scholarly journals Microscopic Traffic Simulation Calibration Level for Reliable Estimation of Vehicle Emissions

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Jinsoo Kim ◽  
Jae Hun Kim ◽  
Gunwoo Lee ◽  
Hyun-ju Shin ◽  
Jahng Hyon Park
Keyword(s):  
Vehicle Emissions ◽  
Traffic Simulation ◽  
Calibration Procedure ◽  
Traffic Data ◽  
Microscopic Traffic Simulation ◽  
Micro Scale ◽  
Reliable Estimation ◽  
Calibration Measurement ◽  
Emission Models ◽  
Calibrated Simulation

Vehicle emissions are largely determined by the details of driving behaviours. Accordingly, emissions are often estimated by integrating micro-scale emission models into traffic simulations. Under this approach, it is essential to replicate the actual traffic situation being considered in an emission evaluation using a proper calibration procedure. Most previous research with respect to traffic flow has primarily focused on adjusting the complex combinations of parameters evaluated in these models, but it is not guaranteed that the use of widely used calibration measures can lead more accurate emissions estimates. Accordingly, we propose a systematic guideline for calibration to ensure reliable micro-scale emissions estimates. A calibration procedure is thus established in this paper based on various measure of effect (MOE) compositions (i.e., calibration levels) consisting of aggregated traffic data to identify the level that most reliably estimates micro-scale emissions. Five calibration levels of progressively more detailed measurements are first defined, valid calibration levels are identified, and the reliable calibration level is finally selected based on the available traffic data. The effect of vehicle type (i.e., light vs. heavy vehicles) composition on the estimated emissions is also evaluated for a well-calibrated simulation. We expect that a highly reliable estimation of emissions is possible using this more detailed traffic simulation calibration measurement.

scholarly journals Vehicle Emission Computation Through Microscopic Traffic Simulation Calibrated Using Genetic Algorithm

2019 ◽  
Vol 9 (1) ◽  
pp. 67-80 ◽  
Author(s):  
Yun Wei ◽  
Ying Yu ◽  
Lifeng Xu ◽  
Wei Huang ◽  
Jianhua Guo ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Simulation Model ◽  
Vehicle Emissions ◽  
Traffic Simulation ◽  
Urban Region ◽  
Vehicle Emission ◽  
Activity Data ◽  
Microscopic Traffic Simulation ◽  
Emission Models ◽  
Vehicle Activity

Abstract Vehicle emission calculation is critical for evaluating motor vehicle related environmental protection policies. Currently, many studies calculate vehicle emissions from integrating the microscopic traffic simulation model and the vehicle emission model. However, conventionally vehicle emission models are presented as a stand-alone software, requiring a laborious processing of the simulated second-by-second vehicle activity data. This is inefficient, in particular, when multiple runs of vehicle emission calculations are needed. Therefore, an integrated vehicle emission computation system is proposed around a microscopic traffic simulation model. In doing so, the relational database technique is used to store the simulated traffic activity data, and these data are used in emission computation through a built-in emission computation module developed based on the IVE model. In order to ensure the validity of the simulated vehicle activity data, the simulation model is calibrated using the genetic algorithm. The proposed system was implemented for a central urban region of Nanjing city. Hourly vehicle emissions of three types of vehicles were computed using the proposed system for the afternoon peak period, and the results were compared with those computed directly from the IVE software with a trivial difference in the results from the proposed system and the IVE software, indicating the validity of the proposed system. In addition, it was found for the study region that passenger cars are critical for controlling CO, buses are critical for controlling CO and VOC, and trucks are critical for controlling NOx and CO2. Future work is to test the proposed system in more traffic management and control strategies, and more vehicle emission models are to be incorporated in the system.

scholarly journals An Automatic Calibration Procedure of Driving Behaviour Parameters in the Presence of High Bus Volume

2019 ◽  
Vol 31 (5) ◽  
pp. 491-502 ◽  
Author(s):  
Nima Dadashzadeh ◽  
Murat Ergun ◽  
Sercan Kesten ◽  
Marijan Žura
Keyword(s):  
Calibration Procedure ◽  
Automatic Calibration ◽  
Traffic Data ◽  
Microscopic Traffic Simulation ◽  
Change Models ◽  
Calibration Process ◽  
Car Following ◽  
Driving Behaviour ◽  
Optimization Stage ◽  
Behaviour Models

Most of the microscopic traffic simulation programs used today incorporate car-following and lane-change models to simulate driving behaviour across a given area. The main goal of this study has been to develop an automatic calibration process for the parameters of driving behaviour models using metaheuristic algorithms. Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and a combination of GA and PSO (i.e. hybrid GAPSO and hybrid PSOGA) were used during the optimization stage. In order to verify our proposed methodology, a suitable study area with high bus volume on-ramp from the O-1 Highway in Istanbul has been modelled in VISSIM. Traffic data have been gathered through detectors. The calibration procedure has been coded using MATLAB and implemented via the VISSIM-MATLAB COM interface. Using the proposed methodology, the results of the calibrated model showed that hybrid GAPSO and hybrid PSOGA techniques outperformed the GA-only and PSO-only techniques during the calibration process. Thus, both are recommended for use in the calibration of microsimulation traffic models, rather than GA-only and PSO-only techniques.

scholarly journals Modelling Bicycle Infrastructure in SUMO

10.29007/6cs5 ◽  
2019 ◽  
Author(s):  
Georgios Grigoropoulos ◽  
Leonhard Lücken ◽  
Jakob Erdmann ◽  
Heather Kaths
Keyword(s):  
Traffic Simulation ◽  
Design Guidelines ◽  
Simulation Software ◽  
Urban Traffic ◽  
Traffic Signal Control ◽  
Traffic Data ◽  
Left Turn ◽  
Microscopic Traffic Simulation ◽  
Design Elements ◽  
Bicycle Infrastructure

Bicycle traffic is becoming an increasingly important part of urban traffic. Thus, the simulation and accurate representation of bicycle traffic in microscopic traffic simulation software is gaining importance. As bicycle traffic increases, dedicated bicycle infrastructure is designed to accommodate bicycle traffic. Especially at intersections, the design of intersection approaches follows specific rules and geometric limitations as defined by official design guidelines used in different countries across the world. However, when special environmental factors that affect the intersection layout, such as available space or gradient are not considered, specific standard forms of intersection approaches can be determined based on the number of traffic lanes, the traffic signal control and in the case of this study, the availability as well as the type of dedicated bicycle infrastructure. Categories with available bicycle infrastructure include the cases of bicycle lanes or advisory cycle lanes with advance stop lines for direct left turning bicyclists, the bicycle lanes or advisory bicycle lanes with bicycle boxes and bicycle lanes or bicycle paths with advanced stop lines and a stop area downstream for facilitating an indirect left turn or a two-stage (left) turn of bicyclists. The simulation of such bicycle infrastructure is not natively supported in microscopic traffic simulation software and is mostly only possible through intuitive adjustment of existing network design elements. In this paper, fictional intersections with special bicycle infrastructure are modelled in SUMO. Bicycle traffic data is collected at intersections in Germany with different types of bicycle infrastructure. The collected bicycle traffic data is then used to evaluate the intersection models. Specific recommendations for modelling bicycle infrastructure at intersection approaches in SUMO are provided, and limitations of the proposed methodologies and software limitations are discussed. Results show that the developed solutions can be used to model the bicycle traffic behavior with a reasonable degree of accuracy only for simulation scenarios and traffic situations unaffected by the identified software limitations.

A calibration procedure for increasing the accuracy of microscopic traffic simulation models

SIMULATION ◽  
2016 ◽  
Vol 93 (1) ◽  
pp. 35-47 ◽  
Author(s):  
Dwayne Henclewood ◽  
Wonho Suh ◽  
Michael O Rodgers ◽  
Richard Fujimoto ◽  
Michael P Hunter
Keyword(s):  
Traffic Simulation ◽  
Transportation Network ◽  
Flow Characteristics ◽  
Field Performance ◽  
Simulation Models ◽  
Calibration Procedure ◽  
Connected Vehicle ◽  
Microscopic Traffic Simulation ◽  
Vehicle Technologies ◽  
Operational Issues

Efforts to address operational issues in transportation have been the focus of many research efforts. A number of these efforts were geared toward developing microscopic traffic simulation models to accurately represent the complex and dynamic operation of a transportation network. One of the challenges with such models is that they do not always adequately reflect field conditions—particularly when representing traffic operations across different time periods. This paper presents a robust calibration procedure that aims to increase the accuracy of calibrated microscopic traffic simulation models. This procedure is based on a Monte Carlo approach to generate candidate parameter sets, which are aimed to produce calibrated simulation models. Model runs of these parameter sets are evaluated against robust calibration criteria, including startup and saturation flow characteristics and travel time distributions. The parameter sets that satisfy these criteria are considered as adequately calibrated to accurately reflect field performance measures. In applying this procedure, the results suggest that this approach offers a robust and effective method of calibrating simulation models where disaggregate-level vehicle data are available—which is becoming more prevalent with further advancements in mobile sensor and connected vehicle technologies.

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