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In this work, moving synchronized flow patterns (MSP) in empirical city traffic at signals have been observed which was predicted by Kerner (2013, 2014). The single vehicle data has been obtained through aerial observations. Based on this microscopic data, we have found trajectories for all vehicles together with vehicle speeds as functions of time and space. This has allowed us to find empirical MSPs in oversaturated city traffic as well as to perform microscopic analysis, that revealed the following empirical spatiotemporal features of MSPs: (i) MSPs emerge upstream of the queue at the signal and then they can propagate through the complete road section, (ii) merging of several MSPs into a single MSP, (iii) dissolving MSPs and (iv) spontaneous emerging of MSPs faraway upstream of the signal, (v) spontaneous emerging of moving queue within an MSP that is far away upstream of the signal. As a base for this work, we used an unmanned aerial vehicle (UAV) to record videos of inner city traffic situations and supervised tracking methods to gather the vehicle trajectories. [ABSTRACT FROM AUTHOR]

• Propose a cooperative signal-free intersection control framework under V2X communications. • Proposed framework integrates virtual platooning control and traffic flow regulation. • Virtual platooning controller mitigates effects of parametric inaccuracies and unparameterized disturbances. • Virtual platooning controller guarantees string stability. • Traffic flow regulation alleviates traffic spillbacks and travel delays. The emerging technologies of connectivity and automation enable the potential for signal-free intersection control. In this context, virtual platooning is posited to be an innovative, decentralized control strategy that maps two-dimensional vehicle movements onto a one-dimension virtual platoon to enable intersection operations. However, the effectiveness of virtual platooning-based control can be limited or degraded by parametric inaccuracies and unparameterized disturbances in vehicle dynamics, heavy traffic congestion, and/or uncoordinated platoons in multi-lane intersections. To explicitly address these limitations, this study proposes a hybrid cooperative intersection control framework consisting of microscopic-level virtual platooning control and macroscopic-level traffic flow regulation for traffic environments with connected autonomous vehicles. In virtual platooning control, vehicles approaching an intersection are organized into coordinated independent virtual platoons to avoid potential conflicts triggered by platoon formation changes. Through coordination, vehicles in a platoon are grouped into compatible passing sets to maintain desired safe spacing when proceeding through the intersection. We propose a distributed adaptive sliding mode controller (DASMC) which uses the backstepping control method and model reference adaptive control method to address parametric inaccuracies, and the sliding mode control method to consistently suppress the negative effects of the unparameterized disturbances. Each vehicle approaching the intersection utilizes the kinematic information from neighboring vehicles to implement the DASMC in a distributed manner such that vehicles within the same virtual platoon can achieve consensus safely. However, virtual platooning control cannot preclude excessive traffic from approaching the intersection, which can cause undesired spillbacks and degrade intersection control performance. To address this issue, traffic flow regulation is integrated with the virtual platooning control using an iterative feedback loop mechanism. In each iteration of the iterative feedback loop, a constrained finite-time optimal control (CFTOC) problem is solved to determine the optimal input flow permitted to proceed through the intersection, and the virtual platooning control provides feedback on the queue status to the CFTOC to initiate the next iteration. The effectiveness of the proposed intersection control framework is evaluated through numerical experiments. The results indicate that the proposed virtual platooning DASMC controller can mitigate the effects of parametric inaccuracies and unparameterized disturbances to achieve consensus for approaching vehicles, as well as guarantee string stability. Further, the proposed framework can alleviate traffic spillbacks and travel delays effectively through traffic flow regulation. [ABSTRACT FROM AUTHOR]

During a pandemic such as COVID-19, managing public transit effectively becomes a critical policy decision. On the one hand, efficient transportation plays a pivotal role in enabling the movement of essential workers and keeping the economy moving. On the other hand, public transit can be a vector for disease propagation due to travelers' proximity within shared and enclosed spaces. Without strategic preparedness, mass transit facilities are potential hotbeds for spreading infectious diseases. Thus, transportation agencies face a complex trade-off when developing context-specific operating strategies for public transit. This work provides a network-based analysis framework for understanding this trade-off, as well as tools for calculating targeted commute restrictions under different policy constraints, e.g., regarding public health considerations (limiting infection levels) and economic activity (limiting the reduction in travel). The resulting plans ensure that the traffic flow restrictions imposed on each route are adaptive to the time-varying epidemic dynamics. A case study based on the COVID-19 pandemic reveals that a well-planned subway system in New York City can sustain 88% of transit flow while reducing the risk of disease transmission by 50% relative to fully-loaded public transit systems. Transport policy-makers can exploit this optimization-based framework to address safety-and-mobility trade-offs and make proactive transit management plans during an epidemic outbreak. • Network-based analysis for safety-and-mobility trade-offs. • Integrate spatial compartmental and transit network models for epidemic management. • Heuristic for time-varying mass transit flow control policies. [ABSTRACT FROM AUTHOR]

Abstract: The continuously increasing daily traffic congestions on motorway networks around the world call for innovative control measures that would drastically improve the current traffic conditions. Mainstream traffic flow control (MTFC) is proposed as a novel and efficient motorway traffic management tool, and its possible implementation and principal impact on traffic flow efficiency is analysed. Variable speed limits, suitably operated and enforced, is considered as one (out of several possible) way(s) for MTFC realisation, either as a stand-alone measure or in combination with ramp metering. A previously developed, computationally efficient software tool for optimal integrated motorway network traffic control including MTFC is applied to a large-scale motorway ring-road. It is demonstrated via several investigated control scenarios that traffic flow can be substantially improved via MTFC with or without integration with coordinated ramp metering actions. [Copyright &y& Elsevier]

Abstract: The characterization of the dynamics of traffic states remains fundamental to seeking for the solutions of diverse traffic problems. To gain more insights in traffic dynamics in the temporal domain, this paper explored traffic patterns in higher-dimensional state spaces, where we attempted to map the one-dimensional traffic series into appropriate multidimensional spaces by Takens’ algorithm. After such a state space reconstruction, we then made use of the largest Lyapunov exponent to depict the rate of expansion or contraction of traffic state trajectories in the reconstructed spaces. The correlation dimension was further estimated to examine if the traffic state trajectories exhibited chaotic-like or stochastic-like motions. An empirical study using flow, speed, and occupancy time-series data as well as the speed-flow, speed-occupancy, and flow-occupancy paired data collected from dual-loop detectors on a freeway of Taiwan was conducted. The numerical results revealed that different nonlinear traffic patterns could emerge depending on the observed time-scale, history data and time-of-day. In addition, with consideration of sequential order and spatiotemporal features, more information about traffic dynamical evolution was extracted. [Copyright &y& Elsevier]

Abstract: In this work, we apply the iterative learning control approach to address the traffic density control problem in a macroscopic level freeway environment with ramp metering. The traffic density control problem is first formulated into an output tracking and disturbance rejection problem. Through rigorous analysis, it is shown that the iterative learning control method can effectively deal with this class of control problem and greatly improve the traffic response. Next, the iterative learning control is combined with error feedback in a complementary modular manner to achieve the output tracking and system robustness. The effectiveness of the new approach is further verified through case studies with intensive simulations. [Copyright &y& Elsevier]

Abstract: This paper deals with the construction of fuzzy costs and more particularly with their meaning in traffic assignment models based on fuzzy logic tools. The idea is to separate different possible semantics, namely imprecision, uncertainty and grade of preference. The classically encountered approach is based on the gathering of those different meanings into a single fuzzy cost. It is demonstrated in this paper that it may sometimes lead to inconsistencies. We propose another approach, based on decision theory with possibility measurement of uncertainty. [Copyright &y& Elsevier]

Abstract: The fuzzy version of group model of traffic flow in street networks is presented. At first definitions of vehicles groups and its elementary transformations are introduced. Then the generic transformer of vehicle groups at an entrance of intersection is derived and network evaluation performed. The introduction of the fuzzy group definition as fuzzy set of similar vehicle groups made possible to extend results have obtained for crisp model to fuzzy one. Vehicle group transformations were generalized to fuzzy environment by law of extension and new formulas for delay were derived. Remarks concerning delay defuzzyfication and advantages of fuzzy group model over crisp one ended the paper. [Copyright &y& Elsevier]

Abstract: This paper describes and discusses the possibilities of steering the transportation planning process in the face of bounded rationality and unbounded uncertainty: (a) through the introduction of the concept of ‘systemicity’; (b) by expanding the spectrum of the existing planning paradigm currently in use; (c) by reducing complexity through the application of tests of adequacy, dependency, suitability, and adaptability; (d) through the introduction of soft systems thinking; and (e) by using ‘abductive’ in addition to deductive and inductive inferencing. It is concluded that the application of these strategies, adjustments, and tests to the existing planning procedure will hopefully enrich and strengthen our planning effort and make it more robust. [Copyright &y& Elsevier]