In recent years, there have been intensive efforts to consider human factors (HFs) in the modeling of human driver behavior. In particular, “engineering” car-following models widely used in traffic ...simulation have been extended to include HFs. This extension is needed to generate critical situations, which are often attributable to human error. However, incorporation of reaction processes requires advanced models that take driver predictions and delayed responses into account. In this paper, a methodology for integrating HFs into driver behavior modeling is developed based on a long short-term memory architecture. The proposed methodology employed a three-layer psychological concept: perception, information processing, and action. The perception layer modeled (imperfect) estimation of visually received stimuli. Information processing included short-term memory and the projection of perceived stimuli into the near future. The executed action, based on the sensed as well as anticipated dynamic driving state, was delayed by the perception–reaction time. To represent individual differences among driver types, the available training dataset was classified in four clusters according to observable driver characteristics. The methodology was demonstrated with data recorded at an urban signalized intersection. Model performance was compared with that of two established engineering models, the intelligent driver model and the (extended) full velocity difference model. The results indicated that the human driver model developed here showed superior performance in replicating real-world trajectories compared with existing models and was able to represent the varying driving strategies of different groups.
Developing new solutions to complicated large-scale problems typically requires large-scale numerical simulation. Therefore, traffic simulations often run against randomized simulations instead of ...real-world traffic situations. This paper demonstrates a method to calculate the statistical significance of numerical simulations and optimizations in the presence of numerous random variables in complex systems using one-sided paired t-tests. While the paper covers a specific Fujitsu traffic-optimization project which uses SUMO for simulating the traffic situation, the method can be applied to many similar projects where a complete investigation of the solution space is not feasible due to the size of the solution space.
With an increasing number of vehicles equipped with adaptive cruise control (ACC), the impact of such vehicles on the collective dynamics of traffic flow becomes relevant. By means of simulation, we ...investigate the influence of variable percentages of ACC vehicles on traffic flow characteristics. For simulating the ACC vehicles, we propose a new car-following model that also serves as the basis of an ACC implementation in real cars. The model is based on the intelligent driver model (IDM) and inherits its intuitive behavioural parameters: desired velocity, acceleration, comfortable deceleration and desired minimum time headway. It eliminates, however, the sometimes unrealistic behaviour of the IDM in cut-in situations with ensuing small gaps that regularly are caused by lane changes of other vehicles in dense or congested traffic. We simulate the influence of different ACC strategies on the maximum capacity before breakdown and the (dynamic) bottleneck capacity after breakdown. With a suitable strategy, we find sensitivities of the order of 0.3, i.e. 1 per cent more ACC vehicles will lead to an increase in the capacities by about 0.3 per cent. This sensitivity multiplies when considering travel times at actual breakdowns.
The ongoing research in intelligent transport systems and connected and automated vehicles, enabled by advancements in artificial intelligence, integrating traffic simulations has become an essential ...part of product/software development for the automotive industry. Nowadays, traffic simulations are used to mimic real-world environment scenarios for virtual testing of advanced transportation technologies. . With the increase in data collection methods for traffic flow, the calibration of the microscopic traffic simulations has emerged as an important research area. The underlying question in traffic modeling is how accurately simulations can mimic the real environment traffic flow conditions? This paper attempts to create a framework for microscopic traffic simulation calibration procedure which can be scaled for large networks. This paper makes the following major contributions. First, a calibration framework is proposed which harnesses the existing data set collected from The Ohio State University (OSU) campus bus service (CABS) busses using Global Positioning System (GPS) sensors to determine the traffic state in the real environment and create a microscopic traffic simulation. The traffic simulation is implemented for a section of the OSU campus (“Woody Hayes Drive") in an opensource traffic simulator – Simulation of Urban MObility (SUMO). The traffic flow generation is probabilistic to introduce variability between scenarios. The second contribution is the development of a communication interface between real-time dSpace ASM Hardware in Loop setup with SUMO to create a complete real-time simulation of urban environments for advanced driver assist systems (ADAS) virtual testing. Ademonstration scenario is the Ohio State University campus network with traffic demand generated using the calibrated model from the first part of the work.
Connected vehicles (CVs) and their supporting infrastructure are expected to play an important role in the management of traffic congestion. As highway expansion projects are becoming less common, ...deploying emerging technologies is essential to make the most of the current road infrastructure. Most published studies report that CVs improve traffic performance only marginally. Here, we propose that CVs drive cooperatively with cooperative adaptive cruise control (CACC)-enabled vehicles by designating a CACC lane for periods with high flows of slow-moving heavy-duty drayage trucks. To assess if this approach could help absorb year 2035 projected drayage traffic increases at the Ports of Los Angeles and Long Beach, which is the largest port complex in the U.S.A., we analyze three 2035 scenarios for I-710, a key freeway for freight transportation in Southern California: (1) CACC-enabled vehicles are deployed under mixed traffic conditions; (2) CACC-enabled vehicles are restricted to the first lane (left-most lane); (3) the first lane is reserved for CACC-enabled vehicles, and access is optional. Our results suggest that substantial speed improvements can be obtained, but only when the first lane is CACC reserved with optional access, because this approach creates more platooning opportunities and thus helps maximize the benefits of CACC.
Analytical models and traffic microsimulation are two widely used platforms for evaluating roundabout operations. The application of the correct inputs and proper specification of calibration ...parameters should precede the actual simulation, to replicate field traffic conditions. In this sense, simultaneous data collection and estimation of the input, calibration, and validation variables, along with knowledge of their definitions, are crucial. Although simultaneity of data gathering is virtually guaranteed with the use of wide-frame videos captured with an unmanned aerial system (UAS), there are cases where sight distance restrictions may obscure observations of the back of queue and arrival patterns. This paper explores the calibration and validation efforts associated with an analytical platform, SIDRA 9, and a microsimulation model, TransModeler 5, conducted under sight-restricted conditions. Video captured from a drone, followed by trajectory extraction using video processing software, was used to analyze operations on two approaches at a single-lane roundabout. In the process, the team employed a specialized demand estimation method, and developed a novel data collection scheme for estimating the critical headway distribution in TransModeler 5. Because of sight distance constraints, the model validation was limited to the use of the observable system travel time and associated travel speed within the field of view. The comparison results, for both platforms, have confirmed the value of model calibration in more accurately describing field performance. The calibrated models performed differently between the two approaches, with the approach having a larger presence of buses and heavy vehicles yielding slightly poorer results.
State of Bicycle Modeling in SUMO Roosta, Aboozar; Kaths, Heather; Barthauer, Mirko ...
SUMO Conference Proceedings,
06/2023, Letnik:
4
Journal Article
Recenzirano
Odprti dostop
Microscopic traffic simulation tools provide ever-increasing value in the design and implementation of motor vehicle transport systems. Research and development of automated and intelligent ...technologies have highlighted the usefulness of simulation tools and development efforts have accelerated in recent years. However, the majority of traffic simulation software is developed with a focus on motor vehicle traffic and has limited capabilities in the simulation of bicycles and other micro-mobility modes. Bicycles, e-bikes and cargo bikes represent a non-negligible modal share in many urban areas and their impact on the operation, efficiency and safety of traffic systems must be considered in any comprehensive study. The Differentiation between different types of micro-mobility modes, including microcars, e-kick scooters, different types of bicycles and other personal mobility devices, has not yet attracted enough attention in the development of simulation software which creates difficulties in including these modes in simulation-based studies. On November 25th, 2022, members of the SUMO team at DLR organized a workshop to assess the state of bicycle simulation in SUMO, identify shortcomings and missing capabilities and prioritize the order in which bicycle traffic related features should be modified or implemented in the future. In this paper, different aspects of simulating bicycle traffic in SUMO are examined and an overview of the results of the workshop discussions is given. Some suggestions for the future development of SUMO emerging from this workshop, are presented as a conclusion.
High-occupancy vehicle (HOV) lane performance degradation has become more prevalent in many regions because of the growing travel demand and the increasing number of HOV lane-eligible vehicles. ...Conventional capacity expansion strategies, such as adding a second HOV lane, can be a promising solution. However, they can be difficult in areas where there is little room left to add new travel lanes in both directions. In that case, adding a contraflow HOV lane could be a good compromise, especially if the peak travel demands in the HOV lanes are tidal. In this work, we study the impact of adding a contraflow HOV lane on a section of the I-215 freeway, which connects two major cities in Riverside County, California. Two alternative designs, “full contraflow” and “partial contraflow” HOV lanes, are evaluated in the traffic microsimulation environment. The evaluation results show that in the case of the full contraflow HOV lane design, the average delay during peak hours in the southbound direction of the freeway would be reduced by 76% compared with the scenario with no additional HOV lane. The implementation of the full contraflow HOV lane to supplement the existing HOV lanes would also increase the average speed in the currently degraded HOV lane from 37.8 to 55.0 mph, which is significantly above 45 mph, the speed threshold for HOV lane performance degradation.
Usage profiles of shared autonomous fleets will considerably differ from present-day privately owned vehicles. Thus, requirements on powertrain and other vehicle components are expected to change ...significantly. While there are still no real-world data available, automotive requirement engineering strongly depends on synthetic driving profiles, for example, forwarded by traffic simulation. These simulations, however, are quite challenging as they need to combine multi-modal, large-scale fleet simulations with microscopic traffic modeling to simultaneously produce realistic usage profiles and detailed driving cycles. We aim to combine the two open-source tools MATSim and SUMO to achieve this goal. As an important step in this endeavor, we analyze the consistency of both MATSim and SUMO with regard to traffic dynamics by means of three experiments with an increasing level of complexity: (i) analytically on a homogeneous road segment in the steady-state; (ii) numerically on a homogeneous road segment in the non-stationary state for a synthetic test case; and (iii) numerically for a highly non-linear medium-sized real-world test case in Berlin. We analyze the simulation results with respect to macroscopic flow–density–speed relations. In addition, we also study network impedances for the Berlin test case. We show that the traffic dynamics of MATSim and SUMO behave differently for the various test cases and discuss the implications on our tool-coupling efforts.
Simulation is an indispensable tool for the assessment of highway-related capital investments and operational changes. Model calibration, a challenging task in any simulation study, is a crucial ...step. The model’s robustness, accuracy, and quality are directly dependent on it. Many parameters exist, and field observations are often lacking to aid in their correct specification. Recently, videos from drones have created a uniquely powerful way to aid this process. Observations of the inputs (demand), outputs (vehicles processed), processing rates (e.g., saturation flow rates), and performance results (times in system, queue dynamics, and delays) are all available simultaneously. For signalized intersections, only the signal timing events are missing, and those data can be obtained from signal timing logs. This paper illustrates how modeling teams can use drone data to calibrate model parameters pertaining to intersection operation. It shows how saturation flow rates can be adjusted for signalized intersections so that queue dynamics and delays can be matched. For roundabouts, it illustrates how critical gaps and move-up times can be adjusted to match field observations of performance. Three real-world settings with associated drone data are used as case study examples.
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