Desired Speed Distribution Research Articles

Determining Desired Speeds from Vehicle Trajectory Data

Desired speed or free speed distributions are important input parameters for microscopic traffic flow simulations. Whereas driven speeds can be measured, desired speeds are not detectable for all vehicles because of vehicles constraining each other. An established approach to estimating desired speed distributions is the modified Kaplan–Meier approach, which estimates desired speed distributions based on single vehicle data from stationary detectors. We propose a novel approach to determine desired speeds based on vehicle trajectory data. The proposed approach, as well as the modified Kaplan–Meier approach, is applied to a trajectory dataset recorded on a German freeway. With the modified Kaplan–Meier approach, we observed that the resulting desired speed distributions vary by approximately 5 km/h depending on the position of the stationary detectors. The desired speed distributions obtained from the trajectory-based approach are approximately 5 to 10 km/h higher than those estimated by the modified Kaplan–Meier approach. This difference in results is probably because the trajectory-based approach observes each vehicle over a longer distance rather than just at stationary points. Nevertheless, it can be concluded that the estimation of desired speed distributions is subject to a certain degree of inaccuracy. The analysis of the vehicle trajectory data revealed a notable intra-vehicle instability in desired speeds, with a difference of 5 to 7 km/h observed for 40% of the vehicles between different periods of free driving. These findings should be considered in the context of calibrating microscopic traffic flow simulations.

Bicycle as a traffic mode: From microscopic cycling behavior to macroscopic bicycle flow

Cities allocate dedicated road space to bicycles in favor of active-mode road users. For urban environments with a mass bicycle volume, bicycle traffic congestion is likely to occur. Hence, a thorough understanding of bicycle traffic flow is necessary for the assessment of cycling infrastructure and the development of traffic management strategies considering cycling efficiency. This study aims to investigate bicycle flow characteristics using microscopic traffic simulation. As bicycle flow performance is subject to the non-lane-based movement strategy and the behavioral heterogeneity among cyclists, various scenarios with different microsimulation settings are evaluated. Ultimately, we derive the functional form fundamental diagrams and macroscopic fundamental diagrams using a curve-fitting approach and an analytical method, respectively. Important macroscopic traffic flow parameters, such as capacity, critical speed, critical density, backward wave speed, etc., are estimated. The results show that lane width, overtaking incentive, and desired speed distribution are factors that affect bicycle flow performance. The distinct features of bicycle flow under different traffic states are identified by discussing the simulation outcome and comparing the estimated flow parameters. The findings can be utilized by future research regarding large-scale bicycle traffic flow modeling and control.

Modelling speed behaviour in rural highways: Safety analysis of driving under adverse road-weather conditions.

This study proposes a methodical approach to model desired speed distributions under different road-weather and traffic conditions followed by identification of road-weather conditions with potentially higher safety risks in rural divided highways located in extremely cold regions. Desired speed distributions encompassing unique combinations of adverse road-weather and traffic conditions are modelled as normal distributions characterized by their means and standard deviations formulated based on two principal statistical theorems and techniques i.e., Central Limit Theorem and Minimum Variance Unbiased Estimation. Combination of the precipitation conditions, road surface conditions, time of the day, temperature, traffic flow and the heavy vehicle percentage at the time of travel were considered in defining the combinations of road-weather and traffic conditions. The findings reveal that simultaneous occurrence of particular precipitation and pavement conditions significantly affect the characteristics of the desired speed distribution and potentially expose drivers to elevated safety risks. Jurisdictions experiencing extreme road-weather conditions may adapt the proposed methodology to assess speed behaviour under different road-weather conditions to establishing and deploying weather-responsive traffic management strategies such as variable speed limit to regulate speeding and improve traffic safety in winter.

Global sensitivity analysis of VISSIM parameters for project-level traffic emissions: a case study at a signalized intersection

ABSTRACT Combining traffic micro-simulation models and emission models is a primary method to estimate traffic emissions. However, there has been limited research on the impact of traffic micro-simulation model parameters on simulator outputs, which are critical to emissions calculations. Based on combining VISSIM and MOVES, this study uses the Morris and Sobol methods to explore the impact of parameters in VISSIM on operating mode distribution and travel time distribution. Taking an urban signal control intersection with three traffic scenarios in Chengdu, China as an example, this study verifies the methods’ feasibility. Apart from these parameters, which have been proved to be necessary calibration parameters, including the desired speed distribution, the desired acceleration function, and the desired deceleration function, an additional 24 parameters related to simulation setting and driving behaviour models are selected as the initial parameters. The number of interaction objects, maximum look-ahead distance, average standstill distance, additive part of safety distance, and safety distance reduction factor close to a stop line, are considered to be the important parameters for this case study. The impact of these five parameters on the bins of operating mode distribution and travel time distribution are further analyzed with One-at-a-time, and these parameters are compared with those reported in previous studies. It is concluded that the important parameters selected in this study are reasonable and can support the calibration of VISSIM parameters for this case’s traffic emissions.

Calibrating Microsimulation Parameters for Vehicular Travel Time

Travel time is one of the simplest yet the most important parameter for transportation facility users as well as transportation engineers. Travel time data is valuable for widerange of transportation analysis including congestion management, transportation planning and passenger’sdecision making.Traffic simulation models are now becoming necessary tools to understand the behavior of traffic and reduce vehicular travel times, but it is very important to calibrate these models first. Thisstudy attempts to determines the values of those parameters,using microsimulation,that significantly affect the travel time. These parameters arethenused for calibrating the traffic simulation model that results in realistic travel time.Study was conducted on an urban road andfield data was collected during weekdays for peak hours. The traffic network was modelled usingVISSIM®.The calibration parameters were desired speed distribution, number of lanes,average standstill distance and minimum headway. After calibrating the model, the travel times collected from field data and those by simulations for different modes of transportation were in close agreement.

Parameters Influencing Lane Flow Distribution on Multilane Freeways in PTV Vissim

Abstract In a parameter study, we systematically varied parameter values, and quantified the resulting traffic flow in each individual lane. We modeled two-, three-, and four-lane freeway sections with the microscopic traffic flow simulation tool PTV Vissim. We compared the results with findings from literature. Simulations using car following model Wiedemann 99 fit better to empirical studies than those using Wiedemann 74. Empirically determinable parameters, that have a relevant influence on lane flow distribution are desired speed distributions (mean for heavy-duty vehicles and standard deviation for cars), heavy-duty vehicle share, and the gradient of the section. Additionally, the driving behavior parameters CC1 (headway time), CC3 (threshold for entering following), and safety distance reduction factor have an influence. As CC1 is one of the most relevant parameters for calibrating capacity, CC3 and the safety distance reduction factor remain for lane flow adjustment.

A Method for Joint Estimation of Homogeneous Model Parameters and Heterogeneous Desired Speeds

One of the main strengths of microscopic pedestrian simulation models is the ability to explicitly represent the heterogeneity of the pedestrian population. Most pedestrian populations are heterogeneous with respect to the desired speed, and the outputs of microscopic models are naturally sensitive to the desired speed; it has a direct effect on the flow and travel time, thus strongly affecting results that are of interest when applying pedestrian simulation models in practice. An inaccurate desired speed distribution will in most cases lead to inaccurate simulation results. In this paper we propose a method to estimate the desired speed distribution by treating the desired speeds as model parameters to be adjusted in the calibration together with other model parameters. This leads to an optimization problem that is computationally costly to solve for large data sets. We propose a heuristic method to solve this optimization problem by decomposing the original problem in simpler parts that are solved separately. We demonstrate the method on trajectory data from Stockholm central station and analyze the results to conclude that the method is able to produce a plausible desired speed distribution under slightly congested conditions.

Simulation-Based Analysis of the Effect of Significant Traffic Parameters on Lane Changing for Driving Logic “Cautious” on a Freeway

Lane changing of traffic flow is a complicated and significant behavior for traffic safety on the road. Frequent lane changing can cause serious traffic safety issues, particularly on a two-lane road section of a freeway. This study aimed to analyze the effect of significant traffic parameters for traffic safety on lane change frequency using the studied calibrated values for driving logic “conscious” in VISSIM. Video-recorded traffic data were utilized to calibrate the model under specified traffic conditions, and the relationship between observed variables were estimated using simulation plots. The results revealed that changes in average desired speed and traffic volume had a positive relationship with lane change frequency. In addition, lane change frequency was observed to be higher when the speed distribution was set large. 3D surface plots were also developed to show the integrated effect of specified traffic parameters on lane change frequency. Results showed that high average desired speed and large desired speed distribution coupled with high traffic volume increased the lane change frequency tremendously. The study also attempted to develop a regression model to quantify the effect of the observed parameters on lane change frequency. The regression model results showed that desired speed distribution had the highest effect on lane change frequency compared to other traffic parameters. The findings of the current study highlight the most significant traffic parameters that influence the lane change frequency.

Micro-simulation of Desired Speed for Temporary Work Zone with a New Calibration Method

Nowadays, the studies of parameter calibration for long-term work zones are limited to driver behaviour and car-following parameters, and no research was found related to calibration of the desired speed distributions during temporary work zones. Obtaining realistic results from simulations of temporary work zones is difficult. Thus, it would be valuable for gaining more valid simulation data if a method of calibrating the desired speed distribution could be applied for traffic simulation model of highway temporary work zones. The calibration method was proposed in five steps: (1) collect and analyse data, (2) plot the travel speed cumulative frequency curves and calibrate the desired speed distribution, (3) conduct simulation runs, (4) validate the simulation results, and (5) propose a new calibration method, which was assessed by T-tests, and the results are very promising. Finally, a simplified calibration method called “Five-Point Method” is presented and the recommended values of five-point are given.

Effects of desired speeds for queuing and delay on single-lane road segments

To improve road safety on parts of the road network carrying low traffic volumes, road designs are proposed including single-lane road segments and periodic overtaking lanes. These roads have been proven to contribute to substantial benefits in terms of road safety. However, overtaking of slower vehicles is only possible on segments including an overtaking lane and not on the single-lane road segments. Driver and vehicle heterogeneity resulting in differences in desired speeds are consequently decisive for the traffic performance. Sufficient quality of service is relying on an appropriate design and distribution of single-lane segments and overtaking lanes. In this paper, we study the effect of the desired speed distribution on traffic performance on single-lane road segments. Expressions are derived for the travel time, delay and percent time spent following. The derived expressions link the desired speed distribution, the single-lane segment length and the traffic flow to the resulting traffic performance. The results are verified through comparison with measures based on microscopic traffic simulation. The conclusion is that there is a good agreement between derived measures and simulation results. The derived measures should therefore not only be of theoretical interest, but also of practical use to estimate traffic performance on single-lane road segments.

Driving Type Categorizing and Microscopic Simulation Model Calibration

Microsimulation programs, before being used for traffic analysis in practice, should be calibrated to reproduce the traffic characteristics and to represent the driver population in reality. A driver behavior questionnaire survey conducted in China revealed that significant differences in driving behavior existed in drivers. Calibration should be done by taking these differences in driving style into account. In this study, 30 drivers in Changsha, China, were invited to participate in in-car tests and complete a questionnaire. Factor analysis revealed the interdependencies between observed acceleration or deceleration characteristics and other variables. Four driving types were classified according to the four factor scores. Further analysis of repeated trips validated the consistency of driver membership within a class. A censoring method was applied to calibrate the desired acceleration functions and desired speed distributions in a simulation model for these four driving types. Distinct differences were found in desired speed and maximum desired acceleration or deceleration of the four driving types. It is expected that the categorization of driving types will be useful in model calibration.

Modeling Highway Safety and Simulation in Rainy Weather

Research was done to examine comprehensively the safety impact of rainy weather conditions on multivehicle crash frequency and severity and to validate the impact on traffic operations through microsimulation modeling. Three primary tasks were performed to meet these objectives. For weather data processing, available data were used to estimate the following factors: rainfall intensity, water film depth, and deficiency of car-following distance. For statistical modeling, negative binomial regression was used for crash frequency, and sequential logistic regression was tested with forward and backward formats for crash severity. A better format for the crash severity estimation was determined by combining all model performance measures. VISSIM was used to design traffic simulation models to reflect the effect of weather on traffic operation with five scenarios of the following weather-sensitive parameter adjustments: desired deceleration rate function, desired speed distribution, and headway time. As weather-related determinants, daily rainfall and wind speed were found to be statistically significant to crash frequency and severity estimations, respectively. VISSIM provided the most similar traffic data to the observed data when both desired speed distribution and deceleration rate function were adjusted. Statistical modeling in this research can be used to examine highway safety in rainy weather and to provide quantitative support on implementing road weather safety management strategies. Correspondingly, the adjustments of weather-sensitive traffic parameters will be the preliminary step to measure the strategy efficiencies through safety surrogate indexes in traffic simulation.

Effect of desired speed variability on highway traffic flow

Traffic flow is a function of many natural, environmental, and human factors. Not only that weather and road condition can vary, but drivers' decisions and policies also can affect the flow. Here we analyze the effect of distribution of desired speeds. We show that a broader distribution can reduce the flow efficiency and increase congestions. Since different drivers react differently to changes in weather or road conditions, such a change leads to a change in desired speed distribution as well. As a result, nonintuitive changes in traffic flow may occur. Besides providing insight and analyzing the underlying mechanism of a collective phenomenon, this example sheds light on a fundamental aspect of computational modeling. Although "mean-field" models that deal with average values only and ignore variability are simpler and easier to analyze, they can very easily turn into oversimplifications and miss relevant qualitative phenomena.

Effects of geometric design on freeway capacity: Impacts of truck lane restrictions

This paper presents a framework for estimating analytical expressions for the capacity reductions caused by a subset of vehicles forced to slow down at horizontal/vertical curves on multilane freeways. In each lane the underperforming stream is described in terms of its desired speed distribution (either discrete or continuous), and it is explicitly modeled as a stochastic process that disturbs light vehicles as per Newell’s kinematic wave theory of moving bottlenecks. The model is applied for estimating the impact of truck lane restrictions. It is found that system capacity is maximized either (i) when each truck type uses a different lane or (ii) when they share the same lane, depending on the relative proportion of heavy trucks. Moreover, this application sheds some light to the puzzling empirical result in several places around the world, where time and time again it is observed that the operational improvements of truck lane restrictions are small or negligible.

Desired Speed Distributions on Two-Lane Highways under various Conditions

On a two-lane highway with passing restrictions, user dissatisfaction usually is caused by the inability to drive at the desired speed because of a relatively slower lead vehicle. Although this condition clearly shows that vehicles in this state are following, current definitions of “following vehicle” are based mainly on headway alone. A “follower” can be more logically defined as a vehicle traveling below its desired speed because of the presence of a relatively slower lead vehicle. The problem arises because the desired speeds of different drivers vary significantly; the variation makes it difficult to assess whether a vehicle is constrained on the basis of directly accessible data alone. A study was done to develop desired speed distributions for various traffic, weather, and ambient conditions, which can be later used as input for simulation or to calculate a vehicle's following probability given its current speed. The collected data were classified according to different traffic, geometric, weather, and ambient conditions to form 64 data sets for analysis. The desired speed distributions were estimated by using the modified Kaplan-Meier approach and were found to be suitable for use as either simulation input or as a tool that can be used for follower identification. Differences between holiday and weekday travel speed preferences and effects of weather on driver speed choices were also found.

Impact of Active Speed Limiters on Traffic Flow and Safety

Speed limiters, which control the maximum speeds of vehicles so equipped, have been proposed in recent years as speed management tools. A simulation-based evaluation is described of the impact of a wide installation of speed limiters on traffic flow characteristics and on safety. Microscopic traffic simulation is used; it models the driving behavior of individual vehicles in detail and so captures not only the impact of speed limiters on equipped vehicles but also the interaction between equipped and unequipped vehicles and the resulting impact on the latter. In the experiment, the impact is evaluated of preset speed limiters for two limiter-set speeds, 100 km/h and 120 km/h, at various desired speed distributions and congestion levels. The simulation results show that speed limiters can reduce average traffic speeds up to 10% and that the variability of traffic speeds may also be lowered. Consequently, a significant reduction in accident rates might be achieved.

On a kinetic model of the internet traffic

We present the modification of the Prigogine‐Herman kinetic equation related to the network traffic. We discuss a solution of this equation for homogeneous time‐independent situations and for the lognormal desired speed distribution function, obtained from the traffic measurements. This solution clearly shows two modes corresponding to individual flow patterns (low concentration mode) and to collective flow patterns (traffic jam mode). For situations with low concentration, there is almost a linear dependence of the information flow versus the concentration and the higher the average speed the lower the concentration at which the optimum flow takes place. When approaching the critical concentration, there are no essential differences in the flow for different average speeds, whereas for the individual flow regions there are dramatic differences.

Kinetic model of network traffic

We present the first results on the application of the Prigogine–Herman kinetic approach (Kinetic Theory of Vehicular Traffic, American Elsevier Publishing Company, Inc., New York, 1971) to the network traffic. We discuss the solution of the kinetic equation for homogeneous time-independent situations and for the desired speed distribution function, obtained from traffic measurements analysis. For the log-normal desired speed distribution function the solution clearly shows two modes corresponding to individual flow patterns (low-concentration mode) and to collective flow patterns (traffic jam mode). For low-concentration situations we found almost linear dependence of the information flow versus the concentration and that the higher the average speed the lower the concentration at which the optimum flow takes place. When approaching the critical concentration there are no essential differences in the flow for different desired average speeds, whereas for the individual flow regions there are dramatic differences.

On single-lane roads

A road which narrows at a bottleneck from an ∞-lane road to a one-lane road is studied with the aid of two stochastic processes. Special attention is given to headways and gaps. At the bottleneck an equilibrium headway can be viewed as the maximum of a shifted exponential random variable and a minimum headway. After the bottleneck the situation becomes far more complicated. However, limiting results are obtained for headways and gaps at a large distance from the bottleneck. The asymptotic behavior of headways and gaps is largely determined by the behavior of the desired speed distribution at the lower extreme of its support.

On single-lane roads

A road which narrows at a bottleneck from an ∞-lane road to a one-lane road is studied with the aid of two stochastic processes. Special attention is given to headways and gaps. At the bottleneck an equilibrium headway can be viewed as the maximum of a shifted exponential random variable and a minimum headway. After the bottleneck the situation becomes far more complicated. However, limiting results are obtained for headways and gaps at a large distance from the bottleneck. The asymptotic behavior of headways and gaps is largely determined by the behavior of the desired speed distribution at the lower extreme of its support.