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Connected and autonomous driving technologies offer a novel solution for intersection control optimization. Connected and autonomous vehicles (CAVs) can access signal plans and optimize trajectories to minimize delays and reduce fuel consumption. However, optimizing trajectories for individual vehicles significantly increases complexity, especially for joint optimization of traffic signals and vehicle trajectories. Given the current technical, regulatory, and policy constraints, a superior intersection management approach is necessary before fully automated driving is achieved. This paper introduces an adaptive coupling control (ACC) method based on vehicle platooning to optimize signal timings and vehicle trajectories in mixed traffic. Initially, vehicle platoon segmentation is conducted, led by CAVs. The study then proposes a single‐layer coupled optimization model based on vehicle platoons, simplifying the joint optimization model. To address logistic constraint difficulties, a linearization of the coupled model (LCM) method is developed. Numerical experiments demonstrate that the ACC method significantly reduces vehicle delay and fuel consumption. At high CAV penetration rates (0.8 < R <1) and high traffic volumes (over 900 pcu/h), vehicle platoon control delivers excellent performance, with delays and fuel consumption even lower than in a fully automated environment (R = 1). This surprising result suggests that the mixed platoon system (ACC method) positively impacts mixed traffic. [ABSTRACT FROM AUTHOR]

Efficient traffic flow management at intersections is vital for optimizing urban transportation networks. This paper presents a comprehensive approach to refining traffic flow by analyzing the capacity of roads and integrating fuzzy logic-based traffic light control systems. We examined the capacity of roads connecting intersections, considering factors such as road vehicle capacity, vehicle speed, and traffic flow volume, through detailed mathematical modeling and analysis. Control is determined by the maximum capacity of each road segment, providing valuable insights into traffic flow dynamics. Building upon this capacity and flow analysis, the research introduces a novel intelligent traffic light controller (ITLC) system based on fuzzy logic principles. By incorporating real-time traffic data and leveraging fuzzy logic algorithms, our ITLC system dynamically adjusts traffic light timings to optimize vehicle flow at two intersections. The paper discusses the design and implementation of the ITLC system, highlighting its adaptive capabilities in response to changing traffic conditions. Simulation results demonstrate the effectiveness of the ITLC system in improving traffic flow and reducing congestion at intersections. Furthermore, this research provides an analysis of the mathematical models used to calculate road capacity, offering insights into the underlying principles of traffic flow optimization. Through the simulation, we have validated the accuracy and reliability of our controller. [ABSTRACT FROM AUTHOR]

The article offers information on the Dominican government's presentation of the Santo Domingo Integrated Transportation System (SIT-SD), a project addressing traffic congestion and mobility issues in the capital city, with an estimated investment of 3.2 billion dollars. Topics include the initiative's focus on reducing private vehicle traffic and promoting collective transportation by connecting the entire metropolitan region of Greater Santo Domingo through a public-private partnership model.

The aim of this manuscript is to detect recent trends in air transport research through a bibliometric analysis. We retrieved all articles published between 2013 and 2022 in the Q1 of the Transportation ranking of the Social Sciences Citation Index published in the Journal Citations Reports (Q1-T), and in the Journal of Air Transport Management. Among these records, we retained for the analysis the articles related to air transport. Analyzing the author keywords of articles and retaining the Top 10 cited articles in each of the samples, we identified six research topics for each of the samples. Both samples share the topics of Industry Analysis, Air Traffic Management and COVID-19 and Air Transport. The specific topics of Q1-T sample are High Speed Rail and Air Transport, Environmental Impact of Air Transport and UAV and Urban Air Mobility. We also found that materials of Q1-T are mainly written from the regulator perspective, and JATM materials from the perspective of airport and airline managers. We believe that these results are useful for administrators evaluating air transport academics, and air transport academics themselves looking for new avenues of research and stakeholders of the air transport industry interested in evidence-based decision making. [ABSTRACT FROM AUTHOR]

The use of the Internet of things (IoT) devices is growing rapidly in the current industrial market. Integrating these devices into the network system has subjected the information to Cybersecurity attacks putting the market of IoT technology at risk. As a result, accurate protection algorithms and efficient monitoring systems need to be developed. This paper proposes a new framework design relays on a stochastic measurement of determining parameters based on a novel adaptive deep learning (ADL) algorithm for industrial manufacturing such as transportation, energy. The new framework will be designed to incorporate an element of randomness as opposed to deterministic frameworks. The implemented method considered the network forensic systems and intrusion detection (ID); therefore, the prediction model is set up to alert the administrator about the system status. The framework is proposed based on five prioritized protection stages. The developed model tested on the Bot-IoT dataset, which is well-structured and valid for training, as confirmed by literature. The result has shown the ability to simulate the IoT network traffic along with risk assessment against different types of attacks by using the ADL algorithm. The new framework will be designed to improve computational efficiency by being able to adjust their structure based on the inputs. The research contributions are that it will help in the development of an algorithm which can minimize traffic accidents, improve traffic flow, minimize energy wastes, and save costs of controlling traffic flow. Findings show that using this new algorithm has 100% accuracy, which makes it an excellent choice for the detection of threats and errors. [ABSTRACT FROM AUTHOR]

Connected and automated vehicles (CAVs) and regular human-piloted vehicles (RVs) will coexist in the near future. Research has indicated the feasibility of using CAVs to stabilize traffic flow and eliminate stop-and-go waves. In light of this, we develop distributed control schemes to stabilize mixed vehicular platoons by using CAV as the leading vehicle. We address several challenges, such as limited information perception capabilities of RVs, the uncertain actuation of human drivers, and external disturbances. Only local information from the preceding vehicle is used in the controllers. Modifications of the input-to-state string stability (ISSS) are established to cope with the uncertainty and disturbance characteristics while conditions for stability are derived. The proposed control schemes can attenuate the effect of disturbances while maintaining the ISSS property. The relationships between ISSS and other string stability concepts are clarified. Finally, numerical experiments are conducted to validate the effectiveness of the proposed platoon control schemes. [ABSTRACT FROM AUTHOR]

This paper proposes a framework of signalized corridor management with vehicle platooning and trajectory control (SCoPTO) using connected automated vehicle (CAV) technologies. In this framework, the major road platoons can request green time extensions when arriving at the downstream intersections to reduce unnecessary stops. The vehicular trajectories of CAVs can also be optimized to maximize the utilization of the green time and reduce the start-up lost time. CAV platooning operation is implemented such that CAVs can pass the intersection efficiently to potentially increase green time utilization and improve traffic stability. Simulations are performed in a realistic signalized corridor with three intersections, and the results show that the proposed SCoPTO framework can significantly improve the throughput and reduce the average delay across different CAV penetration rates. This study provides insights for traffic management centers to use SCoPTO for future urban signalized corridor management. [ABSTRACT FROM AUTHOR]

When multiple equilibria exist, the desired traffic equilibrium, may not be reached through a day-to-day dynamic adjustment process. Han et al. ["Discrete-Time Day-to-Day Dynamic Congestion Pricing Scheme Considering Multiple Equilibria." Transportation Research Part B: Methodological 104: 1–16.] proposed a day-to-day dynamic pricing scheme charged on all links to ensure the desired traffic equilibrium can be achieved even when multiple equilibria exist. However, due to many practical constraints, the second-best pricing scheme has more practical interests. This study first discussed the issues of existing congestion pricing schemes for second-best case. Then, this study developed a second-best dynamic road pricing scheme that is implemented on a dynamic subset of the road links in the network. Our rigorous theoretical proof and numerical tests prove that the dynamic pricing scheme can drive the traffic state evolution towards the desired second-best traffic user equilibrium state from any initial traffic state. [ABSTRACT FROM AUTHOR]

We investigate the problem of controller design after linearization around the steady-state solutions of second-order traffic models. At steady-state the traffic variables follow space-dependent autonomous ODEs. The steady-state solutions can be used to account for the heterogeneity of the road in space, which can be caused by different environmental factors. Proceeding by analogy with open-channel flow studies, where such states are relevant for operating a network with efficient control strategies, we analyse and compare steady-state solutions for different second-order traffic models. We show that the steady-state density profile remains in three different regions. The behaviour of the considered models is discussed, leading to proposed corrections of the models. We select one corrected model, which we use for the design and implementation of a boundary controller to illustrate the effectiveness of our approach. [ABSTRACT FROM AUTHOR]

A promising methodology is proposed to estimate reliable annual average daily traffic (AADT) volumes for no-surveyed road sections using probe volumes collected by a vehicle global positioning system (GPS). This research was inspired by the obvious concept that probe counts are a direct portion of AADT from the viewpoint of vehicle trip behavior. The method converts the probe volume of target road section to AADT using the nonlinear relationship between geographical neighborhoods composed of observed AADT volumes and annual average daily probe volumes. The relationship is determined with a locally weighted power-curve model. A feasibility of the proposed method was demonstrated through a case study using real-world data. Analysis results show that the proposed method is a practical and cost-effective way to estimate reliable AADT for unmeasured road segments. This indicates that there exists a strong relationship between AADT values and vehicle-GPS probe values from the trip characteristics of a road network. [ABSTRACT FROM AUTHOR]

Highlights • Model heterogeneous flows in the interdependent infrastructure system. • Consider partial capacity losses under facility disruption risks. • Formulate a non-linear integer programming model for the studied problem. • Draw insights into the features of the proposed model with numerical examples. • Reveal managerial insights into optimal location design and facility improvement. Abstract Due to the interdependency between multiple infrastructure systems, the performance of a facility may depend on the resources or supplies received from other facilities. However, cross-system interdependence has seldom been studied in the location design context, probably due to the lack of a concise model describing interdependence across heterogeneous systems. This paper proposes a new heterogeneous flow scheme to describe cross-system interdependence. This scheme has two features distinguished from existing models in describing an interdependent facility location problem. First, it is a simple linear model upon which a compact facility location model can be built. Secondly, it relaxes the need to maintain flow conservation between different systems and is suitable in describing heterogeneous systems that take in and output different resources or services. Built on this scheme, this paper proposes a reliable location design model for a nexus of interdependent infrastructure systems. This model aims to locate the optimal facility locations in multiple heterogeneous systems to balance the tradeoff between the facility investment and the expected nexus operation performance. Different from other reliable facility location models, this expected performance captures interdependence among heterogeneous systems due to the resource input-output relationships. The consideration of continuous partial capacity losses complements the reliable location literature that mainly focuses on binary disruptions. Two numerical examples are conducted for investigating features and applications of the proposed model. The results indicate that with a standard off-the-shelf integer programming solver, the proposed model is able to solve optimal facility location design for problem instances of realistic scales to the near-optimum solutions with optimality gap assurance. Sensitivity analyses of key parameters indicate that improving facility capacity and reducing interdependency between systems can mitigate impacts of facility capacity losses and reduce the overall system cost. [ABSTRACT FROM AUTHOR]

Highlights • Estimating historical traffic volumes between sparsely-located traffic sensors is addressed. • Neural network yields 24% more accurate results than the state of the practice approach. • Value of vehicle probe data in estimating historical traffic volumes is quantified. Abstract This paper focuses on the problem of estimating historical traffic volumes between sparsely-located traffic sensors, which transportation agencies need to accurately compute statewide performance measures. To this end, the paper examines applications of vehicle probe data, automatic traffic recorder counts, and neural network models to estimate hourly volumes in the Maryland highway network, and proposes a novel approach that combines neural networks with an existing profiling method. On average, the proposed approach yields 24% more accurate estimates than volume profiles, which are currently used by transportation agencies across the US to compute statewide performance measures. The paper also quantifies the value of using vehicle probe data in estimating hourly traffic volumes, which provides important managerial insights to transportation agencies interested in acquiring this type of data. For example, results show that volumes can be estimated with a mean absolute percent error of about 21% at locations where average number of observed probes is between 30 and 47 vehicles/h, which provides a useful guideline for assessing the value of probe vehicle data from different vendors. [ABSTRACT FROM AUTHOR]

Abstract We study different mixes of private and public supply of roads in a network with bottleneck congestion and heterogeneous users. There are two parallel links for one origin and destination pair and two groups of travellers, where the group with the higher value of time also has higher schedule delay values. Previous scholars argued that as users become more heterogeneous, they benefit more from product differentiation, making private supply of roads more efficient. However, we find that local monopoly power might also increase if there is a 'separating equilibrium', which is an equilibrium where at least one group only uses one private road due to the different combinations of toll and congestion of the two roads. The private road can thus increase its toll without worrying about the competition from the other road for this group: it has a local monopoly over them. This lowers the efficiency of private supply. The problem is especially severe with flat tolls, which are constant over the peak. With fine tolls – which vary continuously over the day – there tends to be a pooling equilibrium – where both types use both roads – and competition remains intense. Flat tolling is also worse for users than fine tolling, as it has higher generalized prices. [ABSTRACT FROM AUTHOR]

The traffic during rush hour in metropolises is always in heavy congestion, so the wagon trucks of logistic transportation are mostly forbidden during rush hour. In fact, quite a few logistic transportations are fulfilled by converted passenger vehicles. This paper aims to model the logistic companies' behaviors and see through the effect of their cooperation modes on the companies and on the whole traffic conditions. The logistic companies decide their transportation pricing, warehouse using and route choosing separately or as a group (cooperation) to compete with others. It is also assumed that the heavy freight vehicles, light freight vehicles and the auto vehicles share the same network. Three models based on variational inequalities are proposed to describe the companies' behaviors when there is no cooperation, simple cooperation and deep cooperation, respectively, and the modified diagonalization method is used to solve these models. The total transportation demand is elastic, which depends on the users' choice of logistics company and further depends on all the companies' prices, warehouse and route choices. The goodness of different coalitions to the companies and the whole traffic system is well investigated in the numerical examples. [ABSTRACT FROM AUTHOR]

Abstract Uniqueness of the dynamic user-equilibrium assignment is still an important issue. This paper proves uniqueness with a milder condition compared to past studies and shows another counterexample to the uniqueness. A unidirectional network , in which any node on any shortest route has a unique node potential, is introduced. Orders of vehicles are determined by this node potential so that, given any two vehicles passing through the same node, the lower potential vehicle arrives at the node before the higher potential vehicle. It is shown that, for a unidirectional network in equilibrium, the link travel times and traffic volumes of congested links are uniquely determined. Moreover, a simple non-unidirectional network having multiple equilibria is introduced. This example exhibits importance of unidirectional-network structure to prove uniqueness. [ABSTRACT FROM AUTHOR]

Public transport (PT) disruption can occur due to various factors such as malfunctions and breakdowns of vehicles, power outages, and personnel strikes. This paper explores the network-wide impacts of PT strikes (train, tram, and bus strikes) on traffic congestion in Melbourne, Australia using a network modeling approach. A primary survey aimed to investigate the mode shift of users when each public transport mode ceases was conducted with 648 public transport users in May 2016. Findings show that train withdrawal was expected to result in 43% of users shifting to car. Smaller yet significant shifts to car was also expected with bus withdrawal (34%) and tram withdrawal (17%). Based on the survey results and the use of a four-step transport model, train withdrawal was expected to increase the number of severely congested road links by 130% and reduce the average travel speed from 48 km/h to 39 km/h (20% decrease). Bus and tram withdrawal was also found to increase congestion although the result was less severe. Future research should investigate the switching behavior in actual withdrawal events and explore the long-term effects of public transport withdrawal. [ABSTRACT FROM AUTHOR]

Public transit systems with efficient designs and operating plans can reduce both total costs and greenhouse gas (GHG) emissions. Total costs are a sum of user cost and agency cost. In previous work, we explored in various hypothetical city scenarios possible tradeoffs between GHG emissions and total costs for optimally designed transit systems. However, most current transit systems were not designed to minimize total costs. This study aims at finding the potential emission impact when optimizing the total costs of such a system, the MUNI bus network for the city of San Francisco. The continuum approximation (CA) method is used to obtain a stylized representation of the network. Total costs and emissions are derived as functions of system attributes such as headways and spacing. We analyze the optimal total costs and emissions and the corresponding attributes. Our result shows that a significant reduction in GHG emissions is achieved when total costs are reduced simultaneously. The cost-optimal MUNI bus system has a total cost of 0.15 billion $/year and emits 1 680 metric tons of greenhouse gases. These figures amount to about half of the cost and a third of the emissions in the current MUNI bus system. The optimal system has a lower spatial availability but a higher temporal availability of bus service than the current system, which highlights the potential benefits of providing more frequent express bus services. [ABSTRACT FROM AUTHOR]

Bike-sharing systems have rapidly expanded around the world in recent years. However, bike-sharing research focusing on East Asia is limited. The impacts of bike-sharing on travelers’ usage of other transport modes in an integrated transportation system remain unclear. This study develops a spatial Agent-based model to simulate the use of bike-sharing services and other transport modes in Taipei city, considering their interactions through the modeling of the modal split based on the heterogeneous mode choice behaviors of travelers. Two scenarios are proposed for the development of a bike-sharing system: 1) bike infrastructure extensions; and 2) bike-sharing incentives. Two scenarios are evaluated along with the corresponding environmental and social impacts. The simulation results indicate that free use of bike-sharing to connect the transit system can be most sustainable with 1.5 million US dollars in transportation damage cost saved per year, and 22 premature deaths further prevented per year due to mode shift to cycling and walking based on the business as usual (BAU) scenario. However, bike-sharing has limited influence on the use of motorcycles, which is nearly invariable. This model can be a powerful tool to help policy-makers improve the sustainability of a multi-modal transportation system with bike-sharing. [ABSTRACT FROM AUTHOR]

Most of the previous studies on dynamic traffic assignment are based on traditional analytical framework, for instance, the idea of Dynamic User Equilibrium has been widely used in depicting both the route choice and the departure time choice. However, some recent studies have demonstrated that the dynamic traffic flow assignment largely depends on travelers’ rationality degree, travelers’ heterogeneity and what the traffic information the travelers have. In this paper, we develop a new self-adaptive multi agent model to depict travelers’ behavior in Dynamic Traffic Assignment. We use Cumulative Prospect Theory with heterogeneous reference points to illustrate travelers’ bounded rationality. We use reinforcement-learning model to depict travelers’ route and departure time choosing behavior under the condition of imperfect information. We design the evolution rule of travelers’ expected arrival time and the algorithm of traffic flow assignment. Compared with the traditional model, the self-adaptive multi agent model we proposed in this paper can effectively help travelers avoid the rush hour. Finally, we report and analyze the effect of travelers’ group behavior on the transportation system, and give some insights into the relation between travelers’ group behavior and the performance of transportation system. [ABSTRACT FROM AUTHOR]

Cities around the world are inundated by cars and suffer traffic congestion that results in excess delays, reduced safety and environmental pollution. The interplay between road infrastructure and travel choices defines the level and the spatio-temporal extent of congestion. Given the existing infrastructure, understanding how the route choice decisions are made and how travellers interact with each other is a crucial first step in mitigating traffic congestion. This is a problem with fundamental importance, as it has implications for other limited supply systems where agents compete for resources and reach an equilibrium. Here, we observe the route choice decisions and the traffic conditions through an extensive data set of GPS trajectories. We compare the actual paths followed by travellers to those implied by equilibrium conditions (i) at a microscopic scale, where we focus on individual path similarities, and (ii) at a macroscopic scale, where we perform network-level comparison of the traffic loads. We present that non-cooperative or selfish equilibrium replicates the actual traffic (to a certain extent) at the macroscopic scale, while the majority of individual decisions cannot be reproduced by neither selfish nor cooperative equilibrium models. [ABSTRACT FROM AUTHOR]

Contemporary traffic engineering relies on effective management of transportation infrastructure to supply the variable mobility demands. Urban arterial congestion is a recurring problem that affects urban traffic flow. The degree of congestion may amplify if the arterial is a principal arterial that leads to a major bridge. Bosporus Bridge, inaugurated in 1973 and renamed in July 2016 as the Martyrs Bridge, is the first of the three suspension bridges connecting the Anatolian and European sides of Istanbul, Turkey. The Martyrs Bridge, along with the recently inaugurated Eurasia Roadway Tunnel provides a direct connection between the southern districts of the Anatolian and European sides of Istanbul for roadway traffic excluding trucks. Recurring congestion observed along the 5·7 km long westbound approach arterial from the Anatolian side of Istanbul to the bridge initiated a study to investigate methods to mitigate congestion through traffic management and improved roadway parameters. A micro simulation model based on traffic data suggested the applicability of traffic speed management along the existing infrastructure to relieve congestion and provide flow stability. The micro simulation model also provided the means for parametric evaluation of the effects of heavy vehicles, lane-width values and interchange spacing on the arterial flow speed and delay. [ABSTRACT FROM AUTHOR]

The variable speed limit (VSL) is a control instrument of emerging intelligent transportation systems used to help manage motorway traffic. The VSL has the potential to improve traffic safety and reduce both traffic congestion and emissions through better harmonisation of traffic flow. The VSL results in a reduction of speed variations among vehicles travelling along controlled sections. In this paper, a modified logic-tree-based algorithm is proposed to improve the mobility benefits of VSL controllers. The modified algorithm is assessed using a case study in Auckland, New Zealand. Analysis of the case study is based on a critical bottleneck section of the Auckland motorway using the Aimsun micro-simulator. The proposed algorithm is compared with a known algorithm proposed in the literature and used in practice. The simulation results of the case study show that the proposed logic-tree-based VSL control algorithm outperforms the existing method. Compared with a no-control scenario, it results in respective improvements of 6%, 11%, 3%, 9% and 3% in the capacity of the bottleneck section, the total travel time and emissions of carbon dioxide, carbon monoxide and nitrogen oxides. [ABSTRACT FROM AUTHOR]

Urban transportation systems are vulnerable to congestion, accidents, weather, special events, and other costly delays. Whereas typical policy responses prioritize reduction of delays under normal conditions to improve the efficiency of urban road systems, analytic support for investments that improve resilience (defined as system recovery from additional disruptions) is still scarce. In this effort, we represent paved roads as a transportation network by mapping intersections to nodes and road segments between the intersections to links. We built road networks for 40 of the urban areas defined by the U.S. Census Bureau. We developed and calibrated a model to evaluate traffic delays using link loads. The loads may be regarded as traffic-based centrality measures, estimating the number of individuals using corresponding road segments. Efficiency was estimated as the average annual delay per peak-period auto commuter, and modeled results were found to be close to observed data, with the notable exception of New York City. Resilience was estimated as the change in efficiency resulting from roadway disruptions and was found to vary between cities, with increased delays due to a 5% random loss of road linkages ranging from 9.5% in Los Angeles to 56.0% in San Francisco. The results demonstrate that many urban road systems that operate inefficiently under normal conditions are nevertheless resilient to disruption, whereas some more efficient cities are more fragile. The implication is that resilience, not just efficiency, should be considered explicitly in roadway project selection and justify investment opportunities related to disaster and other disruptions. [ABSTRACT FROM AUTHOR]

In order for the world to stay within the safety threshold of a 2°C increase in average temperature agreed by virtually all governments, the transport sector needs to be decarbonized. The two main obstacles that have prevented this from happening have been the absence of a global legally binding deal and the high relative cost of clean vehicle/energy technologies. The Paris Agreement, which commits countries to reductions of GHG emissions, has virtually solved the first problem and paved the way for countries to implement environmental taxes and subsidies in order to change the relative costs of clean alternatives, which would solve the second problem. These policy actions combined with investment in clean infrastructure and regulation can decarbonize the transport sector. [ABSTRACT FROM AUTHOR]

The primary objective of the study was to identify the factors that influenced the comfort perception of e-bike, e-scooter and bicycle riders in mid-block bicycle lanes on urban streets and to estimate the bicycle level of service (BLOS) of a mid-block bicycle lane with mixed two-wheeled traffic. Data were collected at thirty locations on thirty different streets in Nanjing area in China. Pearson’s Chi-square tests were conducted to make comparisons of the comfort perception among different cyclist groups. The factors that significantly affected the comfort perception of the cyclists included the age of the cyclists, the type of two-wheeled vehicles, the volume of two-wheeled vehicles, the width of mid-block bicycle lanes, the proportions of e-bikes and e-scooters in two-wheeled vehicles, the physical separation between motorized, bicycle and pedestrian lanes, the slope of bicycle lanes, the roadside access points and the roadside land use. Ordered probit models were developed to quantitatively evaluate the impacts of different contributing factors on the comfort perception of the riders of e-bikes, e-scooters and bicycles. The results showed that compared to the riders of bicycles, the riders of e-bikes and e-scooters were more likely to perceive a poor comfort level. The comfort perception of the cyclists increased with an increase in the width of the mid-block bicycle lane, whereas it decreased with an increase in the volume of two-wheeled vehicles. The proportions of e-bikes and e-scooters in two-wheeled vehicles negatively affected the comfort perception of the cyclists. In addition, the presence of physical separation between the motorized, bicycle and pedestrian lanes significantly increased the comfort perception of the cyclists. With the comfort perception models, a procedure was developed and insights were gained to help transportation professionals estimate the BLOS of a mid-block bicycle lane with mixed two-wheeled traffic. [ABSTRACT FROM AUTHOR]

To deal with the conflicts between left-turn and through traffic streams and increase the discharge capacity, this paper addresses the pre-signal which is implemented at a signalized intersection. Such an intersection with pre-signal is termed as a tandem intersection. For the tandem intersection, phase swap sorting strategy is deemed as the most effective phasing scheme in view of some exclusive merits, such as easier compliance of drivers, and shorter sorting area. However, a major limitation of the phase swap sorting strategy is not considered in previous studies: if one or more vehicle is left at the sorting area after the signal light turns to red, the capacity of the approach would be dramatically dropped. Besides, previous signal control studies deal with a fixed timing plan that is not adaptive with the fluctuation of traffic flows. Therefore, to cope with these two gaps, this paper firstly takes an in-depth analysis of the traffic flow operations at the tandem intersection. Secondly, three groups of loop detectors are placed to obtain the real-time vehicle information for adaptive signalization. The lane selection behavior in the sorting area is considered to set the green time for intersection signals. With the objective of minimizing the vehicle delay, the signal control parameters are then optimized based on a dynamic programming method. Finally, numerical experiments show that average vehicle delay and maximum queue length can be reduced under all scenarios. [ABSTRACT FROM AUTHOR]

The primary purpose of the speed limit system is to enforce reasonable and safe speed. To reduce secondary problems such as accidents and queuing, Variable Speed Limits (VSL) has been suggested. In this paper VSL is used to better safety and traffic parameters. Traffic parameters including speed, queue length and stopping time have been pondering. For VLS, an optimization decision tree algorithm with the function of microscopic simulation was used. The results in case of sub saturated, saturated and supersaturated at a bottleneck are examined and compared with the Allaby logic tree. The results show that the proposed decision tree shows an improved performance in terms of safety and comfort along the highway. The VSL pilot project is part of the Road Safety Improvement Program included in Iran's road safety action plan that is in the research process in the BHRC Research Institute, Road and Housing & Urban Development Research that is planned for next 10-year Transportation safety view Plan. [ABSTRACT FROM AUTHOR]

The article presents a case study of the saturation flow rate difference between the default values in North Carolina and the sufficiency of the used saturation flow rates in the state's most basic signalized intersection capacity.

Increasing the intensity of transport traffic, changing in restructuring and high-speed modes of transport flows more stringent requirements for controls and traffic management impose to ensure the necessary level of efficiency and safety of the transport traffic. To resolve this problem, it is necessary to build road network optimal in length, density and on transport performance indicators. Aim: The aim of the study is to evaluate the workload and analysis of capacity of the road network of modern regional center. Materials and Methods: All studies and calculations in paper, the authors conducted on the example of the road network of the Primorsky district of Odessa (Ukraine). Few streets that are transit arteries of the historic center were chosen to assess the road network capacity. On these streets the movement to the main passenger and transport creating unit - Railway Station is happening. To assess the capacity of the considered road network the methods of field observations were used, because they are based on direct measurements of traffic characteristics in different parts of the road network. Results: The study gave an objective picture of important correspondences. An assessment of degree of loading the considered road network was made; for that the capacity of multilane roadway was calculated. Analysis of the data showed that the state of traffic in the study area is densely saturated. It was made the recommendation for improvement of traffic of modern regional center. [ABSTRACT FROM AUTHOR]

Traffic equilibrium models are fundamental to the analysis of transportation systems. The stochastic user equilibrium (SUE) model which relaxes the perfect information assumption of the deterministic user equilibrium is one such model. The aim of this paper is to develop a new user equilibrium model, namely the MDM-SUE model, that uses the marginal distribution model (MDM) as the underlying route choice model. In this choice model, the marginal distributions of the path utilities are specified but the joint distribution is not. By focusing on the joint distribution that maximizes expected utility, we show that MDM-SUE exists and is unique under mild assumptions on the marginal distributions. We develop a convex optimization formulation for the MDM-SUE. For specific choices of marginal distributions, the MDM-SUE model recreates the optimization formulation of logit SUE and weibit SUE. Moreover, the model is flexible since it can capture perception variance scaling at the route level and allows for modeling different user preferences by allowing for skewed distributions and heavy tailed distributions. The model can also be generalized to incorporate bounded support distributions and discrete distributions which allows to distinguish between used and unused routes within the SUE framework. We adapt the method of successive averages to develop an efficient approach to compute MDM-SUE traffic flows. In our numerical experiments, we test the ability of MDM-SUE to relax the assumption that the error terms are independently and identically distributed random variables as in the logit models and study the additional modeling flexibility that MDM-SUE provides on small-sized networks as well as on the large network of the city of Winnipeg. The results indicate that the model provides both modeling flexibility and computational tractability in traffic equilibrium. [ABSTRACT FROM AUTHOR]

With the rapid development of transportation, traffic questions have become the major issue for social, economic and environmental aspects. Especially, during serious emergencies, it is very important to alleviate road traffic congestion and improve the efficiency of evacuation to reduce casualties, and addressing these problems has been a major task for the agencies responsible in recent decades. Advanced road guidance strategies have been developed for homogeneous traffic flows, or to reduce traffic congestion and enhance the road capacity in a symmetric two-route scenario. However, feedback strategies have rarely been considered for pedestrian-vehicle mixed traffic flows with variable velocities and sizes in an asymmetric multi-route traffic system, which is a common phenomenon in many developing countries. In this study, we propose a weighted road occupancy feedback strategy (WROFS) for pedestrian-vehicle mixed traffic flows, which considers the system equilibrium to ease traffic congestion. In order to more realistic simulating the behavior of mixed traffic objects, the paper adopted a refined and dynamic cellular automaton model (RDPV_CA model) as the update mechanism for pedestrian-vehicle mixed traffic flow. Moreover, a bounded rational threshold control was introduced into the feedback strategy to avoid some negative effect of delayed information and reduce. Based on comparisons with the two previously proposed strategies, the simulation results obtained in a pedestrian-vehicle traffic flow scenario demonstrated that the proposed strategy with a bounded rational threshold was more effective and system equilibrium, system stability were reached. [ABSTRACT FROM AUTHOR]

This paper provides an overview on the ACROSSEE project (funded by the ERDF under the SEE program), its objectives, general methodology, and the main results. Moreover, the main survey results are presented as they relate to the Romanian road and rail border-crossing points (BCPs) with the Eastern neighbourly country, Moldavia. Results include the actual status of the road BCP, surveys on exiting and entering traffic flows, answers to specific questionnaires of the truck and car drivers in relation with origin-destination of the trips, average waiting time in queue and time required for procedures and controls. Discussion on the mathematical modelling is presented and a provisional simulation model is developed, using ARENA software. The early results are used in order to introduce the need for future assessment of the transit time in a road BCP, with the main purpose: the substantiation of the strategic and operational actions for improvements in trade and transport crossings of the EU borders, considering the need for more vigilant and less time-consuming checks at the outside borders of the EU. [ABSTRACT FROM AUTHOR]

In this paper, a new car-following model is proposed by considering driver's desired velocity according to Transportation Cyber Physical Systems. The effect of driver's desired velocity on traffic flow has been investigated through linear stability theory and nonlinear reductive perturbation method. The linear stability condition shows that driver's desired velocity effect can enlarge the stable region of traffic flow. From nonlinear analysis, the Burgers equation and mKdV equation are derived to describe the evolution properties of traffic density waves in the stable and unstable regions respectively. Numerical simulation is carried out to verify the analytical results, which reveals that traffic congestion can be suppressed efficiently by taking driver's desired velocity effect into account. [ABSTRACT FROM AUTHOR]

This review discusses some issues related to the use of simulation in transportation analysis. Potential pitfalls are identified and discussed. An overview of some methods relevant to the use of an advanced simulation tool in an optimization context is also provided. [ABSTRACT FROM AUTHOR]

Disasters have substantial negative impacts on the transportation system performance. To be resilient, transportation systems should recover quickly and function effectively after disasters. However, reconstruction of road links has to be implemented as a multistage procedure due to limited budget. Hence, guidance needs to be provided on when and where to reconstruct to maintain high system performance during the recovery period. This article proposes a novel multi-stage network design model for identifying the optimal reconstruction sequence that maximizes the resilience of transportation networks with budget constraints. To achieve this, resilience is quantified as the sum of the recovery ratios of system performance during reconstruction. A day-to-day traffic assignment model and a logit-based loading model are integrated to describe the traffic flow evolution during reconstruction. The model is implemented on two test transportation networks. The results show that the optimal reconstruction sequence leads to the most significant improvement in postdisaster performance. Stability analysis indicates that effective traffic control strategies are necessary to ensure the flow stability during reconstruction. [ABSTRACT FROM AUTHOR]

The evacuation operations problem aims to avoid or mitigate the potential loss of life in a region threatened or affected by a disaster. It is shaped to a large extent by the evolution of evacuation traffic resulting from the demand–supply interactions of the associated transportation network. Information-based control is a strategic tool for evacuation traffic operations as it can enable greater access to the affected population and more effective response. However, comparatively few studies have focused on the implementation of information-based control in evacuation operations. This study develops a control module for evacuation operations centered on addressing the demand–supply interactions by using behavior-consistent information strategies. These strategies incorporate the likely responses of evacuees to the information provided in the determination of route guidance information. The control module works as an iterative computational process involving an evacuee route choice model and a control model of information strategies to determine the route guidance information to direct evacuation traffic so as to approach a desired network traffic flow pattern. The problem is formulated as a fuzzy logic based optimization framework to explicitly incorporate practical concerns related to information dissemination characteristics and social equity in evacuation operations. Numerical experiments highlight the importance of accounting for the demand–supply interactions, as the use of behavior-consistent information strategies can lead evacuee route choices to approach the operator-desired proportions corresponding to the desired traffic pattern. The results also indicate that while a behavior-consistent information strategy can be effective, gaps with the desired route proportions can exist due to the discrete nature of the linguistic messages and the real-world difficulty in accurately modeling evacuees’ actual route choice behavior. [ABSTRACT FROM AUTHOR]