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Traffic load patterning on long span bridges
Published in Nigel Powers, Dan M. Frangopol, Riadh Al-Mahaidi, Colin Caprani, Maintenance, Safety, Risk, Management and Life-Cycle Performance of Bridges, 2018
Microsimulation models consist of vehicle-following models and lane-changing models to simulate the vehicle movements on the road. It is powerful and convenient to record the position, direction, speed, axle arrangement, and other features of one single vehicle at any time, making it very useful for bridge loading studies. In recent years, Microsimulation models have been widely used in traffic analysis with different levels of accuracy (Orosz et al., 2010). However, it is quite important to deal with the calibration and validation process, as the data is simulated, to ensure its validity (Treiber et al., 2000). Ten microsimulation models (including IDM) are compared by Brockfeld et al. (2004) and they found it is almost impossible to calibrate results to within 10% variance. The common range of differences is 14 to 16% and the performances of various models are quite similar.
An Operation-Reduced Fast Modeling in 5G Communication Systems
Published in Zoran S. Bojkovic, Dragorad A. Milovanovic, Tulsi Pawan Fowdur, 5G Multimedia Communication, 2020
Vladimir Mladenovic, Sergey Makov, Yigang Cen, Asutosh Kar
Microsimulation is a method to mimic a complex phenomenon through the description of its microcomponents. Essentially, it leaves the system free to develop without too many constraints and simplifying assumptions [18]. But when we use microsimulation with symbolic-only contain, and we change with particular numerical values in the final stage, it becomes MSSA. Furthermore, we will observe each element of the symbolic calculation through MSSA, which will further provide a better testing and verification of the fast computation as well as reduction of operations [19,20]. Also, MSSA provides calculation directly in the first run without the need for more simulation attempts.
Evaluating the capability of deterministic and stochastic simulation tools to model oversaturated freeway operations
Published in Gianluca Dell’Acqua, Fred Wegman, Transport Infrastructure and Systems, 2017
D. Jolovic, P. Martin, A. Stevanovic, S. Sajjadi
There are several widely spread microsimulation tools on the US market—TSS Aimsun, PTV Vissim, Transmodeler, Corsim, etc. This paper applies PTV Vissim as an alternative tool to model and analyze the oversaturated freeway segment. Generally, microsimulation tools will produce more accurate results but require more input, and can be time-consuming. On the other hand, FREEVAL was created to be a simple tool for quick facility assessment. The results may not be as comprehensive as from the micro simulator, due to its macroscopic nature.
Investigating the safety performance of the new continuous green T-partial cloverleaf A interchange
Published in Journal of Transportation Safety & Security, 2023
Mutasem Alzoubaidi, Milan Zlatkovic
Using the collected data from UDOT, the test-case network’s safety performance was studied for the traffic conditions of 2019 and those of the future year 2029. The CGT-parclo A, parclo A, parclo progressA, DPI, folded interchange, and parclo B were all designed in Autodesk AutoCAD Civil 3 D according to the American Association of State Highway and Transportation Officials’ Green Book (American Association of State Highway & Transportation Officials, 2018). Based on these designs, seven scenarios were developed and modeled for each year and peak hour, where the scenarios varied in the interchange design at I-15 and SR-151 as follows: existing condition (SPUI model), CGT-parclo A model, parclo A model, parclo progressA model, DPI model, folded interchange model, and parclo B model. For the 2019 models, traffic control and signal timings for the ramp terminals of each of the CGT-parclo A, parclo A, parclo progressA, DPI, folded interchange, and parclo B were optimized using Synchro 10, which is a traffic signal timing and optimization tool. As for the future 2029 models, traffic control and signal timing optimization were also carried out using Synchro 10 for the predicted traffic volumes. The simulation network was built in VISSIM 11 microsimulation software. Additionally, Econolite’s external ASC/3 Software-in-the-Loop (SIL) signal controller was used to mimic the real-world signal operations for each model. VISSIM’s trajectory output files were then processed in FHWA’s SSAM. This was conducted for all scenarios and both modeling years of the study.
Modeling activity-based tour shared travel choices, tour-level activity participation and time allocation
Published in Transportmetrica A: Transport Science, 2022
Nazmul Arefin Khan, Muhammad Ahsanul Habib
The prototype SDS model generates the baseline information for 2006. Next, it runs simulations for the years 2007 until 2021. The simulation results are validated for the base year 2006 and simulation year 2016 using the 2006 and 2016 Canadian Censuses, respectively, based on distance and duration to mandatory activity-tours (Figure 2). The comparative analysis suggests that both year 2006 and 2016 demonstrate an under-representation of less than 2% until a distance of 19.9 km is reached. Distance category 20–24.9 km shows an over-representation of less than 1% in both years. Higher distance categories (i.e. 25–29.9 km and 30 km and above) are over-represented by around 3%. For mandatory activity-tour duration, the validation is done using 2016 Canadian Census data since 2006 Census data does not include such an indicator. The duration of mandatory activity-tours indicates that the SDS model under-represents the ‘less than 30 minutes’ and ‘30–59 minutes’ categories by 0.2% and 2.8%, respectively. The maximum difference is found for ‘60 minutes and over’ category, which is an over-representation of only 4%. Therefore, based on the validation results, the microsimulation model can be considered reasonably satisfactory.
Combined connected vehicles and variable speed limit strategies to reduce rear-end crash risk under fog conditions
Published in Journal of Intelligent Transportation Systems, 2020
Yina Wu, Mohamed Abdel-Aty, Ling Wang, Md Sharikur Rahman
This paper aims to combine CV and VSL controls to reduce the rear-end crash risk when a bottleneck occurs under fog conditions. A new VSL control algorithm will be firstly proposed based on the occurrence of rear-end crashes by using traffic and weather characteristics. Then, the feedback control algorithm of the V2I system was developed to further test the benefits of the VSL controls under the CV environment. The developed algorithm has been tested using the VISSIM microsimulation tool via an integrated VISSIM-COM interface. A surrogate safety measure, time to collision (TTC), is used to capture the change of rear-end crash risk with the proposed control strategies. In addition, total travel time (TTT) is used to evaluate the change of network efficiency.