a new definition of lost times at the macroscopic level based on the modified CTM. Calibration with observations in existing studies, as well as new observations, further suggest that the model can reasonably capture all traffic queue discharge features. We also discuss solutions to the new model under various Riemann problem scenarios and show that they produce realistic results while offering observable improvements in the modeling of traffic dynamics under certain scenarios.

Modelling of Pedestrian Speed-Density and Volume-Density Relationships in Outdoor Walkways

The aim of this study was to model pedestrian flow parameters needed in the design of pedestrian facilities. The study also characterized the flow with a view to understanding pedestrian interaction problems especially with regards to their congestion. Twenty-five locations across Kano metropolis were selected for study, thirteen locations from the city district while twelve sites were chosen from the Waje district. All the sites were high flow pedestrian locations that met the study objectives. The data was categorized into four; young male, adult male, young female and adult female. The results indicated that adult women walked faster than their male counterparts in the City district while young males were faster than the female. The adult female recorded an average speed of 73.90 m/min against the speed of 71.30 m/min for the adult male. The average characteristics of the pedestrian in the city district are speed 67.30 m/min; density 11.23 Ped/m2 and volume 33.60 Ped/m/min. In the Waje district, however, the male pedestrian whether adult or young walked faster than their corresponding female counterparts with speed of 71.45 m/min for the adult male and 59.90 m/min for the adult female. The young male was faster than the young female by 17.9%. The average pedestrian flow parameters for the Waje district indicated a combine speed of 60.21 m/min; density of 8.72 Ped/m2 and volume of 30.92 Ped/m/min. The pedestrians in the city district had a higher flow rate, higher density and higher speed than those of the Waje district. This means the city district is a little more concentrated than the Waje district in terms of pedestrian flow. The aggregate average flow parameters of pedestrians in the metropolitan area gave the following parameters: speed 68.92 m/min; density 10.03 Ped/m2 and volume 32.33 Ped/m/min. The predictive models for Kano showed a free flow speed of 59.55 m/min and a maximum flow rate of 73.0 Ped/m/min. Comparing the Kano pedestrian model with other countries it was found that the Kano pedestrian walked slower than pedestrians from Singapore and the United States

EVALUATION OF SPEED–FLOW CHARACTERISTICS ON TWO-LANE HIGHWAYS WITH MIXED TRAFFIC

The HCM (Highway Capacity Manual 2010) classifies two-lane rural highway that passes through developed areas as ‘Class III’ and suggests using Percent Free-Flow Speed (PFFS) as performance measure to define Level Of Service (LOS). Apparently, this performance measure addresses the main limitation associated with using Average Travel Speed (ATS) as a measure of performance. However, larger speed differential under heterogeneous traffic causes error in estimating Free-Flow Speed (FFS) and thus affects PFFS. This implication was examined in the present study using field data collected on a national highway approaching a city. Speed–flow equations were developed and intercept values were compared to the FFS obtained according to HCM guidelines. Comparison confirms a very close agreement between average FFS value and those obtained for different types of vehicle separately except for car. This consequently causes an error in estimating PFFS since the traffic composition consists of significant proportion of car. The possible capacity of the highway section was observed to be around 2300 pc/h for mixed traffic situation.

Free Speed Modeling for Urban Arterials - A Case Study on Delhi

Free-flow speed is an important characteristic for capacity and level-of-service analysis of urban arterials. The objective of this study is to develop models for estimating free-flow speed. Many generic factors like weather, environment, vehicles, roadway characteristics, driver and traffic streams either singly or in combination influence the free flow speed. The quantitative measures of these factors are desirable for reliable free flow speed measurement and system design. In this paper an attempt has been made to identify the factors which affect the free flow speed. Data collection was done on the midblock segments of urban arterials in Delhi. Further, the geometric properties of the arterial were collected by dividing the given stretch of the road into smaller segments. The factors such as, total number of vehicles, major intersections, access points and length of the sections seem to have a significant influence on free flow speeds.

Influence of Lane and Vehicle Subclass on Free-flow Speeds for Urban Roads in Heterogeneous Traffic

Free-flow speed (FFS) is the speed of vehicles under low volume conditions, when the drivers tend to drive at their desired speed without being affected by control delay. Estimation of FFS is important in several applications. FFS varies extensively across various road facilities as they are influenced by driver behaviour, vehicle characteristics, road factors, landuse, geometric features, control factors, etc.The estimation of FFS in homogeneous traffic is comparatively simpler as the speed variation across vehicles is limited. However, in heterogeneous traffic conditions existing in countries such as India, the FFS distribution varies across vehicle classes. The studies conducted by the authors explored the FFS distribution of various vehicle classes such as two-wheelers, three-wheelers, cars, buses, etc. However, detailed analysis revealed that the variation in FFS can be better explained by further classification of vehicles into subclasses. The study also found that the vehicle's lane position is a factor affecting FFS.The study was conducted on four- and six-lane divided roads in Chennai, India. A total of 24 study sections were chosen for data collection. Speed data were collected during early morning hours to ensure free-flow conditions. The vehicle movements were recorded using video cameras. The details regarding site factors such as carriageway width, link length, landuse, presence of kerb and type of area were collected manually. The speed and lane data were extracted and tabulated from the video recordings. The authors studied the speeds of about 17,800 vehicles (36% two-wheelers, 8% three-wheelers, 8% buses, 33% cars, 10% light commercial vehicles and 5% trucks). The vehicles were classified into 14 subclasses and speeds were analysed. The study also evaluated the effect of lane position on FFS of different classes of vehicles. It was found that vehicles on kerb lanes experienced lower speeds than those on inner lanes. Furthermore, FFS models for four- and six-lane divided roads were developed using multiple linear regression. Significant difference in speeds was observed within and across subclasses of vehicles. The models also evaluated the effects of various road factors such as carriageway width, link length, adjacent landuse type and presence of kerb on FFS. Models such as these can find applications in planning and operational analysis of urban road facilities.

Predicting Free Flow Speed and Crash Risk of Bicycle Traffic Flow Using Artificial Neural Network Models

Free flow speed is a fundamental measure of traffic performance and has been found to affect the severity of crash risk. However, the previous studies lack analysis and modelling of impact factors on bicycles’ free flow speed. The main focus of this study is to develop multilayer back propagation artificial neural network (BPANN) models for the prediction of free flow speed and crash risk on the separated bicycle path. Four different models with considering different combinations of input variables (e.g., path width, traffic condition, bicycle type, and cyclists’ characteristics) were developed. 459 field data samples were collected from eleven bicycle paths in Hangzhou, China, and 70% of total samples were used for training, 15% for validation, and 15% for testing. The results show that considering the input variables of bicycle types and characteristics of cyclists will effectively improve the accuracy of the prediction models. Meanwhile, the parameters of bicycle types have more significant effect on predicting free flow speed of bicycle compared to those of cyclists’ characteristics. The findings could contribute for evaluation, planning, and management of bicycle safety.

Generic Speed–Flow Models for Basic Freeway Segments on General-Purpose and Managed Lanes in Undersaturated Flow Conditions

This paper presents a generic set of undersaturated speed–flow models for basic freeway segments on general purpose and managed lanes (MLs) consistent with the Highway Capacity Manual 2010 (HCM 2010). The proposed models predict segment space mean speed under a wide set of freeway operational conditions that can affect its free-flow speed (FFS) and capacity. Furthermore, the proposed models allow quantifying the impacts of nonrecurring events, such as severe weather conditions, incidents, and work zones on the speed–flow relationship. In addition, the model allows calibration of real-world facilities through adjustments to FFS and capacity. The incorporation of analyses of reliability and active traffic and demand management in the HCM context requires a set of speed–flow models capable of accounting for the effect of nonrecurring sources of congestion. Currently, the HCM 2010 provides a set of speed–flow models to predict space mean speed and consequently other freeway performance measures. This family of equations provides a limited adjustment to FFS. With guidance from NCHRP Project 3-96, separate speed–flow models are proposed for MLs through use of a different form from that in the HCM. The proposed generic equations describing the speed–flow relationship provide consistency between speed–flow relationships of managed and general purpose lanes and can incorporate any capacity or FFS adjustments to predict segment speed under different circumstances. The proposed generic equations are wholly consistent with the speed–flow models in the HCM 2010 and predict the same speed under any flow rate.

Relationship of Lane Width to Capacity for Urban Expressways

To increase the capacity of urban expressways in Shanghai, China, additional lanes were created during the past decade through reconstruction. Field measurements indicate that maximum lane width is 3.97 m and minimum width is only 2.73 m. To investigate the relationship between lane width and capacity for urban expressways, 3 months of traffic flow data were extracted and filtered from the system to manage inductive detectors on Shanghai's urban expressways. Analysis of all 440 segments of expressways in Shanghai showed that only 60 sites could reach their capacity; the characteristics of these 60 sites were further analyzed statistically. An analysis of a variance, a regression analysis, and a t-test were used to explore the relationship between lane width and capacity. The research showed that lane width had no statistically significant effect on capacity. Two causes that might account for this finding are discussed further: (a) free-flow speeds are similar for different lane widths according to the findings of a t-test that found no statistically significant differences and (b) the critical speed when capacity is reached for a Shanghai expressway is very low, only 45 km/h. Thus, drivers can deal with a narrow lane width at such a low critical speed. This finding suggests that geometric design policies for capacity purposes should provide substantial flexibility for use of narrower lane widths on urban expressways with low speed limits, although those lane widths must be subject to safety considerations.

Planning-Level Methodology for Freeway Facilities

This paper presents a planning-level methodology for the analysis of freeway facilities. The proposed approach is based on and compatible with the operational method of the Highway Capacity Manual 2010 (HCM 2010). The approach is specifically constructed with the intent to minimize input data requirements. The method covers both under- and oversaturated flow conditions and produces estimates of travel time, speed, density, and level of service. The underlying methodology relies on developing a relationship between a basic freeway segment's delay rate per unit distance and its demand-to-capacity ratio. For weaving segments, the study develops capacity adjustment factors on the basis of volume ratio and segment length. With these factors, demand-to-capacity ratios on weave segments were adjusted and the segment was treated similarly to a basic freeway segment. For merge and diverge segments, a novel methodology is proposed to estimate their capacity on the basis of demand level, free-flow speed, and space mean speed. Subsequently, capacity adjustment factors are calculated on those segments and their demand-to-capacity ratios are adjusted accordingly. The proposed approach is applied to two examples in the HCM 2010 and produced very promising results. For undersaturated flow conditions, facility travel time is at most 3.4% and density was at most 1.1% at variance from the results found by applying the HCM 2010 operational methodology. The corresponding differences for oversaturated conditions are 6.7% and 13.0%, respectively.

Automatic Congestion Identification with Two-Component Mixture Models

Automatic identification of traffic congestion is an important component of any intelligent transportation system. These systems need computer algorithms to identify current congestion and to predict the evolution of future congestion. The output of the congestion identification algorithm enables various users to be better informed and make safer, more coordinated, and smarter use of transportation networks. A new automatic congestion identification algorithm was proposed; it assumed that the speed data were drawn from a two-component mixture model. The first component represented the speed distribution in congestion, and the second component was the free-flow speed distribution. The proposed algorithm was first calibrated by using historical speed data in a two-component mixture model. A free-flow speed threshold based on the estimated parameters of the free-flow speed distribution was set. Subsequently, a road segment was identified as having free flow if its speed was greater than the threshold and congested if its speed was less than the threshold. The mixture components considered lognormal and gamma-skewed distributions and normal symmetric distributions. The proposed algorithm was tested by using two real data sets collected from two different roadways and was demonstrated to produce good performance.

Methodology to Compute Travel Time of a Roundabout Corridor

Urban and suburban arterials with roundabouts in series are becoming more prevalent in North America. While the Highway Capacity Manual (HCM) provides a methodology for computing segment travel time of urban streets with various forms of intersection control, the manual does not provide a similar procedure for corridors with interdependent roundabouts. Such a methodology is necessary to evaluate performance of roundabout corridors and will allow the practitioner to compare both roundabout and signalized treatments for the same series of intersections. This paper presents a series of models intended to predict arterial travel time for a corridor with roundabouts, including a model for free-flow speed (FFS), a model to predict the length of the roundabout influence area (RIA, the area where geometric delay has incurred), a model for geometric delay, and models for impeded delay and average travel speed. These models were calibrated with data from seven roundabout corridors. The resulting models suggest that while FFS is a function of segment length, posted speed limit, and central island diameter, RIA length and geometric delay are functions of the FFS itself, as well as other geometric elements. The impeded delay and average travel speed are functions of traffic congestion and FFS. After validating the models with travel time data from two additional roundabout corridors not used in model development, the authors present a framework for incorporating the procedure for travel time prediction into the HCM analysis of urban streets.

Performance Measures to Characterize Corridor Travel Time Delay Based on Probe Vehicle Data

Anonymous probe vehicle data are being collected on roadways throughout the United States. These data are incorporated into local and statewide mobility reports to measure the performance of highways and arterial systems. Predefined spatially located segments, known as traffic message channels (TMCs), are spatially and temporally joined with probe vehicle speed data. Through the analysis of these data, transportation agencies have been developing agencywide travel time performance measures. One widely accepted performance measure is travel time reliability, which is calculated along a series of TMCs. When reliable travel times are not achieved because of incidents and recurring congestion, it is desirable to understand the time and the location of these occurrences so that the corridor can be proactively managed. This research emphasizes a visually intuitive methodology that aggregates a series of TMC segments based on a cursory review of congestion hotspots within a corridor. Instead of a fixed congestion speed threshold, each TMC is assigned a congestion threshold based on the 70th percentile of the 15-min average speeds between 02:00 and 06:00. An analysis of approximately 90 million speed records collected in 2013 along I-80 in northern New Jersey was performed for this project. Travel time inflation, the time exceeding the expected travel time at 70% of measured free-flow speed, was used to evaluate each of the 166 directional TMC segments along 70 mi of I-80. This performance measure accounts for speed variability caused by roadway geometry and other Highway Capacity Manual speed-reducing friction factors associated with each TMC.

Full Bayesian Mixed-Effect Intervention Model for Before–After Speed Data Analysis

The analysis of before–after speed data to evaluate the effectiveness of safety interventions is often limited to a non-model-based comparison of speed-related indicators. Moreover, modeling of speed data often does not take into account the nested nature of the data. The objective of the study was to quantify the effect of posted speed limit (PSL) reductions in an urban, residential context. The study employed a mixed-effect intervention model, which could address limitations of existing methods. To model mean free-flow speed and the probability of a speed being below or equal to various thresholds, mixed-effect normal regression and binomial logistic regression models were used. Use of a comprehensive, unique, and disaggregated data set enabled not only the before–after evaluation of the PSL reduction but also the exploration of the effects of various temporal, traffic, and road geometry factors on speed. Results demonstrated the appropriateness of using the mixed-effect model for speed data. Parameter estimations showed that nighttimes; weekends; a high proportion of vans, buses, and trucks; evening peak periods; collector roads; and low hourly traffic volumes were all associated with an increase in the mean free-flow speed and a decrease in the probability of speeds being below or equal to various thresholds. Evaluation results showed the mean free-flow speed was reduced by 3.85 km/h in the after period and that speeds below or equal to 50, 60, 70, and 80 km/h increased by 20.0%, 9.2%, 2.8%, and 0.9%, respectively. All improvements were statistically significant; this finding implied that the PSL reduction was effective at influencing vehicle speed.

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

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.

Empirical Evidences of Dynamic Speed Limit Impact on a Metropolitan Freeway

The claimed benefits of dynamic speed limit (DSL) strategies (e.g. increase of throughput or speed homogenization) still remain as a controversial topic. The present paper presents an empirical assessment of DSL policies with aggregated traffic flow data.A DSL system installed on the C-32 metropolitan freeway accessing the city of Barcelona (Spain) since February 2009 allows a before-after comparison between non-DSL and DSL scenarios. In order to achieve this objective, a new methodology is proposed. It includes speed-based data stratification for assessing the DSL drivers’ compliance, detecting the causes which motivate drivers’ behavior and the main DSL algorithms inefficiencies. In addition, a computation-friendly approach for searching stationary traffic periods is developed, differing from Cassidy (1998). The whole process permits to obtain a clear fundamental diagram characterization under DSL strategies.The paper proves that when speed limits are lower than free-flow speed, the slope of the free-flow branch of the fundamental diagram is lowered proportionally. This implies that critical occupancies are higher than in their non-DSL analogues. Remarkably, almost any capacity increase is reported in the vicinity of the analyzed bottleneck.

Analysis of Traffic Flow Speed-Density Relation Model Characteristics

AbstractThe fundamental diagram is the graphical representation of the relations between traffic flow, speed, and density, and has long been the foundation of traffic flow theory and transportation engineering. Eighty years after the seminal Greenshields model, a variety of models have been proposed to mathematically represent the speed-density relation. Speed-density relation models play an important role in understanding how a shock wave propagates through traffic, as well as determining level of service. In this paper, 10 typical speed-density relation models are summarized and analyzed by parameter calibrations and fitting errors using Beijing Expressway data. The results show that fitting errors for speed-density models are not sensitive to using different sets of field data, whereas some physically meaningful parameters, such as free-flow speed and jam density, vary widely under different sets of field data. The Newell and Logistic models demonstrate good stability. This research provides practical ...

The impact of precipitation on land interfacility transport times.

Timely transfer of patients among facilities within a regionalized critical-care system remains a large obstacle to effective patient care. For medical transport systems where dispatchers are responsible for planning these interfacility transfers, accurate estimates of interfacility transfer times play a large role in planning and resource-allocation decisions. However, the impact of adverse weather conditions on transfer times is not well understood. Precipitation negatively impacts driving conditions and can decrease free-flow speeds and increase travel times. The objective of this research was to quantify and model the effects of different precipitation types on land travel times for interfacility patient transfers. It was hypothesized that the effects of precipitation would accumulate as the distance of the transfer increased, and they would differ based on the type of precipitation. Urgent and emergent interfacility transfers carried out by the medical transport system in Ontario from 2005 through 2011 were linked to Environment Canada's (Gatineau, Quebec, Canada) climate data. Two linear models were built to estimate travel times based on precipitation type and driving distance: one for transfers between cities (intercity) and another for transfers within a city (intracity). Precipitation affected both transfer types. For intercity transfers, the magnitude of the delays increased as driving distance increased. For median-distance intercity transfers (48 km), snow produced delays of approximately 9.1% (3.1 minutes), while rain produced delays of 8.4% (2.9 minutes). For intracity transfers, the magnitude of delays attributed to precipitation did not depend on distance driven. Transfers in rain were 8.6% longer (1.7 minutes) compared to no precipitation, whereas only statistically marginal effects were observed for snow. Precipitation increases the duration of interfacility land ambulance travel times by eight percent to ten percent. For transfers between cities, snow is associated with the longest delays (versus rain), but for transfers within a single city, rain is associated with the longest delays.

Isothermal velocity measurements in two HyperVapotron geometries using Particle Image Velocimetry (PIV)

HyperVapotron beam stopping elements are high heat flux devices able to transfer large amounts of heat (of the order of 10–20MW/m2) efficiently and reliably making them strong candidates as plasma facing components for future nuclear fusion reactors or other applications where high heat flux transfer is required. They employ the Vapotron effect, a two phase complex heat transfer mechanism. The physics of operation of the device are not well understood and are believed to be strongly linked to the evolution of the flow fields of coolant flowing inside the grooves that form part of the design. An experimental study of the spatial and temporal behaviour of the flow field under isothermal conditions has been carried out on two replicas of HyperVapotron geometries taken from the Mega Amp Spherical Tokamak (MAST) and the Joint European Torus (JET) experiments. The models were tested under three isothermal operating conditions to collect coolant flow data and assess how the design and operational conditions might affect the thermal performance of the devices for single phase heat transfer. It was discovered that the in-groove speeds of MAST are lower and the flow structures less stable but less sensitive to free stream speed perturbations compared to the JET geometry. The MAST geometry was found to suffer from hydrodynamic end effects. A wake formation was discovered at the top of the groove entrance for the JET geometry, while this is absent from the MAST geometry. The wake does not affect significantly the mean operation of the device but it may affect the coolant pumping load of the device. For the JET variant, there is evidence that the typical operation with free stream flow speed of 6m/s is advantageous.

Collision-free nonuniform dynamics within continuous optimal velocity models.

Optimal velocity (OV) car-following models give with few parameters stable stop-and -go waves propagating like in empirical data. Unfortunately, classical OV models locally oscillate with vehicles colliding and moving backward. In order to solve this problem, the models have to be completed with additional parameters. This leads to an increase of the complexity. In this paper, a new OV model with no additional parameters is defined. For any value of the inputs, the model is intrinsically asymmetric and collision-free. This is achieved by using a first-order ordinary model with two predecessors in interaction, instead of the usual inertial delayed first-order or second-order models coupled with the predecessor. The model has stable uniform solutions as well as various stable stop-and -go patterns with bimodal distribution of the speed. As observable in real data, the modal speed values in congested states are not restricted to the free flow speed and zero. They depend on the form of the OV function. Properties of linear, concave, convex, or sigmoid speed functions are explored with no limitation due to collisions.