Traffic signals may generate bottlenecks due to an unfair timing balance. Facing this problem, adaptive traffic signal controllers have been proposed to compute the phase durations according to conditions monitored from on-road sensors. However, high hardware requirements, as well as complex setups, make the majority of these approaches infeasible for most cities. This paper proposes an adaptive traffic signal fuzzy-logic controller which uses the flow rate, retrieved from simple traffic counters, as a unique input requirement. The controller dynamically computes the cycle duration according to the arrival flow rates, executing a fuzzy inference system guided by the reasoning: the higher the traffic flow, the longer the cycle length. The computed cycle is split into different phases proportionally to the arrival flow rates according to Webster’s method for signalization. Consequently, the controller only requires determining minimum/maximum flow rates and cycle lengths to establish if–then mappings, allowing the reduction of technical requirements and computational overhead. The controller was tested through a microsimulation model of a real isolated intersection, which was calibrated with data collected from a six-month traffic study. Results revealed that the proposed controller with fewer input requirements and lower computational costs has a competitive performance compared to the best and most used approaches, being a feasible solution for many cities.

Traffic emission is one of the most severe issues in our modern societies. A large part of emissions occurs in cities and especially at intersections due to the high interactions between vehicles. In this paper, we proposed a cellular automata model to investigate the different traffic emissions (CO${}_2$, PM, VOC, and NO${}_x$) and speeds at a two-lane signalized intersection. The model is designed to analyze the effects of signalization by isolating the parameters involved in vehicle-vehicle interactions (lane changing, speed, density, and traffic heterogeneity). It was found that the traffic emission increases (decreases) with the increasing of green lights duration ($T_g$) at low (high) values of vehicles injection rate ($\alpha$). Moreover, by taking CO${}_2$ as the order parameter, the phase diagram shows that the system can be in four different phases (I, II, III, and IV) depending on $\alpha$ and $T_g$. The transition from phase II (I) to phase III (II) is second order, while the transition from phase II to phase IV is first order. To reduce the traffic emission and enhance the speed, two strategies were proposed. Simulation results show a maximum reduction of 13.6% in vehicles’ emissions and an increase of 9.5% in the mean speed when adopting self-organizing intersection (second strategy) at low and intermediate $\alpha$. However, the first strategy enhances the mean speed up to 28.8% and reduces the traffic emissions by 3.6% at high $\alpha$. Therefore, the combination of both strategies is recommended to promote the traffic efficiency in all traffic states. Finally, the model results illustrate that the system shows low traffic emission adopting symmetric lane-changing rules than asymmetric rules.

Unsignalized mid-block raised crosswalks have been adopted as inclusive transport strategies, providing humps to reduce vehicles’ speed to promote drivers to yield to pedestrians. The interaction between vehicles and pedestrians can induce local jams that can merge to become a gridlock. The purpose of this paper is to investigate the interaction between vehicles and the mid-block raised crosswalk, analyzing its effects on traffic flow, instantaneous CO${}_2$ emissions, and energy dissipation. A pedestrian–vehicle cellular automata model was developed, where a single-lane road with a mid-block raised crosswalk is considered. The lane boundaries were controlled with the injections rate ($\alpha$) and extraction rate ($\beta$), while the pedestrians’ entrance was controlled with the rate (${\alpha }_p$). The system’s phase diagram was constructed, identifying four phases: maximum current, jamming, congestion, and gridlock. All observed phase transitions are of the second order. The transition from maximum current (or jamming) phase to gridlock phase is not noticed. Moreover, since the crosswalk is a bottleneck, the gridlock phase takes place when the pedestrians’ influx exceeds a critical value (${\alpha }_p$ > 0.8). The study also revealed that the crosswalk is the main precursor of energy dissipation and CO${}_2$ emissions, whose major effects are observed during the jamming phase.

An autonomic distributed system is composed of geographically distributed autonomic components. One open challenge in autonomic computing is the efficient monitoring at runtime oriented towards the collection of information, from which the system itself will detect, diagnose, and repair problems that result from failures in software and/or hardware components. For this purpose, communication-induced checkpointing (CIC) can be a useful tool. CIC aims to form global consistent snapshots from which the system can recover. To achieve this, CIC solutions monitor exchanged information among the processes to identify dangerous checkpointing patterns. When a dangerous pattern is identified, it is broken by locally triggering a forced checkpoint. Nevertheless, not all triggered forced checkpoints are necessary. In this paper, we present a delayed CIC approach that reduces forced checkpoints by using triggering rules called safe checkpoint conditions. Finally, we present simulation results that show that our proposal is more efficient than other current solutions.

Mobile distributed systems (MDS) deal with data transmissions among geographically distributed mobile sources. In this environment, the preservation of temporal dependencies among exchanged real-time multimedia data is mainly affected the asynchronous transmissions, by constant topology changes, unpredictable delays, as well as the lack of global memory and clock. Existing solutions for distributed intermedia synchronization are based on the assumption of a homogeneous end-to-end system, where symmetrical unbounded overhead cannot affect the throughput. This assumption, however, is not feasible for MDS due to the constraints of the wireless medium and the mobility implications. This paper presents a distributed multimedia synchronization protocol oriented to satisfy logical and temporal dependencies in the exchange of real-time data in MDS by using logical mapping, avoiding the use of global references. Two main aspects of the protocol include the computation of the deadline for messages by using only relative time points and by dividing the processing stage to achieve synchronization with an asymmetric principle of design. With the simulations results we demonstrate that our protocol is effective in diminishing the synchronization error. Furthermore, the protocol is efficient as regards processing and storage costs at the mobile hosts, and in the overhead attached per message with a reduced usage of bandwidth across the wired and wireless channels in comparison with the Real-time Transport Protocol (RTP).