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Macroscopic fundamental diagram (MFD)-based perimeter control has a potential to improve traffic throughput and relieve the overall congestion. In practice, not only the MFD but also the traffic demand suffers from a variety of inherent uncertainties. Hence, this paper aims to contrive a robust control technique to address the perimeter traffic flow control issue in the oversaturated region. To this end, an integral sliding mode control is proposed to drive the traffic state to the desirable condition. The developed strategy deals with practical issues such as finite time stability and range of uncertainty in both MFD and traffic demand. Theoretical analysis verifies that the developed integral sliding mode control approach can guarantee the finite time convergence of the traffic state to the desired one. The performance of the developed scheme is attested by considering various traffic scenarios with uncertain MFDs and traffic demand, in which a comparative performance study with the proportional and integral control method is conducted. It is indicated that the developed scheme can alleviate the congestion in the urban network and improve the throughput of the urban network. Practical Applications: The research presented in this article proposes a novel perimeter control technique designed to enhance traffic flow management in densely populated urban road networks, particularly during peak congestion times. By leveraging the macroscopic fundamental diagram (MFD) and integral sliding mode control theory, the method significantly boosts traffic throughput and alleviates the impact of congestion. This advancement can be seamlessly integrated into current urban traffic management systems, leading to more efficient and convenient urban commutes. Additionally, it addresses the rise in vehicle emissions due to heavy traffic, aiding in the reduction of pollution and supporting sustainable development initiatives. The technique also curtails vehicle fuel consumption and cuts down on costs associated with congestion-related delays, thereby fostering resource optimization and economic growth within urban environments. Moreover, the method is designed to be resilient, taking into account the variability of traffic demand and ensuring the robustness of the traffic control strategy. Overall, the article demonstrates the practical application of advanced control technologies to address real-world traffic challenges, providing a scalable and robust solution adaptable to realistic situations with the uncertainties of urban traffic demand. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach to intersection improvement planning utilizing telematics data from connected vehicles to generate performance measures for mobility, safety, and emissions. Congestion, crashes, and emissions are three major issues in urban areas, particularly at intersections, and agencies often struggle to prioritize improvement plans because of a lack of objective data. Traditional infrastructure sensors provide limited information at selected locations, but it is not feasible to deploy them at all intersections. The use of telematics data from connected vehicles provides a high granularity of information on driving events and trajectories that can be used in conjunction with vehicle emission modeling to efficiently generate performance measures for all intersections. In a case study of over 300 intersections in Arlington, Texas, the Pareto front method was used to evaluate and rank intersections based on multiple criteria. Intersections falling on the Pareto front were identified as having at least one outstanding (poor) performance measure and were required to be given priority for improvement. The results were cross-validated with historical crash reports and the judgments of city traffic engineers, demonstrating the effectiveness of the proposed framework in generating objective and reliable intersection performance measures. This approach has the potential to significantly improve intersection safety, mobility, and environmental impact, and can serve as a valuable decision-support tool for transportation agencies. [ABSTRACT FROM AUTHOR]

This study proposes a new approach for measuring field pedestrian waiting delay and developed a new pedestrian waiting delay model for signalized midblock crosswalks under mixed traffic conditions. Eight signalized midblock crosswalks were selected in the southern part of India, and data were collected using videographic technique. Pedestrian characteristics, cycle time, and phase lengths were extracted using frame-by-frame extraction technique with a least count of 0.03 s. In the current study, field pedestrian waiting delay was measured by plotting queue length against cycle time. The proposed approach was validated using the conventional approach for measuring field waiting delay. A new pedestrian waiting delay model was developed for signalized midblock crosswalks under mixed traffic conditions. Two new coefficients, i.e., the coefficient of nonuniform arrival rate (Δ1) and the coefficient of noncompliance behavior (Δ2), were incorporated into the existing Webster delay model. The former is modeled using regression analysis, and the latter is calculated as the proportion of violators. The proposed pedestrian waiting delay model was validated with the field waiting delay. The proposed new approach for measuring field waiting delay had an error of 5% compared with the conventional approach for measuring waiting delay. Hence the proposed approach for measuring pedestrian waiting can replace the conventional method for measuring field waiting delay because the new method minimizes the data extraction time. The proposed pedestrian delay model was found to be accurate in estimating the pedestrian waiting delay at signalized midblock crosswalks. The mean absolute percentage error (MAPE) value of the new pedestrian waiting delay was found to be less than 12%. The proposed waiting delay model can be used to define the level of service (LOS) at signalized midblock crosswalks, and will aid traffic engineers and urban planners in improving pedestrian facilities and safety [ABSTRACT FROM AUTHOR]

Following major hazards and incidents, it is crucial to mitigate the congestion at intersections of urban traffic systems with disruptions; maximize the evacuation, rescue, and recovery efficiency; and prevent a hazard from turning into a disaster. An optimized traffic signal design strategy can effectively contribute to maintaining an efficient traffic system operation despite various disruptions. Most of the existing studies focused on static and generic congestion scenarios during the recovery stage, rather than realistic time-progressive scenarios covering the whole process following a disruption. An adaptive traffic signal control strategy in response to traffic disruptions at a single intersection is proposed by covering both the incident and recovery stages. Dynamic phase selection (DPS) technology is applied to adjust the traffic signal control plan adaptively during the incident stage, while the queue length dissipation (QLD) algorithm is adopted to carry out optimal green time calculation during the recovery stage. The proposed methodology is demonstrated by considering disruptions caused by several typical vehicle crashes at intersections. The proposed DPS+QLD traffic signal strategy is found to improve the resiliency of a typical intersection against disruptions by clearing queues faster, reducing overall traffic loss time, and maintaining stable mobility with superior performance over conventional fixed and actuated traffic signal plans. DOI: 10.1061/JTEPBS.0000671. [ABSTRACT FROM AUTHOR]

The outbreak of coronavirus disease 2019 (COVID-19) disrupted our regular life. Many local authorities enforced a cordon sanitaire to contain the rapid spread of the disease. Travelers can only pass the cordon after the disease screening. This paper aims to propose a method to design a traffic inflow control scheme for onramp metering to maximize urban freeway network throughput with an endurable queuing delay constraint at all offramps around cordon sanitaire. A bilevel programming model is formulated where the lower level is transportation system equilibrium to predict link traffic flows. The upper level is onramp metering optimization that is nonlinear programming. A stochastic queuing model is used to represent the waiting phenomenon at each offramp where the disease testing is conducted. A heuristic algorithm is designed to solve the proposed bilevel programming model where the method of successive averages (MSA) is adopted for the lower-level model, and a genetic algorithm (GA) with elite strategy is adopted for the upper-level model. An experimental study is conducted to demonstrate the effectiveness of the proposed method and algorithm. The results show that these methods can find a good heuristic optimal solution. These methods are useful for freeway operators to determine the optimal onramp control for disease control and prevention. They are also beneficial to set up checkpoints for all kinds of risks such as drunk driving and criminal searching. [ABSTRACT FROM AUTHOR]

Modern urban traffic control (UTC) systems are a key element of intelligent transportation systems (ITS). They represent the answer to the need of increased road network capacity and provide important benefits by reducing delays, stops, and travel times. Traffic parameters, measured or computed in the field, enable an UTC system to operate in a fully adaptive mode. This way, local decision units are able to follow variations in the traffic behavior and produce optimal signaling plans. Therefore, it is highly important to have this information within a distributed approach, where neighboring junctions cooperate to produce optimal control strategies. This paper aims to demonstrate the importance of different traffic parameters and how their absence affects the signaling plans and the accuracy of traffic analyses. The present study uses a local adaptation simulation option embedded in the Synchro 7 modeling tool to assess and classify these parameters according to their impact on performing efficient traffic control; the results can be deployed in any real UTC distributed system to ensure that critical information is successfully exchanged between its local decision units to maintain a fully adaptive operation. [ABSTRACT FROM AUTHOR]

This research aims at developing a system of real-time simulation-based dynamic traffic model under mixed traffic flow conditions. The system consists of two layers, namely, simulation layer and real-time control layer. The system is implemented based on rolling horizon approach, which is advanced for each stage; thus real-time data can be incorporated within the framework. In order to predict normative, as well as predictive, information, a simulation-based dynamic traffic assignment model is employed within each stage. Empirical data for a real city network, such as flows from vehicle detectors, are used to validate the model in a real-time environment. The values of mean absolute percentage error and root-mean-squared percentage error are within 15%, and the results show promising agreements between observed and simulated flows. [ABSTRACT FROM AUTHOR]

Data collected at four locations in a medium-sized city of India are analyzed for pedestrians flow characteristics under mixed traffic conditions. The data are presented in the form of mathematical and graphical relationships between speed and volume, speed and density, flow and area module, and flow and density. The results of analysis are compared with those given in literature. The free-flow speed of pedestrians is observed to be 80 m/min which is higher than that reported for China and Singapore, but slightly lower than that in Germany. It is comparable to free speeds reported for Philippines and the United States. The speed of the pedestrian was found to be influenced by the age and gender also. Male pedestrians move faster than female pedestrians. Pedestrians in the age group of 10–15 years had the highest speed, 82 m/min. the speed was reduced by about 85% when pedestrians move with their baggage (or luggage). [ABSTRACT FROM AUTHOR]

Comments on the study "Effect of Lane Width on Capacity Under Mixed Traffic Conditions in India," by Satish Chandra and Upendra Kumar in the March/April 2003 issue of the "Journal of Transportation Engineering." Failure of the authors to acknowledge the fact that the rate of increase of traffic on the roads in India is higher in comparison to the rate of addition of vehicles; Importance of the knowledge of road capacity for planning purposes; Failure to understand as to how such comparisons can be attributed to the nature of mixed traffic and the regulatory system on Indian roads.