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A Comprehensive Simulation Environment for Testing the Applications of a V2X Infrastructure
Published in Nishu Gupta, Joel J. P. C. Rodrigues, Justin Dauwels, Augmented Intelligence Toward Smart Vehicular Applications, 2020
Apratim Choudhury, Tomasz Maszczyk, Chetan B. Math, Hong Li, Justin Dauwels
There are already some intelligent traffic management systems in existence around the world. In Singapore, the green link determining system (GLIDE) [4, 5] is in operation. This system is an adaptation of the Sydney coordinated adaptive traffic system (SCATS) [6] which applies real-time traffic information to establish a signal scheduling policy. In addition, there are similar systems currently in place in Singapore, such as TrafficScan [7], junction electronic eyes (J-EYES), the expressway monitoring advisory system (EMAS) [5], and electronic road pricing (ERP) [19]. However, most global traffic management solutions are reactionary systems that are activated only when congestion is observed on any part of the traffic network. A more proactive system to tackle congestion would be to implement a strategy that brings about uniformity in the traffic movement profile, such as the green light optimized speed advisory (GLOSA) system [8]. Therefore, the aim of this work is to utilize the integrated simulation environment [9] consisting of VISSIM (traffic simulation), MATLAB (V2X application modeling), and NS3 (communication simulation) to analyze as exhaustively as possible whether the application of GLOSA leads to any benefits with regard to fuel consumption and queue length. GLOSA simulations are carried out with both a fixed-time traffic signal policy and also the GLIDE system in order to compare the differences in the effects that GLOSA may have. Our aim with this chapter is to demonstrate the capability of the simulation platform to model and assess various facets of a large-scale V2X application. To illustrate the versatility, we obtain results by adding variation to the following traffic and communication parameters: Traffic parameters Traffic networkVehicle volumeTraffic signal timing policyV2X penetration rateCommunication parameters Transmitter powerReceiver energy detection thresholdData rate
Integrating data-driven and simulation models to predict traffic state affected by road incidents
Published in Transportation Letters, 2022
Sajjad Shafiei, Adriana-Simona Mihăiţă, Hoang Nguyen, Chen Cai
This study evaluates the proposed framework models for one of the major subnetworks in Sydney, stretching alongside the Victoria Road corridor from CBD to western city (see Figure 2). The subnetwork includes 1,310 links and 428 nodes. The General Transit Feed Specification (GTFS) data is used to import public transport information such as bus time schedules, lines, and bus stop data. There are 81 signalized intersections with the adaptive SCATS control system running. The link traffic counts obtained from the SCATS detectors are aggregated in 15-min time intervals. Most of the SCATS signals are located throughout the main corridor and near the Sydney CBD. The simulation is conducted for 4-hour morning peak hours from 6:00 to 10:00 AM using AIMSUN microscopic simulation model. AIMSUN is a discrete-event simulation tool established based on car-following and lane-changing models (Aimsun 2013). Therefore, detailed traffic phenomena such as congestion propagation and dissipation of queues are simulated over time. We used a modified multinomial logit model as an advanced stochastic route choice model (Aimsun 2013). Maximum five shortest paths are calculated using Dijkstra’s label-setting algorithm. The probability of choosing a path k is then calculated according to the utility function of each path.
Operational performance evaluation of adaptive traffic control systems: A Bayesian modeling approach using real-world GPS and private sector PROBE data
Published in Journal of Intelligent Transportation Systems, 2020
Zulqarnain H. Khattak, Mark J. Magalotti, Michael D. Fontaine
These various systems have been examined in several studies. A study regarding the Sydney Coordinated Adaptive Traffic system (SCATS) in Park City, Utah compared the performance of coordinated time-of-day signal timing to SCATS. A before study was conducted on Time of Day (TOD) coordinated signals, however a post-SCATS evaluation could not occur until two years after the original before study. As a result, performance of the system was evaluated using an off and on technique that compared a coordinated time-of-day plan with SCATS. The results suggested that performance gains with SCATS active were measurably greater than those with SCATS off for travel time and number of stops. The relevance of an off on technique in place of a before after study was analyzed and results showed that the two datasets behaved consistently 62.5% of the time hence, concluding that the values provide a basis of support for using the off data which better represent the before signal timings on an after network (Kergaye, Stevanovic, & Martin, 2010 b). Kergaye, Stevanovic, & Martin, 2010a again used the same before SCATS data and off/on data for comparison with a microsimulation model build in VISSIM and found similar results for performance gains of SCATS. They concluded that a well-calibrated microsimulation model can accurately reflect field conditions, but such an effort can be very challenging.
Fine-tuning time-of-day partitions for signal timing plan development: revisiting clustering approaches
Published in Transportmetrica A: Transport Science, 2019
Peng Chen, Nan Zheng, Weili Sun, Yunpeng Wang
To demonstrate the mechanism between TOD partition and signal control plan, the optimal signal timings were determined using Synchro for all investigated clusters. As aforementioned, for each TOD interval an optimal signal timing plan will be developed. In order to account for the prevailing traffic conditions to a large extent, the 85th percentile directional volumes at each TOD interval were selected and used for optimization process. The parameters of cycle length and green split were obtained accordingly. Recall that the intersection of interest was operated by the adaptive traffic system, i.e. SCATS. For comparison purpose, the signal timings developed for TOD partitions by ordinal clustering under Δt = 15 min on 25 August 2008 (as shown in Figure 3(b)) were used. Figure 8 presents the results of optimal cycle lengths by fine-tuned TOD intervals and SCATS.