Speed-flow Models Research Articles

Novel Speed-Flow Model Based on Queuing Theory and Its Potential Application in Highway Capacity Guidelines

Speed-flow relationships are incorporated in many highway capacity guidelines such as the U.S. Highway Capacity Manual (HCM) and the German Highway Capacity Manual (HBS). The speed-flow relationship can be used to predict the operating speed depending on the traffic volume. Based on traffic-flow theory, many models for the speed-flow relationship under fluid and congested traffic conditions have been developed. However, most of the speed-flow relationships used in guidelines are either based on empirical regression analysis and thus lack a theoretical background or include model parameters that do not have a realistic meaning. In this paper, a speed-flow relationship is derived based on the queuing theory in a form that the main model parameters can be expressed as real traffic-flow parameters, which can be obtained by field measurements. These parameters are the free-flow speed, the potential capacity of the imbedded queuing system, and a parameter for the stochastics of the queuing system. By varying the model parameters, different geometric, traffic, and control conditions can be considered. Even the impact of new technologies such as connected and automated vehicles can be accounted for by adjusting those parameters.

Electric Vehicle Charging Load Prediction Model Considering Traffic Conditions and Temperature

The paper presents a novel charging load prediction model for electric vehicles that takes into account traffic conditions and ambient temperature, which are often overlooked in conventional EV load prediction models. Additionally, the paper investigates the impact of disordered charging on distribution networks. Firstly, the paper creates a traffic road network topology and speed-flow model to accurately simulate the driving status of EVs on real road networks. Next, we calculate the electric vehicle power consumption per unit kilometer by considering the effects of temperature and vehicle speed on electricity consumption. Then, we combine the vehicle’s main parameters to create a single electric vehicle charging model, use the Monte Carlo method to simulate electric vehicle travel behavior and charging, and obtain the spatial and temporal distribution of total charging load. Finally, the actual traffic road network and typical distribution network in northern China are used to analyze charging load forecast estimates for each typical functional area under real vehicle–road circumstances. The results show that the charging load demand in different areas has obvious spatial and temporal distribution characteristics and differences, and traffic conditions and temperature factors have a significant impact on electric vehicle charging load.

Nationwide Demand Modeling for an Urban Air Mobility Commuting Mission

In this paper, we present a comprehensive and reproducible urban air mobility (UAM) demand model centered around publicly available data and open source tools capable of demand estimation at the national level. A discrete mode-choice demand model is developed using longitudinal origin–destination employment statistics flow data, American community survey economic data, and the Open Source Routing Machine (OSRM) to identify the utility of a UAM commuter service relative to other modes of transportation. Using the implemented model, we identify New York City, San Francisco, and Los Angeles as cities with the highest potential commuter demand, and Seattle as the city most resilient to increases in delay time. A sensitivity study of demand is performed and shows that strong demand exists for short trips with low total delay times and for longer trips with a low ticket price per kilometer, with the former showing resilience to increases in operational costs and the latter showing resilience to increases in delays. The demand model is supported by a speed-flow model, which fuses highway performance monitoring system data with OpenStreetMap data to provide traffic-adjusted road segment speeds to OSRM. The speed-flow model has the capability of providing congestion data for road segments across the United States without the use of commercial data sets or routing services and is shown to improve routing duration accuracy in congested regions.

Emergency Evacuation Based on Cellular Automata

With the increasing number or scale of large-scale assembly activities, emergency evacuation has become increasingly important. In order to understand the evacuation behavior of people, this paper uses European distance, simulation and other methods to optimize the research and design of evacuation in emergency. The main contents of this paper are as follows: First, based on the principle and update rules of cellular automata, determine the three key factors of gender, age and emotional intensity, and the evacuation model based on cellular automata, and then use MATLAB software to simulate the change of people flow under different anxiety conditions, and output relevant data and visual images. Finally, the differences of the experimental results caused by the key factors are discussed. Secondly, study the evacuation rate change curve, as well as the key factors and their effects. Based on the average speed and average flow model of the system, simulate and output the corresponding visual images. Thirdly, in order to study and determine the best simulated evacuation route and the dynamic process of personnel evacuation in the case of different door widths, based on the evacuation route selection model with the shortest time to reach the two doors, the best pedestrian evacuation route is selected according to the shortest time rule. Fourth, in order to study the impact of reduced visibility in the hall on the whole process. In this paper, the regional discretization method is used to establish the perception range model under visibility and analyze the factor changes in the whole process.

MOVES-Beijing-based high spatial and temporal resolution ammonia emissions from road traffic in Beijing

Ammonia (NH3) is an important precursor of PM2.5 (particulate matter with aerodynamic diameter below 2.5 μm). In recent years, ammonia emissions from road traffic notably increased, growing pollution of PM2.5. Therefore, addressing spatial and temporal ammonia emissions from road traffic is a keyword for controlling urban traffic pollution. However, most of current China's ammonia emissions inventories are annual emissions, lack of spatial and temporal information, which is a gap for governments to make effective and practical policies in terms of controlling road traffic pollution. In this study, based on the built MOVES-Beijing Model, the ammonia emission factors of eight types of vehicle in Beijing, including passenger car (PC), TAXI, middle-duty vehicle (MDV), heavy-duty vehicle (HDV), light-duty truck (LDT), middle-duty gasoline truck (MDGT); middle-duty diesel truck (MDDT) and heavy-duty truck (HDT), were obtained. And through the modified local speed-flow model, the traffic flow was obtained acquisitively with the average speed data of the main roads in Beijing. The road length data were obtained according to the ranging function in the Gaode map and the status of Beijing. Then the high spatial and temporal ammonia emission inventory in Beijing was achieved. The results showed the order of ammonia emission factors (EFs) for different types of vehicles was MDGT > HDV > MDDT > HDT > LDT > TAXI > MDV > PC, and ammonia EFs were the lowest when the vehicle speed was around 48 km/h. Total ammonia emissions on weekdays were slightly higher than on weekends, but were not significant, although there are restrictions during the week. And ammonia emissions from ordinary roads were the highest among the three types of roads, including highways and urban expressways. Due to heavy traffic, ammonia emissions were highest during peak 1 periods. PC's ammonia emissions were 68% due to its larger population.

A study of high temporal-spatial resolution greenhouse gas emissions inventory for on-road vehicles based on traffic speed-flow model: A case of Beijing

In order to explore the establishment method of high-resolution vehicle emission inventory and analyze the temporal and spatial variation law of vehicle greenhouse gases (GHG) emissions. This paper proposes a bottom-up method based on road network information and the real-time average interval speed of road segments. A traffic speed-flow model is proposed to predict the hourly traffic flow and the localized Motor Vehicle Emission Simulator (MOVES) is used to simulate the CO2, N2O and CH4 emission factors. A high temporal (1 h × 1 h) and spatial (1 km × 1 km) resolution GHG emission inventory of motor vehicles in Beijing in 2018 is developed by this means. The actual emissions of CO2, N2O and CH4 are 19,864,590, 82 and 511 t, respectively. And the total GHG emission is 19,901,933 tCO2e combined with global warming potential (GWP). The daily GHG emissions on weekday and weekend are 55206.30 and 52817.64 tCO2e, respectively. There are three obvious peak emission periods on the weekday, namely, the morning peak (8:00–9:00), the noon peak (11:00–12:00) and the evening peak (18:00–19:00), which contribute 11.76%, 11.84% and 12.92% of the daily emission, respectively. The 1 h × 1 h emission grid shows the spatial distribution characteristics of emissions. The areas within the Fifth Ring Road (973 km2) are only 5.93% of the total area of the city (16,410 km2) but contribute 41.53% of the total vehicle GHG emissions. This study provides detailed data support for implementing vehicle GHG emission mitigation measures.

Probabilistic speed–flow models in highway construction work zones

Since variations in exogenous factors could cause unpredictable fluctuations/variability of the speed–flow relationship, the aim of this study was to develop probabilistic speed–flow relationships in a work zone (i.e. a segment of road in which maintenance or construction operations affect the operational characteristics of traffic flow). With observed traffic data from six highway work zones in Shanghai, China, lognormally distributed speed–flow functions were established to formulise probabilistic speed–flow relationships under uncongested and congested traffic conditions. A work zone capacity distribution model was then derived based on these probabilistic speed–flow relationships. The modelling results showed that work zone length, percentage of heavy vehicles and road roughness had strong effects on the probabilistic speed–flow relationships in work zones. A smaller mean work zone capacity was strongly associated with a long work zone length, a large proportion of heavy vehicles and poor road conditions. The models developed in this study could help traffic engineers evaluate the variability of work zone traffic states and the reliability of traffic management strategies.

Review of methods for assessing traffic conditions on basic motorway and expressway sections

Motorways and expressways are the core of each country’s road system. Road planning, design and management requires tools to ensure that roads have the right geometry, traffic layout and equipment. These include methods for capacity estimation and assessing traffic conditions. Because the paper focusses on the basic segments of motorways and expressways (sections located between interchanges and outside of their influence), its objective is to review and compare methods used worldwide and establish whether their assumptions or procedures could be used in Polish conditions. Four methods were selected for analysis: US, German, Swedish and Dutch. Theoretical and empirical comparisons were conducted, with the latter using data from sections of motorways and expressways in Poland collected in the RID-2B project. The results of the analyses showed important differences between the methods in terms of procedures for traffic conditions assessment, assumptions, base capacities, traffic conditions measures, factors or speed-flow models. Significant differences were also found when traffic parameter estimates made with particular methods were compared to real data from Polish roads. The results contributed to the development of Poland’s new method, to be prepared as a result of the RID-2B project. It was concluded that none of the analysed methods can be directly adopted to Polish conditions. An important conclusion is the need to include Poland-specific motorway speed limits and procedure for determining free-flow speed, the basis for further analyses.

Research on road traffic flow status based on survival analysis

: Based on the data of bayonet and floating car, this paper studies the traffic flow state of the main roads in Shenzhen, analyses the relationship between speed and flow, and establishes a speed-flow model. It studies the characteristics of traffic flow in Shenzhen and the overall distribution of congestion duration. The results demonstrate that there is a strong correlation between flow and speed, which have obvious characteristics of morning and evening peak within a day, and the flow and speed show significant differences between work days and non-work days. As for the congestion duration of each road, they are generally under 16 minutes. Specifically, when the congestion duration is less than 8 minutes, there is a high probability that the congestion state ends; while the congestion lasts more than 10 minutes, the congestion status is less likely to end in a short time. In view of the above analysis, it is recommended that relevant departments strengthen monitoring and control of real-time road traffic so that the traffic environment in Shenzhen can be improved.

Merging Vehicles and Lane Speed-Flow Relationship in a Work Zone

In addition to closed merge lanes as physical bottlenecks of work zones, traffic oscillations caused by merging vehicles at multiple locations could reduce work-zone capacity. This study took a step-wise procedure to reveal spatial distributions of merging vehicles along work zones and their influence on speed-flow relationships of lane traffic flows. Field data showed that inserting vehicles from merge lanes could spread their influence over adjacent unclosed through lanes. Moreover, with increases in total volume, merging vehicles could choose their inserting positions further upstream of the work zone, which could induce oscillations near the insertion point. At the identified upstream bottlenecks, capacity drop was found in speed-flow diagrams of through-lane traffic, but it was not found in the diagrams of merge-lane traffic flows. Lack of sufficient demand and special merging behaviors on merge lanes could be attributed to the distinct speed-flow relationship. Two-part piecewise regression models were developed to fit the speed-flow relationships of uncongested and congested flows of through lanes. By comparing the estimated speed-flow models, it was found that when a queue is forming, the extent of the capacity drop and speed reduction is different for through lanes. Queue discharge uses different lengths of time on through lanes and multiple merging locations.

Speed-Flow Relationship at Basic Segment of Federal Highway

Theoretically, at many traffic facility during peak hour, speedflow relationship is only appeared as a normal flow, represented by half of speed-flow curve. Forced flow will only occur during severe overcrowding resulted in drivers trying to use all the space in a way so that the amount of overcapacity. The purpose of this study is to analyse the relationship between speed-flow traffic flows along a basic segment. The objectives of this study is to analyse the time series of speed and flow at basic segment of A550 and A551 study location for 24 hours in a month as well as to determine the maximum flow and critical speed through the speed-flow models. Data obtained from this study were analysed using video recording and image processing techniques. In order to achieve these objectives, the Federal Highway 2 was selected as location for the study. Results show that the speed – flow diagram in one month on both A550 and A551 obtain the maximum flows and critical speeds of 4200 and 5320 veh/hr/ln and 55 and 60 km/hr, respectively.

Avaliação de medidas de desempenho para rodovias de pista simples obtidas a partir de relações fluxo-velocidade

Para estimar o nível de serviço em rodovias de pista simples, o Highway Capacity Manual 2010 (HCM2010) adota como medidas de desempenho a porcentagem de tempo viajando em pelotões (PTSF) e a velocidade média de percurso (ATS). A PTSF, no entanto, é praticamente impossível de ser observada em campo. Na literatura, algumas pesquisas propõem medidas de desempenho alternativas à PTSF que podem ser coletadas diretamente da observação do tráfego. Além disso, as relações fluxo-velocidade têm um papel fundamental na determinação do nível de serviço no HCM2010 e no HBS2001. A meta deste trabalho foi avaliar medidas de desempenho provenientes de relações fluxo-velocidade que pudessem ser adequa-das para descrever a qualidade de serviço em rodovias de pista simples no Brasil. Usando dados de tráfego sintéticos produ-zidos com uma versão do CORSIM calibrada para rodovias no Brasil, foram obtidas relações fluxo-velocidade para diferentes condições (geometria, porcentagens de veículos pesados e velocidades de fluxo livre). Comparações dos valores provenientes desses modelos com dados de campo indicaram que a velocidade média de percurso dos automóveis e a densidade para automóveis poderiam substituir os critérios atuais do HCM para estimar o nível de serviço em rodovias de pista simples no Brasil.

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.

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

Oversaturated speed, flow, and density relationships are of key importance to studies of freeway operations. The Highway Capacity Manual (HCM) oversaturated model, which is defined by a linear transition from the flow and the density at capacity to a zero flow at jam density in the flow–density space, provides a reasonable representation of this relationship but does not provide an unbiased representation for all freeway facilities with different road conditions or driver behavior. This study proposes a method for fitting the HCM model to oversaturated flow and density. Fifteen-minute aggregated flow rate and speed data were collected in 2010 from Traffic.com fixed-location sensors at three sites on North Carolina urban freeways. Density was calculated as the flow rate divided by the speed. The fitted models for these sites were compared with the default HCM model. A set of thresholds was defined to identify eligible sensor observations that represented the steady-state congested traffic conditions. The results revealed that data observations during inclement weather, lane closures, or incidents biased the model-fitting results and therefore needed to be filtered out. The steady-state congestion data identified in the manner proposed in this study fit well with the HCM-based linear flow–density oversaturated model. This method avoids possible bias caused by capacity and jam density differences between the default HCM model and the site-specific models; therefore, the fitted models represented the actual traffic characteristics relationships better than the default HCM models did. Fitting a site-specific HCM-based model is recommended for sites with sufficient speed and flow data.

Modeling speed-flow relationship and merging behavior in work zone merging areas

This paper aims to investigate the speed-flow relationship and drivers’ merging behavior in work zone merging areas. It first proposes lane-based speed-flow models, incorporating traffic conflicts among the lanes. It proceeds to develop a desired merging location model determining where drivers start to consider merging and a binary logit model that is applied to estimate the probabilities that drivers will merge into current adjacent gaps. A merging distance model is also proposed to find the 85th percentile of the merging distance. Finally, real work zone traffic data in Singapore are used to calibrate and evaluate the developed models. The findings show that the speed-flow relationship in the through lane is affected by the merge lane traffic under uncongested circumstances. Satisfactory results indicate that the merging behavioral models can competently predict drivers’ merging behavior and that the merging distance model could provide accurate information for traffic engineers to calculate the merge lane length.

Establishing speed–flow–density relationships for exclusive motorcycle lanes

The motorcycle is a popular mode of transport in Malaysia and developing Asian countries, but its significant representation in the traffic mix results in high rates of motorcycle accidents. As a result, the Malaysian Government decided to segregate motorcycle traffic along its new federal roads as an engineering approach to reduce accidents. However, traffic engineers needed to know the maximum traffic a motorcycle lane could accommodate. Despite substantial literature related to speed–flow–density relationships and capacities of various transport facilities, there is a knowledge gap regarding motorcycle lanes. This paper establishes motorcycle speed–flow–density relationships and capacities of exclusive motorcycle lanes in Malaysia. Observations of motorcycle flows and speeds were conducted along existing and experimental motorcycle lanes. Motorcycle speed–density data were aggregated and plotted for two types of observable motorcycle riding behaviour patterns that were influenced by the widths of a motorcycle lane: the headway pattern (lane width ≤ 1.7 m) and the space pattern (lane width > 1.7 m). For both riding patterns, regression analysis of motorcycle speed–density data best fits the logarithmic model and consequently the motorcycle flow–density and speed–flow models are derived. Motorcycle lane capacities for headway and space riding patterns are estimated as 3300 mc/hr/lane and 2200 mc/hr/m, respectively.

Speed-flow Models for Freeways

The new HCM 2010 proposes in chapter 11 two-stage curves to represent the speed-flow diagram for non-congested flow on freeways where constant speeds are postulated over a rather wide range of volumes. This division of the traffic flow in two parts plus the congested conditions is a rather pragmatic approach. Further the three steps pretend three separate traffic flow regimes, which don’t exist. A continuous function, like it is used in the other guidelines, would replicate the traffic conditions comprehensibly and realistically. Therefore, a model based on simple queueing theory analogy is presented to represent the noncongested part of traffic flow. Moreover several models which represent each state of traffic flow by one function are discussed. These different approaches are compared to real world data from the US and Germany. Based on this analysis a new single-stage model for the approximation of fundamental diagrams for freeways is recommended. The model can also be modified in order to represent the capacity drop effect.

EMİNÖNÜ İÇİN BİR TRAFİK TIKANIKLIK FİYATLANDIRMASI MODELİ

A Traffic Congestion Pricing Model for Eminonu District An investigation on applicability of a congestion pricing scheme to the Eminonu District, which is subject to heavy traffic problems in the Historical Peninsula of Istanbul, has been conducted. The area borders are set; field studies are performed to determine speed-flow characteristics of the roads and the demand function for automobile users. Akcelik and MTC speed-flow models are found suitable to represent the area’s traffic. A computer program is developed to assess the optimum toll under many different conditions with higher sensitivity. As a result, optimum congestion toll rates for different scenarios are calculated and it is concluded that the congestion pricing application would have a

Pedestrian and Vehicle Flow Calibration in Multimodal Traffic Microsimulation

This paper provides a method for including pedestrians in a vehicle microsimulation model, specifically the VISSIM model. VISSIM provides a default mechanism for simulating pedestrian movements; however, this does not adequately replicate pedestrian behavior. We instead define pedestrians as vehicles and calibrate various parameters within VISSIM so that pedestrian behavior is calibrated with pedestrian speed-flow models. We validate and refine these parameters using a real traffic network with high levels of pedestrian traffic crossing at signalized junctions. This work demonstrates the feasibility of modeling vehicle-pedestrian interactions in a realistic manner and provides analysts with a tool for evaluating policies that affect both vehicle and pedestrian flows.

Influence of Various Restrictions on Speed–Flow Models

This paper presents traffic speed models developed on the basis of numerous measurements. In studies of the speed–flow relationships the following research issues were analyzed: impacts of the speed limit, traffic flow, traffic flow composition, and time of day on speed–flow and impacts of qualitative road and roadside features (cross sections, road function, accessibility, intensity of development, roadside pedestrian traffic) on free-flow speed. The research included road sections with numerous constraints of traffic freedom. Such sections include sections of roads through built-up areas (small communities and towns). Regression analysis using generalized multiple regression was the basic tool in investigations. In addition, in analyzing data from speed measurements, the classic form of the logit function for a multiple-valued regression was applied. The analyses showed that even at general and posted speed limits the characteristic traffic flow–speed relations can be identified. The shape of these relations is characteristic of empirical results in which the spread of recorded values is typical for randomness and impacts of local factors. Average speed in traffic flow depends not only on geometric alignment of a road cross section but also on local factors and speed limits. Speed in free-flow traffic is significantly influenced by qualitative road and roadside characteristics. Most important of these factors are type of cross section, intensity of roadside development, and accessibility of the road.