Travel Time Distribution Research Articles

A generalized trajectories-based evaluation approach for pedestrian evacuation models

The fundamental diagram and self-organized phenomena in crowds are widely used to test the applicability of evacuation models. These benchmarks are good indicators for the validity of a model, whereas they are insufficient descriptors for the realistic microscopic behaviors of pedestrians. In recent years, the rapid increase of the trajectory datasets which benefits from the development of recognition technologies open the door to new possibilities for an extensive quantitative validation of the models. In this work, a trajectories-based analysis approach which contains types of indexes is proposed. The indexes are a mix of macroscopic type (fundamental diagram index, speed choice index, and direction choice index) and microscopic type (trajectories pattern index), distribution type (route length distribution index, travel time distribution index) and time-series type (starting position distance time-series index, destination position distance time-series index. Moreover, the Kolmogorov-Smirnov (K-S) test as well as the dynamic time warping (DTW) method are introduced to quantify the similarities of results on different types of indexes. In brief, by comparing experimental and simulation trajectories, we can measure a set of performance scores in different perspectives. Here, the Social Force Model (SFM) and Heuristics Model (HM) are respectively introduced and evaluated. According to the proposed evaluation approach, we show that the HM performs better than the SFM. Our analysis approach is model agnostic and is defined in a general way, such that it can be applied for trajectory sets from different experiment settings. This work can help to improve the accuracy of simulation models, and the pedestrian safety in crowd activities and autonomous vehicle navigation will be benefited.

Spatio-temporal mobility patterns of on-demand ride-hailing service users

ABSTRACT Understanding individual mobility behavior is critical for modeling urban transportation. Different types of emerging data sources such as mobile phone records, social media posts, GPS observations, and smart card transactions have been used to reveal individual mobility behavior. In this paper, spatio-temporal mobility behaviors are reported using large-scale data collected from a ride-hailing service platform. Using passenger-level travel information, to characterize temporal movement patterns, trip generation characteristics, and distribution of gap time between consecutive trips are revealed. To understand spatial mobility patterns, we observe the spatial distribution of residences and workplaces, and the distributions of travel distance and travel time. Our analysis highlights the differences in mobility patterns of ride-hailing services users, compared to the findings of existing studies based on other data sources. The results show the potential of developing high-resolution individual-level mobility models that can predict the demand for emerging mobility services with high fidelity and accuracy.

Impact of shear displacement on advective transport in a laboratory-scale fracture

The impact of shear displacement under different mechanical boundary conditions on fluid flow and advective transport in a single fracture at the laboratory scale is demonstrated in the present study. The shear-induced changes of fracture aperture structures are determined by using the measured normal displacements and digitalized fracture surfaces from laboratory shear tests. Five shear tests on concrete replicas of the same fracture under different mechanical boundary conditions, including constant normal loading (CNL) and constant normal stiffness (CNS), are conducted to analyse the influence of mechanical boundary conditions on the shear-flow-transport processes. Fluid flow in the fracture with different shear displacements are simulated by solving the Reynolds equation. The Lagrangian particle tracking method is applied to model the advective transport in the fracture after shearing. The results generally show that the shear displacements and the normal loading conditions can significantly affect flow patterns and advective travel time distributions in the fracture. For mated fractures, the flow and transport will be enhanced by the increasing shear displacement because of shear dilation. For cases with the same shear displacement, the median advective travel time increases with the increasing boundary normal stiffness. The median advective travel time under the CNS boundary condition is generally longer than that under the CNL boundary condition. The results from this study can help to improve our understanding of stress-dependent solute transport processes in natural rock fractures.

Multiobjective Risk-Aware Path Planning in Uncertain Transient Currents: An Ensemble-Based Stochastic Optimization Approach

A multiobjective, risk-aware framework is developed for optimal path planning of autonomous underwater vehicles operating in uncertain current. The uncertainty in the current is described in terms of a finite ensemble of flow realizations. A new optimization framework is proposed that accounts for the full variability of the ensemble in a single optimization problem whose solution may not necessarily coincide with any of the optimal deterministic paths corresponding to individual ensemble members. We formulate stochastic problemsthat aim to minimize a risk measure of the travel time or energy consumption, using a flexible methodology that enables the user to seamlessly explore various objectives, ranging from risk neutral to risk averse. We illustrate the application of the proposed approach using two case studies based on synthetic 2-D settings, and one case involving a real-world problem in the Gulf of Aden. The results are analyzed to assess the value of stochastic solution, guide the selection of suitable risk measures, and demonstrate the impact of the risk measures on the resulting path and on the distribution of travel times.

GP4: Gaussian Process Proactive Path Planning for the Stochastic on Time Arrival Problem

This paper investigates the stochastic on time arrival (SOTA) problem in Gaussian process (GP) regulated environments. We presume that the travel times of the underlying transportation network follow a multi-variate Gaussian distribution, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</i> . <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e</i> . Gaussian process, and propose a Gaussian process <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">proactive</i> path planner (GP4), which outputs a dynamic routing policy for maximizing the traveller's on-time-arrival probability. When given an instantiated travel time of a certain link, GP is able to analytically represent/predict the posterior travel time distribution over the entire transportation network. With that, we let the ego vehicle ‘proactively’ select the next traversal link, which maximizes the expected stochastic on time arrival probability based on the predicted posterior travel time distribution. Various extensions of GP4 to other forms of travel time distribution assumptions, such as Log-GP and Bi-GP, are proposed and extensive experimental results demonstrate the efficiency and applicability of GP4 to various transportation networks, including a real use case with real traffic data in Chengdu, China.

Water‐Mineral Reactions in a Translated Single Realistic Fracture: Consequences for Contaminant Uptake by Matrix Diffusion

AbstractWe use a realistic fracture along with pore‐scale reactive transport simulations to investigate the impact of fracture filling minerals and water‐mineral reactions on in‐plane groundwater flow patterns and on contaminant uptake by matrix diffusion. The results of the simulations show that sparsely distributed fracture filling calcite patches provide a significant buffering capacity against the infiltration of acidic water. The advance of the geochemical perturbation is characterized by channeling, which is partly smeared out when low Peclet numbers are used. Mineral patches have a significant impact on groundwater flow patterns as shown by the computed distributions of groundwater travel time, which are characterized by long tails. The ability of the fracture to retain contaminants by uptake due to matrix diffusion is investigated by means of two metrics: the Eulerian quantity denoted as F‐factor and the Lagrangian variable known as transport resistance. F‐factor is shown to provide an average single estimate of the bulk retention capacity of the fracture whereas transport resistance is characterized by a distribution, whose very long tail is related to streamlines forced to travel through very narrow throats. A reduction of up to 70% in the mean travel time and 85% in the mean transport resistance is observed as a consequence of geochemical dissolution reactions, which also lead to an overall reduction of their variability.

Matrix Diffusion as a Mechanism Contributing to Fractal Stream Chemistry and Long‐Tailed Transit Time Distributions

AbstractSolute transit or travel time distributions (TTDs) in catchments are relevant to both hydrochemical response and inference of hydrologic mechanisms. Long‐tailed TTDs and fractal scaling behavior of stream concentration power spectra (∼1/frequency, or 1/frequency to a power &lt;2) are widely observed in catchment studies. In several catchments, a significant fraction of streamflow is derived from groundwater in shallow fractured bedrock, where matrix diffusion significantly influences solute transport. I present frequency and time domain theoretical analyses of solute transport to quantify the influence of matrix diffusion on fractal scaling and long‐tailed TTDs. The theoretical concentration power spectra exhibit fractal scaling, and the corresponding TTDs resemble a gamma distribution. The tails of the TTDs are influenced by accessible matrix width, exhibiting a sustained power‐law (rather than exponential) decline for large matrix widths. Application to an experimental catchment shows that theoretical spectra match previously reported power spectral estimates derived from concentration measurements.

Reduction of vegetation-accessible water storage capacity after deforestation affects catchment travel time distributions and increases young water fractions in a headwater catchment

Abstract. Deforestation can considerably affect transpiration dynamics and magnitudes at the catchment scale and thereby alter the partitioning between drainage and evaporative water fluxes released from terrestrial hydrological systems. However, it has so far remained problematic to directly link reductions in transpiration to changes in the physical properties of the system and to quantify these changes in system properties at the catchment scale. As a consequence, it is difficult to quantify the effect of deforestation on parameters of catchment-scale hydrological models. This in turn leads to substantial uncertainties in predictions of the hydrological response after deforestation but also to a poor understanding of how deforestation affects principal descriptors of catchment-scale transport, such as travel time distributions and young water fractions. The objectives of this study in the Wüstebach experimental catchment are therefore to provide a mechanistic explanation of why changes in the partitioning of water fluxes can be observed after deforestation and how this further affects the storage and release dynamics of water. More specifically, we test the hypotheses that (1) post-deforestation changes in water storage dynamics and partitioning of water fluxes are largely a direct consequence of a reduction of the catchment-scale effective vegetation-accessible water storage capacity in the unsaturated root zone (SU, max) after deforestation and that (2) the deforestation-induced reduction of SU, max affects the shape of travel time distributions and results in shifts towards higher fractions of young water in the stream. Simultaneously modelling streamflow and stable water isotope dynamics using meaningfully adjusted model parameters both for the pre- and post-deforestation periods, respectively, a hydrological model with an integrated tracer routine based on the concept of storage-age selection functions is used to track fluxes through the system and to estimate the effects of deforestation on catchment travel time distributions and young water fractions Fyw. It was found that deforestation led to a significant increase in streamflow accompanied by corresponding reductions of evaporative fluxes. This is reflected by an increase in the runoff ratio from CR=0.55 to 0.68 in the post-deforestation period despite similar climatic conditions. This reduction of evaporative fluxes could be linked to a reduction of the catchment-scale water storage volume in the unsaturated soil (SU, max) that is within the reach of active roots and thus accessible for vegetation transpiration from ∼258 mm in the pre-deforestation period to ∼101 mm in the post-deforestation period. The hydrological model, reflecting the changes in the parameter SU, max, indicated that in the post-deforestation period stream water was characterized by slightly yet statistically not significantly higher mean fractions of young water (Fyw∼0.13) than in the pre-deforestation period (Fyw∼0.12). In spite of these limited effects on the overall Fyw, changes were found for wet periods, during which post-deforestation fractions of young water increased to values Fyw∼0.37 for individual storms. Deforestation also caused a significantly increased sensitivity of young water fractions to discharge under wet conditions from dFyw/dQ=0.25 to 0.36. Overall, this study provides quantitative evidence that deforestation resulted in changes in vegetation-accessible storage volumes SU, max and that these changes are not only responsible for changes in the partitioning between drainage and evaporation and thus the fundamental hydrological response characteristics of the Wüstebach catchment, but also for changes in catchment-scale tracer circulation dynamics. In particular for wet conditions, deforestation caused higher proportions of younger water to reach the stream, implying faster routing of stable isotopes and plausibly also solutes through the sub-surface.

Функциональная структура комплекса систем управления движением поездов метрополитена

The main architectural aspects of metro train traffic control systems are presented. The structure of train traffic control processes is presented with the example of the State Unitary Enterprise “Moscow Metro” and the main tasks that need to be solved to achieve high levels of automation of train traffic control in subways are described. A functional structure of a complex of metro train traffic control systems is presented, covering the levels of organization and planning of train traffic, operational traffic control and direct executive systems. The relationship between objects of automation and remote control of train movement, devices of the operational level and systems of organization and planning of movement are shown. The necessity of re-equipping the metro with means of ensuring transport safety and linking them with traffic control systems such as: means of informing passengers, providing the possibility of promptly informing passengers both during normal operation of the transport system and in case of emergency situations, means of communication “passenger – control center (situation center)” is shown. The latter ensures interaction between passengers and operational personnel of the subway, and if necessary, video surveillance equipment that provides enhanced remote control of the current situation in the interior of rolling stock cars and on platforms. The use of complex systems for controlling the movement of trains in subways increases the efficiency of their use by increasing the throughput and carrying capacity, accurate fulfillment of the traffic schedule and the possibility of its rapid recovery in case of failures. At the same time, traffic safety increases by reducing the likelihood of dangerous train convergence , and also the energy consumption for train traction is reduced due to the choice of energy-optimal train control modes and the optimal distribution of travel time along the line by the criterion of minimum energy consumption for the duration of travel along the tracks

Calculating conditional passenger travel time distributions in mixed schedule- and frequency-based public transport networks using Markov chains

Calculation of passenger travel time distributions in public transport networks is important for the evaluation of the level of service provided to passengers. Passenger travel times are deterministic for punctual and uncongested networks, but in reality usually have random fluctuations caused by vehicle delays and other incidents. Advanced methods are therefore needed to calculate the passenger travel time distribution between a given origin and destination. This paper presents a novel approach for calculating the travel time distribution from origin to destination based on vehicle delays and possible missed connections in a mixed schedule- and frequency-based public transport network. Markov chains are used to model the network, making the travel time from the origin to the destination phase-type distributed. The approach is flexible with regard to the specification of vehicle travel times and provides the distribution of passenger travel times without any need for simulation. Additionally, it facilitates detailed analyses of passenger travel times conditional on the usage of specific line segments or stops. The merits of this approach are demonstrated using a case study from Copenhagen.

Validating and Calibrating the Highway Capacity Manual Arterial Travel Time Reliability Methodology

The 6th edition of the Highway Capacity Manual (HCM6) introduced a methodology for estimating and forecasting arterial travel time (TT) distributions (TTD) and their associated travel time reliability (TTR) metrics. Recently, it was shown that the HCM6 severely underestimated both the TTD and the TTR metrics for a test network in Lincoln, NE, U.S. Subsequently, it was shown that the underestimation issue could be eliminated through a proposed calibration methodology. Because this validation and calibration work was done on a single, relatively short section of arterial roadway there is an open research question on whether this finding applies to longer and more congested arterial roadways. The goal of this paper is to validate and calibrate the HCM6 TTR methodology on five arterial roadway testbeds that are longer and more congested than the original testbed. Empirical data from the National Performance Management Research Data Set (NPMRDS) which is managed by INRIX was used to represent the ground truth. Similar to the original study, it was found that the HCM6 TTR methodology severely underestimated the TTDs, and their respective TTR metrics, on all five testbeds. This is problematic, because the HCM6 methodology indicates that the corridors had more reliable TT than the empirical data would suggest. It was also shown that the calibration methodology eliminated this underestimation. It is recommended that users of the HCM6 TTR methodology validate and, if necessary, calibrate the model using local empirical travel data.

Statistical Distance-Based Travel-Time Reliability Measurement for Freeway Bottleneck Identification and Ranking

Freeway bottleneck identification is an essential component in the process of deploying mitigation strategies to reduce congestion at freeway bottlenecks. Most previous studies on bottleneck identification focus on recurrent bottlenecks, and limited work has been conducted to identify the locations of non-recurrent bottlenecks. Therefore, in this study, we propose a new travel time reliability (TTR) measurement and develop a freeway bottleneck identification method based on this measurement, which can identify with high probability not only recurrent bottlenecks but also the locations of non-recurrent bottlenecks. The TTR measurement is developed based on statistical distance between travel time distributions. Three statistical distance measurements, Jensen–Shannon divergence, Wasserstein distance, and Hellinger distance, are applied in the TTR measurement. The bottleneck identification method is evaluated in a case study on I-15 freeway corridor in Salt Lake City, Utah. The three statistical distance measurements show good consistency in ranking locations by the impacts of recurrent and non-recurrent congestion, especially for extreme cases with very high or low variation between travel time distributions. The recurrent bottlenecks identified in this study show their clustering characteristics, which is similar to the generating and dismissing process of recurrent congestion. The locations with high probability of non-recurrent bottlenecks scatter both spatially and temporally, which agrees with the random characteristic of non-recurrent congestion.

Incorporating Travel Time Reliability in Equitable Congestion Pricing Schemes for Heterogeneous Users and Bimodal Networks

Congestion pricing is proposed as an effective travel demand management strategy to circumvent the problem of congestion and generate revenue to finance developmental projects. There are several studies focusing on optimal pricing strategies to minimize the congestion level or maximize the revenue of the system. However, with regard to equity issues, benefiting only users with higher value of time is claimed to be the main factor that prevents implementation of such policies in practice. While many studies aimed to tackle the equity issues by certain welfare analyses, most of these studies fail to fully consider realistic features of users’ behavior and the uncertainty in link travel times. Given the variability of travel time in real-world networks and the impacts of pricing policies on path travel time distributions, it is important to consider the users’ reliability valuations, in addition to their travel time valuations. Thus, the goal in this study is to find an equitable pricing scheme that minimizes the total travel time of auto users in a general bimodal network considering heterogeneous users with different values of time and reliability. A particle swarm optimization algorithm is proposed to find self-funded and Pareto-improving optimal toll values. A reliability-based user equilibrium algorithm is embedded into this optimization algorithm to assign travelers to the equilibrated paths for different user classes given toll values. The proposed approach is successfully applied to a modified Sioux Falls network to explore impacts of subsidization, congestion level, and considering travel time reliability on the pricing strategy and its effectiveness.

Estimation of Path Travel Time Distributions in Stochastic Time-Varying Networks with Correlations

Transportation research has increasingly focused on the modeling of travel time uncertainty in transportation networks. From a user’s perspective, the performance of the network is experienced at the level of a path, and, as such, knowledge of variability of travel times along paths contemplated by the user is necessary. This paper focuses on developing approaches for the estimation of path travel time distributions in stochastic time-varying networks so as to capture generalized correlations between link travel times. Specifically, the goal is to develop methods to estimate path travel time distributions for any path in the networks by synthesizing available trajectory data from various portions of the path, and this paper addresses that problem in a two-fold manner. Firstly, a Monte Carlo simulation (MCS)-based approach is presented for the convolution of time-varying random variables with general correlation structures and distribution shapes. Secondly, a combinatorial data-mining approach is developed, which aims to utilize sparse trajectory data for the estimation of path travel time distributions by implicitly capturing the complex correlation structure in the network travel times. Numerical results indicate that the MCS approach allowing for time-dependence and a time-varying correlation structure outperforms other approaches, and that its performance is robust with respect to different path travel time distributions. Additionally, using the path segmentations from the segment search approach with a MCS approach with time-dependence also produces accurate and robust estimates of the path travel time distributions with the added benefit of shorter computation times.

Transport Upscaling under Flow Heterogeneity and Matrix-Diffusion in Three-Dimensional Discrete Fracture Networks

We investigate the combined effects of network scale flow variability and retention due to matrix-diffusion on the scaling behavior of transport through fractured media. Two of the principal mechanisms controlling the transport of solutes through fractured low-permeability media are broad distributions of flow velocities and retention times in the solid matrix. We study the relative impact of these two processes under different initial conditions using a set of three-dimensional discrete fracture network simulations. We use these simulations to develop and calibrate an upscaled continuous time random walk (CTRW) approach for advective transport based on an Ornstein-Uhlenbeck model for the particle velocities that accounts for the fracture-matrix coupling using a compound Poisson process. This CTRW model can be conditioned on the initial solute distribution and allows to observe late-time scaling behavior at distances beyond what is feasible to observe using high-fidelity direct numerical simulations. We determine that the initial distribution of particles leads to marked differences in the persistent long-term scale behavior in the solute travel time distributions, even those undergoing retention due to matrix diffusion through implementation and analysis of the model.

Arterial Roadway Travel Time Reliability and the COVID-19 Pandemic

This paper evaluated the effect of the COVID-19 preventive orders on arterial roadway travel time reliability (TTR). A comparative analysis was conducted to examine average travel time distributions (TTD), and their associated TTR metrics, before and during the COVID-19 pandemic. Travel time data for four urban arterial corridors in Nebraska, disaggregated by peak period and direction, were analyzed. It was found that in 2020, the average TTD mean and standard deviation values for all 16 scenarios were reduced by an average of 14.0% and 43.4%, respectively. The travel time index, the planning time index, the level of travel time reliability (LOTTR), and the buffer index metrics associated with these TTDs were reduced, on average, by 14.0%, 19.7%, 3.5%, and 35.0%, respectively. In other words, whether the test corridors were more reliable during the pandemic was a function of which TTR metric was used. The paper concludes by arguing for a fundamental change in how arterial TTR is measured and reported to different user groups.

Paleoclimate Signals and Groundwater Age Distributions From 39 Public Water Works in the Netherlands; Insights From Noble Gases and Carbon, Hydrogen and Oxygen Isotope Tracers

AbstractKnowing the age distribution of water abstracted from public water supply wells helps to ensure customer trust in drinking water sources and underpin predictions of water quality evolution. We sampled the mixed water of 39 large public supply well fields for major ion chemistry, 3H, 3He, 18O, 2H, 14CDIC, 13CDIC and noble gases and determined the Noble Gas Temperature (NGT). We used a discrete travel time distribution model to quantify the age distributions using 3H, 4He, 14C apparent age and NGT as the 4 distinctive tracers. Helium‐4 and NGT provided information on the older part of the age distributions and showed that the 14C apparent ages are often the result of mixing of waters ranging between 2,000 and 35,000 years old, instead of being discrete ages with a limited variance as previously assumed. The results reveal a large range of age distributions, comprising vulnerable well fields with &gt;60% young water (&lt;100 years) and well fields with &gt;30% paleo groundwater (&gt;25,000 years) and all forms of intermediate distributions. The age distributions match the hydrogeological setting; well fields with age distributions skewed towards older ages appear in the Roer Valley Graben structure, where fluvial and marine aquitards and sealed faults provide protection from recent recharge. Waters from this graben exhibit paleoclimate signals, with a clear relation between NGT (range 3.2–9.3 °C), 4He (up to 3.3 × 10−6 ccSTP/g) and δ18O (range −8.5‰ to −5.9‰VSMOW). Moreover, 3He/4He ratios of these graben waters suggest a certain influx of He from mantle origin.

Time lags of nitrate, chloride, and tritium in streams assessed by dynamic groundwater flow tracking in a lowland landscape

Abstract. Surface waters are under pressure from diffuse pollution from agricultural activities, and groundwater is known to be a connection between the agricultural fields and streams. This paper is one of the first to calculate long-term in-stream concentrations of tritium, chloride, and nitrate using dynamic groundwater travel time distributions (TTDs) derived from a distributed, transient, 3D groundwater flow model using forward particle tracking. We tested our approach in the Springendalse Beek catchment, a lowland stream in the east of the Netherlands, for which we collected a long time series of chloride and nitrate concentrations (1969–2018). The Netherlands experienced a sharp decrease in concentrations of solutes leaching to groundwater in the 1980s due to legislations on the application of nitrogen to agricultural fields. Stream measurements of chloride and nitrate showed that the corresponding trend reversal in the groundwater-fed stream occurred after a time lag of 5–10 years. By combining calculated TTDs with the known history of nitrogen and chloride inputs, we found that the variable contribution of different groundwater flow paths to stream water quality reasonably explained the majority of long-term and seasonal variation in the measured stream nitrate concentrations. However, combining only TTDs and inputs underestimated the time lag between the peak in nitrogen input and the following trend reversal of nitrate in the stream. This feature was further investigated through an exploration of the model behaviour under different scenarios. A time lag of several years, and up to decades, can occur due to (1) a thick unsaturated zone adding a certain travel time, (2) persistent organic matter with a slow release of N in the unsaturated zone, (3) a long mean travel time (MTT) compared to the rate of the reduction in nitrogen application, (4) areas with a high application of nitrogen (agricultural fields) being located further away from the stream or drainage network, or (5) a higher presence of nitrate attenuating processes close to the stream or drainage network compared to the rest of the catchment. By making the connection between dynamic groundwater travel time distributions and in-stream concentration measurements, we provide a method for validating the travel time approach and make the step towards application in water quality modelling and management.

A novel approach for vehicle travel time distribution: copula-based dependent discrete convolution

ABSTRACT Travel time reliability is considered as one of the key indicators for the performance of transportation systems. The majority of studies concerning estimating arterial travel time distribution commonly assume that the path travel time follows a certain distribution without considering segment correlation. Therefore, convolution is used. However, the assumption of independence of travel times on successive segments may not be appropriate. Recent studies showed that copulas are able to capture segment correlation. These copula models, however, are unfeasible in real-world applications. This paper proposes a novel approach using dependent discrete convolution. Path-level travel time distribution is estimated by aggregating segment-level travel time distributions using copula-based discrete convolution. This estimation is compared to the estimation of traditional convolution, a state-of-the art copula model, and the empirical distribution. It is shown that the proposed methodology produces accurate results within feasible computational time, thus, making it eligible for real-world applications.

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.