Traffic Modelling Software Research Articles

Analyzing the Impact of Road Accidents on Carbon Dioxide Emissions in Freeway Traffic: A Simulation and Statistical Modeling Approach

Roadway accidents significantly contribute to intermittent congestion and increased CO2 emissions on freeways. This research introduces a statistical approach designed to predict the rise in CO2 emissions resulting from traffic disturbances or jams triggered by such incidents. It also assesses the influence of varying levels of accident management effectiveness in different situations. To construct these scenarios, the study employs VISSIM, a traffic modeling software, incorporating diverse factors such as traffic volume, vehicle types, incident durations, and freeway lane counts. It then produces traffic flow characteristics in the form of vehicle paths. The emission estimates are derived by correlating these simulated vehicle paths with emission rates from the MOVES model. The study then applies a regression analysis to examine the connection between the increase in emissions and various influencing factors. The findings indicate that this approach efficiently reflects the impact of variables like accident duration, vehicle mix, and traffic volume on CO2 emissions across different lane configurations. The accuracy of these predictions is also confirmed. The outcomes suggest the model’s potential usage in guiding efforts to lower emissions and determining the optimal duration of incident management, particularly in terms of lane closure, to mitigate emission impacts. This paper also discusses the limitations of the model and the future improvement direction.

Decarbonising mobility in port cities

Ports play an important role in the European transport decarbonisation agenda. Due to the complex characteristics of ports, coordinated and holistic approaches between port authorities and municipalities are of utmost relevance to tackle greenhouse gas emissions reduction. This paper analyses the mobility challenges of a port city and associated carbon dioxide CO2 emissions. The specific objectives of this research are: firstly, to study the implementation of integrated mobility measures in ports to reduce the carbon footprint by promoting an efficient use of transport infrastructure and smart mobility strategies to/from/in the port; secondly, to define and implement electric mobility and digitalization solutions for transport in ports (including the connection between the city and the port). The traffic modelling software PTV VISSIM and the Vehicle Specific Power methodology were used to estimate the emissions of the vehicles present in the road network of a study area. The methodology was applied to the case study of Aveiro, Portugal, which has a port located 8 km from the city centre. The baseline scenario and three alternative scenarios: implementation of electric mobility; digitalization of work patterns through remote work; and mobility-as-a-service (MaaS) were defined. Results showed a reduction in pollutant emissions in all tested scenarios in comparison with the baseline scenario.

High Resolution Modelling of Traffic Emissions Using the Large Eddy Simulation Code Fluidity

The large eddy simulation (LES) code Fluidity was used to simulate the dispersion of NOx traffic emissions along a road in London. The traffic emissions were represented by moving volume sources, one for each vehicle, with time-varying emission rates. Traffic modelling software was used to generate the vehicle movement, while an instantaneous emissions model was used to calculate the NOx emissions at 1 s intervals. The traffic emissions were also modelled as a constant volume source along the length of the road for comparison. A validation of Fluidity against wind tunnel measurements is presented before a qualitative comparison of the LES concentrations with measured roadside concentrations. Fluidity showed an acceptable comparison with the wind tunnel data for velocities and turbulence intensities. The in-canyon tracer concentrations were found to be significantly different between the wind tunnel and Fluidity. This difference was explained by the very high sensitivity of the in-canyon tracer concentrations to the precise release location. Despite this, the comparison showed that Fluidity was able to provide a realistic representation of roadside concentration variations at high temporal resolution, which is not achieved when traffic emissions are modelled as a constant volume source or by Gaussian plume models.

Cycle length optimization through bi-level optimization

This paper describes the formalization of the store-and-forward model in bi-level optimization problem. The study finds the optimal duration of the cycle lengths by given green splits. The queues in front of traffic lights are minimized. Thus, the network allows higher throughput and less congestion with the resulting from this less pollution and better traffic indicators such as delay, density, speed, etc. The results for traffic indicators and pollution are obtained by Aimsun suit – a specialized traffic modelling software product. The optimization is performed by a MATLAB script based on an additional toolbox called YALMIP as well as with a state-of-the-art software product TRANSYT that is compatible with Aismun suit. Results show that it is reasonable to use the script for optimization of traffic as TRANSYT optimizes only green splits and offsets but works with the cycle value form Aimsun.

Deep Learning-Based Queue-Aware Eco-Approach and Departure System for Plug-In Hybrid Electric Buses at Signalized Intersections: A Simulation Study

<div class="section abstract"><div class="htmlview paragraph">Eco-Approach and Departure (EAD) has been considered as a promising eco-driving strategy for vehicles traveling in an urban environment, where information such as signal phase and timing (SPaT) and geometric intersection description is well utilized to guide vehicles passing through intersections in the most energy-efficient manner. Previous studies formulated the optimal trajectory planning problem as finding the shortest path on a graphical model. While this method is effective in terms of energy saving, its computation efficiency can be further enhanced by adopting machine learning techniques. In this paper, we propose an innovative deep learning-based queue-aware eco-approach and departure (DLQ-EAD) system for a plug-in hybrid electric bus (PHEB), which is able to provide an online optimal trajectory for the vehicle considering both the downstream traffic condition (i.e. traffic lights, queues) and the vehicle powertrain efficiency. Based on optimal solutions obtained from the graph-based trajectory planning algorithm (GTPA), a deep neural network (DNN) is developed to learn the optimal vehicle speed for the next time step given its current state. It is demonstrated that the trained DNN can provide energy-efficient trajectories with high computational efficiency and high flexibility adopting to dynamic changes in the surrounding environment. To address the impact of downstream traffic, a queue prediction model is further developed using data from radars and connected vehicles (CVs), as well as signal timing data from SPaT messages. A comprehensive simulation study in the microscopic traffic modeling software PTV VISSIM shows that the proposed DLQ-EAD can achieve 18.7%-24.0% energy efficiency improvements for a single PHEB on various traffic congestion levels. The proposed queue prediction model can be of practical significance even at low penetration rates of CVs. Specifically, additional energy savings of 2.0%-8.2% can be further achieved with 20% vehicles in the network.</div></div>

Safer Predictions

Where is it safest to design access points for highways and express lanes? James Allen reports on a unique traffic modeling software tool that has helped answer this question in Minnesota, and is even influencing policy across the USA

Impacts of connected vehicles in a complex, congested urban freeway setting using multi-resolution modeling methods

Determining the effect automated and connected vehicles could have on traffic flow would – ideally – require testing the vehicles themselves in a real-world environment. In the absence of large-scale, real-world testing, researchers used traffic modeling software to develop and test a vehicle mimicking the behaviors of several automated and connected vehicle (CV) applications in a congested and complex urban network. The algorithm behind the CV ran a suite of mobility-focused applications, inspired by cooperative adaptive cruise control (CACC), speed harmonization, and queue warning applications. The CV was first tested on a small sample network, consistent with approaches obtained from a review of the literature. The research team then sought to understand the potential effects of CV technology on congestion and mobility in a DTATexas context by modeling the traffic impacts of CVs at varying market penetrations on a twelve-mile section of I-35 in Austin, running from south of Riverside Dr. to Parmer Ln at 2035 population levels. Researchers used a multi-resolution modeling (MRM) methodology, which incorporates macroscopic, mesoscopic, and microscopic models.

Analysis of signalized intersection performance using IHCM 1997 method and PTV Vistro software

Brigjend Slamet Riyadi road is the main city road serving the traffic of Surakarta City. It is located in the Central Business District so that many vehicles pass through this road. The relatively high traffic volume in Brigjend Slamet Riyadi affects the signalized intersections performance along this road. This study analyses the performance of signalized intersections along the Brigjend Slamet Riyadi road by using the IHCM 1997 method and PTV Vistro software. The IHCM 1997 method is a traffic modelling method based on empirical Indonesian traffic conditions. PTV Vistro is traffic modelling software based on empirical United States America traffic conditions. Analysis of the signalized intersections performance results using both approaches is compared with the field data. Calibration and validation of models is carried out to see the similarity of traffic performance results between models with field data. In general, the IHCM 1997 method produces vehicle queue length closer to field data than the PTV Vistro software. The IHCM 1997 method tends to produce lower degree of saturation, vehicle delay and level of service than the PTV Vistro software.

Computing Programs for Determining Traffic Flows from Roundabouts

For modelling road traffic at the level of a road network it is necessary to specify the flows of all traffic currents at each intersection. These data can be obtained by direct measurements at the traffic light intersections, but in the case of a roundabout this is not possible directly and the literature as well as the traffic modelling software doesn’t offer ways to solve this issue. Two sets of formulas are proposed by which all traffic flows from the roundabouts with 3 or 4 arms are calculated based on the streams that can be measured. The objective of this paper is to develop computational programs to operate with these formulas. For each of the two sets of analytical relations, a computational program was developed in the Java operating language. The obtained results fully confirm the applicability of the calculation programs. The final stage for capitalizing these programs will be to make them web pages in HTML format, so that they can be accessed and used on the Internet. The achievements presented in this paper are an important step to provide a necessary tool for traffic modelling because these computational programs can be easily integrated into specialized software.

Scenario-based electric bus operation: A case study of Putrajaya, Malaysia

Abstract Globally, transportation sector has emerged as one of the major sources of air pollution. Correspondingly, green mobility (with electric bus) is gaining increasing attention as an essential step to mitigate emission concern. As such, a proper electric bus network design and fleet planning is important especially for bus operator to acquire an adequate number of electric bus, right on time, in order to operate electric bus system viably. Thus, this paper aims to examine the possibility to operate electric bus as a replacement for the conventional bus operation (with natural gas buses for the study area in Putrajaya, Malaysia). In order to determine a proper-designed electric bus operating system in terms of electric bus route, service frequency and quantity, the proposed methodology is developed with the aid of a traffic modeling software to cater various scenarios. Based on the existing (conventional) traffic and transit system in Putrajaya, the developed electric bus operating model is calibrated accordingly by considering various operational concerns including battery capacity and charging facility. The resultant findings revealed that the developed electric bus operating system in Putrajaya outperforms the conventional bus operation, not only in generating a higher profit margin for the bus operator, but also satisfying the passengers in a better manner (by carrying more passengers per unit of bus with a lower energy consumption).

Design and Evaluation of an Adaptive Traffic Signal Control System – A Case Study in Hefei, China

Abstract: As a part of developing an adaptive signal control system using VS-PLUS method for optimal network traffic control, a study was carried out along the Huangshan Road in Hefei, China, to evaluate this system. This paper described the study which included field survey about traffic performance; development of trip matrix using an improved Furness method; using the TRANSYT traffic modelling software to find the optimal fixed-time signal plan and VISSIM micro-simulation software to affirm and evaluate the TRANSYT model and to help assess the optimal signal plan; building adaptive frame signal plan and refining and evaluating the plan using VISSIM with VS-PLUS emulator. The results indicated that average delay per vehicle was reduced significantly with consequent improvement in network performance. Adaptive signal control plan was then designed for the VS-PLUS signal control system based on the optimal fixed-time signal plan. Through micro-simulation, it was shown that delay in the adaptive signal control was shortened noticeably than that in the fixed time control. This study has been the very first for this system. Further and more comprehensive studies are expected to follow to fully evaluate and appreciate this system. This study has filled some of the gaps in evaluating the performance of and provided a benchmark for such an adaptive traffic signal control system in a typical urban setting in cities in China. The study has also raised a number of questions in setting the optimal frame plan regarding driver behaviour, safety concerns and tradeoffs between shorter cycles and higher responsiveness to traffic variations.

Differential Evolution Algorithm Based Solution Approaches for Solving Transportation Network Design Problems

Differential Evolution algorithm has effectively been used to solve engineering optimization problems recently. The Differential Evolution algorithm, which uses similar principles with Genetic Algorithms, is more robust on obtaining optimal solution than many other heuristic algorithms with its simpler structure. In this study, Differential Evolution algorithm is applied to the transportation network design problems and its effectiveness on the solution is investigated. In this context, Differential Evolution based models are developed using bi-level programming approach for the solution of the transportation network design problem and determination of the on-street parking places in urban road networks. In these models, optimal investment and parking strategies are investigated on the upper level. On the lower level, deterministic traffic assignment problem, which represents drivers' responses, is solved using Frank-Wolfe algorithm and VISUM traffic modeling software. In order to determine the effectiveness of the proposed models, numerical applications are carried out on Sioux-Falls test network. Results showed that the Differential Evolution algorithm may effectively been used for the solution of transportation network design problems.