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The paper presents an overview of safety and insights regarding traffic at highway intermediate cross-sections in the interurban highway network. This overview includes rigid and soft 'one plus one' cross-sections, passing lanes traffic and geometric characteristics, as well as criteria for widening a two-lane highway to form a divided multilane highway. The design overview of intermediate highway cross-sections includes traffic and safety warrants, design speed characteristics and cross-section infrastructure components, including elements that enhance traffic safety. These developments are partly an outcome of the new Israeli geometric design policy and controls for rural (interurban) highways. [ABSTRACT FROM AUTHOR]

The freeway system of China is the longest in the world and planned to expand in the following years. However, the safety conditions of freeways are drawing increasing concerns both from the authorities and the public in the country. The safety design and management for freeways are urgently needed considering the current safety situation and great demands of new freeways. The study presented in this paper thoroughly investigated factors affecting safety using detailed data of crashes, traffic characteristics and freeway geometry. A random effects negative binomial (RENB) model was applied to account for spatial variations within groups together with a negative binomial (NB) model. The results indicated a better goodness of fit of RENB model than the NB model. In addition, a good number of factors significantly contributed to crash, such as truck proportion, presence of climbing lane, median barrier offset, curvature and longitudinal grade, were identified. This study was expected to provide a better understanding of how traffic condition and freeway design affect safety and should be useful to freeway engineers to design safe freeways, or develop effective safety countermeasures. [ABSTRACT FROM AUTHOR]

This paper presents an investigation into passing lane length and spacing on two-lane highways. Different combinations of length and spacing were examined under various traffic levels using field data and microscopic traffic simulation. Field data from two side-by-side passing lane study sites in Oregon were used to calibrate and validate the traffic simulation program used in this study. The simulation model was then used to evaluate the effect of different passing lane length and spacing combinations on two-lane highway performance. Study results confirmed the general understanding that using longer and/or more frequent passing lanes yields better operational performance. Moreover, at higher traffic levels, a greater passing lane length, a shorter spacing or both are required to achieve the same improvement in performance. Further, results suggest that passing lane length between 0.75 and 2 miles and spacing between 5 and 15 miles provide the highest effectiveness depending on traffic level. A regression model for performance as a function of traffic flow rate, length and spacing of passing lanes was also developed. [ABSTRACT FROM AUTHOR]

Traffic signals at intersections have a significant effect on traffic emissions. They interrupt traffic flow and create additional acceleration and deceleration driving modes. Therefore, the objective of this paper is to perform the optimization process of vehicle delay and exhaust emissions at isolated signalized intersections. Three-leg intersection located in Kafr El-Sheikh City, Egypt was selected in this study. Field delay times were estimated based on vehicle speed and acceleration profiles using GPS device. On-road measurements of vehicle speeds and emissions were collected simultaneously for all movements of all approaches at the selected intersection. The micro-simulation software VISSIM was used to model and analyze the selected intersection. The model was calibrated and validated using the collected data. Signal timing model was developed for the selected intersection and used for optimization of delay time and vehicle emissions. It was found that the changing of signal timing was effective in improving the operational and environmental performance of the traffic signal under study. Also, the results indicated that when the traffic flow rate is higher, the optimal cycle time corresponding to the performance index function increases. Optimization of the delay times and exhaust emissions gives traffic engineers the option of minimizing vehicle emissions in the designing of the signalized intersections or timing a signal system. [ABSTRACT FROM AUTHOR]

It is well known that pavement distress negatively affects the drivers and passengers of vehicles. Many studies report that foremost among these negative effects is the vibrations that form within the vehicle. Ride comfort depends on the human response to vibration and vehicle response to the road. The goal of this study was to investigate the effect of pavement condition index on ride comfort and to determine the threshold comfort limits for passenger cars on urban asphalt concrete pavements. The pavement condition index (PCI) was determined for pavement sections subject to different surface distress using the PAVER system. Ride (driving) speeds of 20, 30, 40 and 50 km/h were assessed on the same pavement sections to measure vibrational effects inside the vehicle and on the passenger seat. These measurements were then evaluated using the ISO 2631-1 standard in order to determine the a wz values. Using the logistic regression technique, predictive model that took into account linguistic concepts for estimating ride comfort levels based on PCI values was developed. With the aid of this mathematical model, comfort threshold values were determined for each driving speed within an interval of 0-100 PCI. The study results indicated that increasing driving speed was generally associated with higher PCI comfort thresholds. [ABSTRACT FROM AUTHOR]

Previous cellular automata (CA) models have been developed for simulating driver behaviors in response to traffic signal control. However, driver behaviors during traffic signal change intervals, including cross/stop decision and speed adjustment, have not yet been studied. Based on this, this paper aims to propose a change interval CA model for replicating driver’s perception and response to amber light based on stopping probability and speed adjusting functions. The proposed model has been validated by exemplified and field cases. To investigate the applicability of the proposed model, macroscopic and microscopic analyses are conducted. Although the macroscopic fundamental diagram analysis reveals only a small decrease in maximum traffic flow rates with considering driver behaviors in change intervals, in the microscopic analysis, the proposed model can present reasonable vehicular trajectories and deceleration rates during slowdown process. [ABSTRACT FROM AUTHOR]

Enhancing pedestrian safety and improving the design standards of pedestrian facilities at signalized intersection requires a clear understanding of pedestrian delay model and pedestrian crossing behaviours under mixed traffic condition. The existing delay models do not consider the behavioural constrains of pedestrians. This research has been undertaken with the aim of developing a suitable pedestrian delay model for signalized intersection crosswalks, based on considering actual pedestrian crossing behaviours. The required model parameters were extracted from the video-graphic survey conducted for the selected four signalized intersections in Mumbai (India). Crossing behaviours of pedestrians were examined through field data in terms of pedestrian arrival pattern, crossing speed, compliance behaviour and pedestrian-vehicular interactions. Based on pedestrian crossing behaviour analysis results, two new pedestrian delay estimation models were developed and the models were validated by comparing with field and existing model values. The performance level of the proposed models is showing more precise and reliable solutions. The first pedestrian delay model is developed on the basis of compliance behaviour, has two components, such as waiting time delay and crossing time delay. This model can be used to evaluate pedestrian Level Of Service (LOS) and signal timing optimization. The second developed pedestrian delay model is based on noncompliance behaviour, has three components, such as waiting time delay, crossing time delay, and pedestrian-vehicular interaction delay. This model can also be used to evaluate the quality of pedestrian flow, estimating accurate pedestrian delay and LOS for local conditions, which is representative of the prevailing pedestrian condition. [ABSTRACT FROM AUTHOR]

In this paper, we study the capacity of a highway with two on-ramps and one off-ramp in between by using a cellular automaton traffic flow model. We investigate how to maximize the system capacity by assigning proper traffic flow to the two on-ramps. The system phase diagram is presented and eight different regions are observed under different conditions. It is shown that in region I, in which both on-ramps are in free flow and the main road upstream of the upstream on-ramp is in congestion, assigning proper proportion of the demand to two on-ramps could maximize the system capacity. Two critical values of the off-ramp flow ratio p o f f have been observed. When p o f f < p o f f , c 1 ( p o f f , c 1 < p o f f < p o f f , c 2 ), a higher (smaller) proportion of the demand should be assigned to the upstream on-ramp. When p o f f > p o f f , c 2 , no demand should be assigned to the upstream on-ramp. An analytical investigation has been performed to calculate the critical values. The analytical results are in good agreement with the simulation ones. [ABSTRACT FROM AUTHOR]

As the demand for additional capacity on urban freeways continues to increase, there is a need to better understand how to optimize the lane and shoulder configurations so as to improve capacity without adversely impacting operating speed. The overall objective for this research effort was to identify the operational implications of using reduced lane and shoulder widths on freeways. The operational analysis found speeds 3.5 km=h (2.2 mph) higher for a 3.7 m (12 ft) lane as compared to a 3.4 m (11 ft) lane. The authors developed an equation that can be used to predict speeds per lane for freeway locations with boundary conditions similar to those present in the study database. [ABSTRACT FROM AUTHOR]

This study aimed to develop a secondary crash risk prediction model on freeways using real-time traffic flow data. The crash and traffic data were collected on the I-880 freeway for five years in California, United States. The secondary crashes were identified by a method based on speed contour plot. The random effect logit model was used to link the probability of secondary crashes with the real-time traffic flow conditions, primary crash characteristics, environmental conditions, and geometric characteristics. The results showed that real-time traffic variables significantly affect the likelihood of secondary crashes. These traffic variables include the traffic volume, average speed, standard deviation of detector occupancy, and volume difference between adjacent lanes. In addition, the primary crash characteristics, environmental conditions and geometric characteristics also significantly affect the risks of secondary crashes. The model evaluation results showed that the predictive performance of the developed model was deemed satisfactory. The inclusion of traffic flow variables and random effect increases prediction accuracy by 16.6% and 7.7%, respectively. These results have the potential to be used in advanced traffic management systems to develop proactive traffic control strategies to prevent the occurrences of secondary crashes on freeways. [ABSTRACT FROM AUTHOR]

The introduction of connected and autonomous vehicles will bring changes to the highway driving environment. Connected vehicle technology provides real-time information about the surrounding traffic condition and the traffic management center’s decisions. Such information is expected to improve drivers’ efficiency, response, and comfort while enhancing safety and mobility. Connected vehicle technology can also further increase efficiency and reliability of autonomous vehicles, though these vehicles could be operated solely with their on-board sensors, without communication. While several studies have examined the possible effects of connected and autonomous vehicles on the driving environment, most of the modeling approaches in the literature do not distinguish between connectivity and automation, leaving many questions unanswered regarding the implications of different contemplated deployment scenarios. There is need for a comprehensive acceleration framework that distinguishes between these two technologies while modeling the new connected environment. This study presents a framework that utilizes different models with technology-appropriate assumptions to simulate different vehicle types with distinct communication capabilities. The stability analysis of the resulting traffic stream behavior using this framework is presented for different market penetration rates of connected and autonomous vehicles. The analysis reveals that connected and autonomous vehicles can improve string stability. Moreover, automation is found to be more effective in preventing shockwave formation and propagation under the model’s assumptions. In addition to stability, the effects of these technologies on throughput are explored, suggesting substantial potential throughput increases under certain penetration scenarios. [ABSTRACT FROM AUTHOR]

Traffic flow pattern identification, as well as anomaly detection, is an important component for traffic operations and control. To reveal the characteristics of regional traffic flow patterns in large road networks, this paper employs dictionary-based compression theory to identify the features of both spatial and temporal patterns by analyzing the multi-dimensional traffic-related data. An anomaly index is derived to quantify the network traffic in both spatial and temporal perspectives. Both pattern identifications are conducted in three different geographic levels: detector, intersection, and sub-region. From different geographic levels, this study finds several important features of traffic flow patterns, including the geographic distribution of traffic flow patterns, pattern shifts at different times-of-day, pattern fluctuations over different days, etc. Both spatial and temporal traffic flow patterns defined in this study can jointly characterize pattern changes and provide a good performance measure of traffic operations and management. The proposed method is further implemented in a case study for the impact of a newly constructed subway line. The before-and-after study identifies the major changes of surrounding road traffic near the subway stations. It is found that new metro stations attract more commute traffic in weekdays as well as entertaining traffic during weekends. [ABSTRACT FROM AUTHOR]

Previous research is limited regarding factors influencing tram-involved serious injury crashes. The aim of this study is to identify key vehicle, road, environment and driver related factors associated with tram-involved serious injury crashes. Using a binary logistic regression modelling approach, the following factors were identified to be significant in influencing tram-involved fatal crashes in Melbourne: tram floor height, tram age, season, traffic volume, tram lane priority and tram travel speed. Low floor trams, older trams, tram priority lanes and higher tram travelling speeds are more likely to increase tram-involved fatal crashes. Higher traffic volume decreases the likelihood of serious crashes. Fatal crashes are more likely to occur during spring and summer. Findings from this study may offer ideas for future research in the area of tram safety and help to develop countermeasures to prevent specific fatality types from occurring. [ABSTRACT FROM AUTHOR]

In previous studies, little attention has been paid to developing methods for estimating passenger car equivalent (PCE) factors under oversaturated conditions. This paper presents a new method to estimate PCE factors for heavy vehicles based on the assumption that backward wave velocities keep consistent under oversaturated conditions. As the variations of backward wave velocities in mixed flows will be minimal if the traffic stream is uniform, a minimum relative standard deviation optimising model is given based on backward wave velocity. The traffic data drawn from I-80 datasets provided by the next generation simulation are utilised to analyse this method and prove the assumption. In view of the limitation of empirical data, Vissim microscopic traffic software is used to simulate oversaturated traffic flow under different percentages of heavy vehicles. The results show that the effects of heavy vehicles under oversaturated conditions are greater than those under free-flow conditions and the proportion of heavy vehicles has a major impact on the PCE factors. [ABSTRACT FROM AUTHOR]

Improper mandatory lane change (MLC) maneuvers in the vicinity of highway off-ramp will jeopardize traffic efficiency and safety. Providing an advance warning for lane change necessity is one of the efficient methods to perform systematic lane change management, which encourages smooth MLC maneuvers occurring at proper locations to mitigate the negative effects of MLC maneuvers on traffic flow nearby off-ramp. However, the state of the art indicates the lack of rigorous methods to optimally locate this advance warning so that the maximum benefit can be obtained. This research is motivated to address this gap. Specifically, the proposed approach considers that the area downstream of the advance warning includes two zones: (i) the green zone whose traffic ensures safe and smooth lane changes without speed deceleration (S-MLC); the start point of the green zone corresponding to the location of the advance warning; (ii) the yellow zone whose traffic leads to rush lane change maneuvers with speed deceleration (D-MLC). An optimization model is proposed to search for the optimal green and yellow zones. Traffic flow theory such as Greenshield model and shock wave analysis are used to analyze the impacts of the S-MLC and D-MLC maneuvers on the traffic delay. A grid search algorithm is applied to solve the optimization model. Numerical experiments conducted on the simulation model developed in Paramics 6.9.3 indicate that the proposed optimization model can identify the optimal location to set the advance MLC warning nearby an off-ramp so that the traffic delay resulting from lane change maneuvers is minimized, and the corresponding capacity drop and traffic oscillation can be efficiently mitigated. Moreover, the experiments validated the consistency of the green and yellow zones obtained in the simulation traffic flow and from the optimization model for a given optimally located MLC advance warning under various traffic regimes. The proposed approach can be implemented by roadside mobile warning facility or on-board GPS for human-driven vehicles, or embedded into lane change aid systems to serve connected and automated vehicles. Thus it will greatly contribute to both literature and engineering practice in lane change management. [ABSTRACT FROM AUTHOR]

This paper introduces a new centrality measure, nominated by the authors as mobility centrality ( C), which arose during the study of the interregional road network in Greece. The proposed measure is constructed by the use of the anagogic method considering the formula of the kinetic energy of a particle in Physics and adjusting its mathematical analogue to the case of the interregional road network. The new centrality measure is estimated to be useful for the operational analysis of a network (such as the analysis of network flows), since it characterizes as central these vertices that appear to have the greatest tendency to attract or expel network flows. The ability of the proposed centrality measure to illustrate flow tendencies was examined empirically by correlating and regressing mobility centrality to the commuting status of the Greek interregional network and to four of the most common existing centrality measures (betweenness, closeness, straightness and degree centrality) of the available data. The empirical analysis indicated that the proposed centrality measure ( C) presents sufficient ability to describe the status of the Greek interregional commuting system and it is believed that it is able to describe the inner potential that produces flows in a network. [ABSTRACT FROM AUTHOR]

The objective of this work is to determine, by means of simulation and experiments, the effect of pedestrian traffic management in the boarding and alighting time of passengers at metro stations. Studies were made by means of a pedestrian traffic microsimulator (LEGION Studio) and experiments at the Human Dynamic Laboratory (HDL) of Universidad de los Andes in Santiago de Chile, to obtain criteria for the pedestrian traffic management on the platform and doors of metro cars. The methodology consists of building a boarding/alighting hall of a metro car and the relevant portion of the platform in front of the hall. The simulation scenarios included the location of the vertical handrail in the hall of the car, delimitation of a keep out zone in front of the doors and the use of differentiated doors for boarding and alighting. The results of the simulation and laboratory experiments are expressed in Pedestrian Level of Service (LOS), Passenger Service Time (PST), passenger density on the vehicle and platform, and passenger dissatisfaction. Both, the simulation results and laboratory experiments allow us to give some recommendations for the pedestrian traffic management in metro systems. [ABSTRACT FROM AUTHOR]

New variable speed limit (VSL) schemes are developed based on the Kinematic Wave theory to increase freeway bottleneck discharge rates under two scenarios: (i) steady queue and (ii) oscillatory queue. The key principle is to impose VSL control some distance upstream of a bottleneck to starve the inflow to the bottleneck and dissipate the queue. Once the queue near the bottleneck vanishes, another less restrictive VSL is imposed upstream to (i) resolve the heavy queue generated by the first VSL and (ii) regulate the inflow to the bottleneck to sustain the stable maximum bottleneck discharge rate and prevent traffic breakdown. Several strategies are developed for each scenario ranging from the simplest strategy that maximizes the delay saving to more sophisticated strategies for upstream queue management. An analysis of the model parameters suggests that a wide range of the first speed limit (to clear the queue around the bottleneck) can be imposed to realize significant delay savings. [ABSTRACT FROM AUTHOR]

For on-line traffic control at traffic control centers there is a need for fast computations of predictions of traffic flow over a short prediction horizon, say 30 min, to evaluate the impact of different scenarios for the purpose of on-line scenario selection. A novel approach is presented to predict the traffic flow in a large-scale traffic network in an asynchronous, parallel, and distributed way at two or more subnetworks combined with a consistency check at the network level within a reasonable-small computation time. [ABSTRACT FROM AUTHOR]

Highlights: [•] Methodology based on the logic of action research. [•] Technological innovation is conceived to increase road safety. [•] Iterative methodology is proposed for to take user's aspects into account. [•] The device is effective for reducing speed. [•] This gain is maximized when safety device is understood by users. [ABSTRACT FROM AUTHOR]

Abstract: Three-phase traffic flow theory of city traffic has been developed. Based on simulations of a stochastic microscopic traffic flow model, features of moving synchronized flow patterns (MSP) have been studied, which are responsible for a random time-delayed breakdown of a green-wave (GW) organized in a city. A possibility of GW control leading to the prevention of GW breakdown has been demonstrated. A diagram of traffic breakdown in under-saturated traffic (transition from under- to over-saturated city traffic) at the signal has been found; the diagram presents regions of the average arrival flow rate, within which traffic breakdown can occur, in dependence of parameters of the time-function of the arrival flow rate or/and signal parameters. Physical reasons for a crucial difference between results of classical theory of city traffic and three-phase theory are explained. In particular, we have found that under-saturated traffic at the signal can exist during a long time interval, when the average arrival flow rate is larger than the capacity of the classical theory; the classical capacity is equal to a minimum capacity in three-phase theory. Within a range of the average arrival flow rate between the minimum and maximum signal capacities, under-saturated traffic is in a metastable state with respect to traffic breakdown. We have distinguished the following possible causes for the metastability of under-saturated traffic: (i) The arrival flow rate during the green phase is larger than the saturation flow rate. (ii) The length of the upstream front of a queue at the signal is a finite value. (iii) The outflow rate from a MSP (the rate of MSP discharge) is larger than the saturation flow rate. [Copyright &y& Elsevier]

Passing on rural two-lane highways is one of the most important driving tasks. More than 28000 vehicles were observed and the passing maneuvers were recorded of 10 two-lane highways in northern Iraq during June and July months of 2005. It was found that the number of passing maneuver increase as the flow rate for both directions increase up to 1500 veh/hr flow rate. The passing maneuvers decreases with the increase in flow rate. The increase in flow rate causes an increase in demand of passing and decrease in passing supply. Volume of around 212 veh/hr gives a balance between demand of passing and passing supply. [ABSTRACT FROM AUTHOR]

Highlights: [•] An assessment method for highway network vulnerability is developed. [•] Network vulnerability indices based on link physical characteristics and traffic flow are proposed. [•] The impact of unsatisfied demand on vulnerability assessment is modelled. [•] Ability of the developed vulnerability indices to show the impact of demand and network capacity variations is demonstrated. [ABSTRACT FROM AUTHOR]

The article presents a mathematical study of a hydrodynamic model of traffic flow on a circular highway. The concepts discussed in the study include fluid dynamics, the number of vehicles per unit length of the roadway, and the fundamental diagram or fundamental curve. Details on the mathematical notations, equilibrium set, and priority rule of the study are provided.

Freeway interchanges accommodate large traffic volumes within a constrained area. When their design is complex and includes unexpected features, it may increase drivers' workloads and lead to driving errors, thus increasing the likelihood of a crash. The study's goal is to provide a tool for assessing the safety impacts of interchange complexity, promoting a simpler and safer design. This paper presents an interchange complexity model (ICM) that is based on estimations of aggregated drivers' workload in interchanges. A database of 25 interchanges from the New Jersey interstate road system was used to examine the ICM and construct a resulting crash prediction model by comparing their interchange complexity index (ICI) with three years of crash data. Further on, nine additional interchanges were analyzed similarly in order to validate both the use of the ICM and the resulting crash prediction models. Actual observations of the validation data were relatively close to average model predictions. It is proposed that highway planners could use the ICM for estimating the complexity of interchange design alternatives and the implications for road safety to minimize driver errors and thus reduce crash occurrences. [ABSTRACT FROM AUTHOR]

Fusing freeway traffic data such as spot speeds and travel times from a variety of traffic sensors (loops, cameras, automated vehicle identification systems) into a coherent, consistent, and reliable picture of the prevailing traffic conditions (e.g., speeds, flows) is a critical task in any off- or online traffic management or data archival system. This task is challenging as such data differ in terms of spatial and temporal resolution, accuracy, reliability, and most importantly in terms of spatiotemporal semantics. In this article, we propose a data fusion algorithm (the extended generalized Treiber-Helbing filter [the EGTF]) which, although heuristic in nature, uses basic notions from traffic flow theory and is generic in the sense that it does not impose any restrictions on the way the data are structured in a temporal or spatial way. This implies that the data can stem from any data source, given they provide a means to distinguish between free flowing and congested traffic. On the basis of (ground truth and sensor) data from a micro-simulation tool, we demonstrate that the EGTF method results in accurate reconstructed traffic conditions and is robust to increasing degrees of data corruption. Further research should focus on validating the approach on real data. The method can be straightforwardly implemented in any traffic data archiving system or application which requires consistent and coherent traffic data from traffic sensors as inputs. [ABSTRACT FROM AUTHOR]

Horizontal roadway curvature data are essential for roadway safety analysis. However, collecting such data is time-consuming, costly, and dangerous using traditional, manual surveying methods. It is especially difficult to perform such manual measurement when roadways have high traffic volumes. Thus, it would be valuable for transportation agencies if roadway curvature data could be computed from photographic images taken using low-cost digital cameras. This is the first article that develops an algorithm using emerging vision technology to acquire horizontal roadway curvature data from roadway images to perform roadway safety assessment. The proposed algorithm consists of four steps: (1) curve edges image processing, (2) mapping edge positions from an image domain to the real-world domain, (3) calibrating camera parameters, and (4) calculating the curve radius and center from curve points. The proposed algorithm was tested on roadways having various levels of curves and using different image sources to demonstrate its capability. The ground truth curvatures for two cases were also collected to evaluate the error of the proposed algorithm. The test results are very promising, and the computed curvatures are especially accurate for curves of small radii (less than 66 m/200 ft) with less than 1.0% relative errors with respect to the ground truth data. The proposed algorithm can be used as an alternative method that complements the traditional measurement methods used by state DOTs to collect roadway curvature data. [ABSTRACT FROM AUTHOR]

On the basis of one-lane comfortable driving model, this paper established a two-lane traffic cellular automata model, which improves the slow randomization effected by brake light. Considering the driver psychological characteristics and mixed traffic, we studied the lateral influence between vehicles on adjacent lanes. Through computer simulation, the space-time diagram and the fundamental figure under different conditions are obtained. The study found that aggressive driver makes a slight congestion in low-density traffic and improves the capacity of high-density traffic, when the density exceeds 20pcu/km the more aggressive drivers the greater the flow, when the density below 40pcu/km driver character makes an effect, the more cautious driver, the lower the flow. The ratio of big cars has the same effect as the ratio of aggressive drivers. Brake lights have the greatest impact on traffic flow and when the density exceeds 10pcu/km the traffic flow fluctuates. Under periodic boundary conditions, the disturbance of road length on traffic is minimal. The lateral influence only play a limited role in the medium-density conditions, and only affect the average speed of traffic at low density. [ABSTRACT FROM AUTHOR]

General data on the network of Ukrainian highways are presented. The analysis of design methods of highway reconstruction based on the theory of traffic flows and economic calculations of its repay time is made. The relationship between traffic intensity and speed is shown by considering the theory of traffic flows. The methods, taking into account the principle of effectiveness of highway reconstruction based on its repay time, are discussed. [ABSTRACT FROM AUTHOR]

Transportation management policies and practices are currently experiencing evolving trends such as funding limitations, aging facilities, greater travel demand, increased number of visible stakeholders, and higher user expectations. As a result, transportation agencies currently grapple with how to best incorporate a wide range of performance criteria in investment evaluation and decision making. Often, a key prerequisite to multiple criteria decision making is to establish the relative importance of different performance criteria as perceived by decision makers, facility users, and other stakeholders. This paper reviews methods that exist in the literature for weighting and illustrates the applications of some of these methods. For the bridge management case study, the direct-questioning weighting technique was found to yield results that indicated high levels of agreement among bridge experts. For the overall highway asset management case study, the analytical hierarchy process was used to derive the weights across performance criteria. The findings show that the distribution of weights across various highway performance criteria based on the agency perspective can differ from that based on the road users’ perspective. The relative weights of the different performance criteria can help agencies establish the overall combined desirability or otherwise of each alternative transportation action in terms of all performance criteria, identify the best action in a balanced and rational manner, or analyze trade-offs between the alternative actions. [ABSTRACT FROM AUTHOR]

The paper develops a short-term space-time traffic flow forecasting strategy integrating the empirical-based seasonal autoregressive integrated moving average (SARIMA) time-series forecasting technique with the theoretical-based first-order macroscopic traffic flow model—cell transmission model. A case study in Dublin city center which has serious traffic congestion is performed to test the effectiveness of the proposed multivariate traffic forecasting strategy. The results show that the forecasts at the junctions only deviate around 10% at a maximum from the original observations and seem to indicate that the proposed strategy is one of the effective approaches to predict the real-time traffic flow level in a congested network especially at the locations where no continuous data collection takes place. [ABSTRACT FROM AUTHOR]

Capacity can be derived by fitting a relationship between the three fundamental traffic variables: flow, speed, and density. The study uses a dual-regime model with the consideration of all three variables. Different forms of functions were specified for congested and uncongested conditions. An optimization based estimation procedure was developed to minimize the distance between the theoretical functions and the traffic stream variable measurements. The optimal procedure was coded into a computer program and applied to three data sets representing different roadway classifications. The results indicate that the proposed method can produce good estimates of the key traffic stream parameters including the roadway capacity. [ABSTRACT FROM AUTHOR]

How to alleviate the damages of cascading failures triggered by the overload of edges/nodes is common in complex networks. To describe the whole cascading failures process from edges overloading to nodes malfunctioning and the dynamic spanning clustering with the evolvement of traffic flow, we propose a capacity assignment model by introducing an equilibrium assignment rule of flow in artificially created scale-free traffic networks. Additionally, the capacity update rule of node is given in this paper. We show that a single failed edge may undergo the cascading failures of nodes, and a small failure has the potential to trigger a global cascade. It is suggested that enhancing the capacity of node is particularly important for the design of any complex network to defense the cascading failures. Meanwhile, it has very important theoretical significance and practical application worthiness in the development of effective methods to alleviate the damage of one or some failed edges/nodes. [ABSTRACT FROM AUTHOR]

Capacity has traditionally been defined deterministically, and has been assumed to occur immediately before breakdown. Recent studies, however, have shown that the value of capacity, i.e., maximum throughput, is probabilistic, and does not always occur immediately before the breakdown. Four different types of flows (i.e., maximum prebreakdown flow, breakdown flow, maximum queue discharge flow, and average queue discharge flow) referred to as “capacity flows” in this paper, are considered to examine how they differ by day of the week and time of the day, and whether they are significantly different by type of freeway segment. Speed and volume data were obtained, which were initially collected by remote traffic microwave sensors at the US-202 southbound near Philadelphia, from May to August 2004. The four types of flows described above were collected and distinguished by time period, day of the week, and segment type. In conclusion, the mean capacity flows were different during different times of the day, but were the same each day of the week. In comparing segment types, capacity flows per lane are generally not equal between merging, diverging, weaving, and lane drop segments. [ABSTRACT FROM AUTHOR]

Abstract: This paper reports on results of a study undertaken in the UK aimed at investigating factors affecting the car following process. An understanding of the factors affecting this complex decision making process is essential to a wide range of theoretical issues including driver workload, capacity and the modeling of freeway flow, as well as practical applications such as the design of in-vehicle driver aids and assistance systems, many of which have direct relevance to increasing driver safety. The study used an instrumented vehicle to collect time dependent following data for a group of test drivers. Data was collected on two differing types of high speed road, using six primary subjects who drove a test vehicle, supplemented by data on 123 drivers that were observed following the test vehicle. Examination was made of how the time headway chosen by a driver is influenced by a range of situational variables commonly believed to effect behavior, with four main findings. Firstly, headway was found to change according to the type of vehicle being followed (i.e. subjects followed closer to trucks than to cars), secondly, little variation was found with changes in overall traffic flow, thirdly, little correlation was found with road type, and lastly a distinct day-to-day variation in individual behavior was observed. [Copyright &y& Elsevier]

An urban traffic network of signalised intersections can be suitably modelled as a discrete event system, in which the traffic light alternations are described by means of timed coloured Petri nets (TCPNs). A module of basic traffic TCPN model with a signal timing plan for a day is successfully constructed. The traffic operations are ruled by the control logic of TCPN and an analysis method using place invariant is verified. From the basic TCPN model, some of the complicated traffic signal models will be easily obtained. Moreover, a real-world supervisor of the urban traffic light system is implemented by the new methodology. Finally, an urban traffic light control system with five intersections is realised. Also, the performance of the supervisor of the urban traffic light system can be confirmed by the simulation results. [ABSTRACT FROM AUTHOR]

Abstract: Multi-agent systems allow the simulation of complex phenomena that cannot easily be described analytically. Multi-agent approaches are often based on coordinating agents whose actions and interactions are related to the emergence of the phenomenon to be simulated. In this article, we focus on road traffic simulation, specifically the design of a road traffic simulation tool able to deal realistically with road junctions. We propose a multi-agent behavioral model based on (i) the opportunistic individual behaviors that describe the norm violation and (ii) the anticipatory individual abilities of simulated drivers that allow critical situations to be detected. Our proposition has been validated for different traffic scenarios. Specifically, we simulated the traffic in a real intersection and then compared the simulated traffic flow with the real flow to highlight the relevance of our approach. [Copyright &y& Elsevier]

We investigate connectivity in the ad hoc network formed between vehicles that move on a typical highway. We use a common model in vehicular traffic theory in which a fixed point on the highway sees cars passing it that are separated by times with an exponentially distributed duration. We obtain the distribution of the distances between the cars, which allows us to use techniques from queuing theory to study connectivity. We obtain the Laplace transform of the probability distribution of the connectivity distance, explicit expressions for the expected connectivity distance, and the probability distribution and expectation of the number of cars in a platoon. Then, we conduct extensive simulation studies to evaluate the obtained result. The analytical model that we present is able to describe the effects of various system parameters, including road traffic parameters (i.e., speed distribution and traffic flow) and the transmission range of vehicles, on the connectivity. To more precisely study the effect of speed on connectivity, we provide bounds obtained using stochastic ordering techniques. Our approach is based on the work of Miorandi and Altman, which transformed the problem of connectivity distance distribution into that of the distribution of the busy period of an equivalent infinite server queue. We use our analytical results, along with common road traffic statistical data, to understand connectivity in vehicular ad hoc networks. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a novel roadside unit (RSU)-aided message authentication scheme named RAISE, which makes RSUs responsible for verifying the authenticity of messages sent from vehicles and for notifying the results back to vehicles. In addition, RAISE adopts the k-anonymity property for preserving user privacy, where a message cannot be associated with a common vehicle. In the case of the absence of an RSU, we further propose a supplementary scheme, where vehicles would cooperatively work to probabilistically verify only a small percentage of these message signatures based on their own computing capacity. Extensive simulations are conducted to validate the proposed scheme. It is demonstrated that RAISE yields a much better performance than previously reported counterparts in terms of message loss ratio (LR) and delay. [ABSTRACT FROM AUTHOR]

To facilitate the dissemination of a time-critical information in a vehicular ad hoc network (VANET), immediate network connectivity is needed. In other words, a time-critical message from a source should be able to propagate and reach all of the vehicles on the road segment without any delay due to the unavailability of the vehicles to forward the message. Clearly, this requires the road segment to have a certain number of vehicles equipped with communication devices. It is the task of a system designer to determine the minimum number of vehicles (i.e., the minimum penetration) necessary to form a connected network as well as the critical transmission range required to provide such connectivity. In this paper, we present an analytical framework for determining the connectivity requirements in distributing the traffic information in a self-organizing vehicular network. One- and two-way street scenarios are considered. In addition to the conventional perspective on connectivity, where the characteristics of the wireless channel are often neglected, our analysis offers a new view by taking important physical-layer parameters, such as fading, propagation path loss, transmit power, and transmission data rate, into consideration. [ABSTRACT FROM AUTHOR]

As more and more cars are equipped with Global Positioning System (GPS) and Wi-Fi transmitters, it becomes easier to design systems that will allow cars to autonomously interact with each other, e.g., regarding traffic on the roads. Indeed, car manufacturers are already equipping their cars with such devices. Although, currently, these systems are a proprietary, we envision a natural evolution where agent applications will be developed for vehicular systems, e.g., to improve car routing in dense urban areas. Nonetheless, this new technology and agent applications may lead to the emergence of self-interested car owners, who will care more about their own welfare than the social welfare of their peers. These car owners will try to manipulate their agents such that they transmit false data to their peers. Using a simulation environment, which models a real transportation network in a large city, we demonstrate the benefits that are achieved by self- interested agents if no countermeasures are implemented. We then proceed to describe the mechanisms for minimizing the effect of the malicious agents on other agents in the network. [ABSTRACT FROM AUTHOR]

Recognizing temporal patterns in traffic flow has been an important consideration in short-term traffic forecasting research. However, little work has been conducted on identifying and associating traffic pattern occurrence with prevailing traffic conditions. We propose a multilayer strategy that first identifies patterns of traffic based on their structure and evolution in time and then clusters the pattern-based evolution of traffic flow with respect to prevailing traffic flow conditions. Temporal pattern identification is based on the statistical treatment of the recurrent behavior of jointly considered volume and occupancy series; clustering is done via a two-level neural network approach. Results on urban signalized arterial 90-second traffic volume and occupancy data indicate that traffic pattern propagation exhibits variability with respect to its statistical characteristics such as deterministic structure and nonlinear evolution. Further, traffic pattern clustering uncovers four distinct classes of traffic pattern evolution, whereas transitional traffic conditions can be straightforwardly identified. [ABSTRACT FROM AUTHOR]

Abstract: This article presents a visual application which allows a study and analysis of traffic behavior on major roads (more specifically freeways and highways), using as the main surveillance artefact a video camera mounted on a relatively high place (such as a bridge) with a significant image analysis field. The system described presents something new which is the combination of both traditional traffic monitoring systems, that is, monitoring to get information on different traffic parameters and monitoring to detect accidents automatically. Therefore, we present a system in charge of compiling information on different traffic parameters. It also has a surveillance module for that traffic, which can detect a wide range of the most significant incidents on a freeway or highway. [Copyright &y& Elsevier]

In this paper, we use the speed-gradient model proposed by Jiang et al. [Transp. Res. B36, 405 (2002)] to study the effects that various perturbations have on the stability of traffic flow. Our numerical tests show that the effects of perturbations on the stability of traffic flow are related to the initial density, i.e., when the initial density is very low (ρ0 ≤ 0.02) or very high (ρ0 > 0.08), any perturbation has little effect on the stability of traffic flow; when the initial density is relatively low (0.02 < ρ0 ≤ 0.04), small perturbations have little effect on the stability of traffic flow and large perturbations will have effect on it and produce local cluster; when the initial density is relatively high (0.04 < ρ0 ≤ 0.08), any perturbation will have great effect on the stability of traffic flow and produce stop-and-go traffic. These results are completely accordant with the real traffic, which just shows that the speed-gradient model can be used to perfectly explore the consequences caused by various perturbations. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we develop a relaxation strategy to the dynamic O–D estimation problem (DODE) problem. Cast as a variational inequality (VI), the DODE problem endogenizes the determination of the dynamic path-link incidence relationship (i.e., the dynamic assignment matrix) and takes users’ response to traffic congestion into account. In our formulation, traffic dynamics on road links can be modeled by the Lighthill, Whitham and Richards theory, a delay-function model, or a point-queue model, coupled with CTM-like flow distribution models at nodes. Which model to use depends, of course, on specific modeling situations. Different from numerous previous studies, our formulation avoids the bi-level structure that poses analytical and numerical difficulties. This is achieved by balancing the path cost and the path deviation (the latter measures the difference between estimated and measured traffic conditions), weighed by a dispersion parameter which determines the extent to which users’ behavior is respected. We prove the equivalence between the VI problem and the derived dynamic DODE optimality conditions, and establish the conditions under which a solution to the VI problem exists. A column generation algorithm is proposed to solve the VI problem. Numerical results based on synthetic data are also presented. [Copyright &y& Elsevier]

Online traffic flow modeling is of increasing importance due to intelligent transport systems and technologies. The flow-density relation plays an important role in traffic flow modeling and provides a basic way to illustrate traffic flow behavior under different traffic flow and traffic density conditions. Until now the research effort has focused mainly on the shape of the relation. The time series of the relation has not been identified clearly, even though the time series of the relation reflects the upstream/downstream traffic conditions and should be considered in the traffic flow modeling. In this paper, the dynamic flow-density relation is identified based on the classification of traffic states and is quantified employing fuzzy logic. The quantified dynamic flow-density relation builds the basis for online application of a macroscopic traffic flow model. The new approach to online modeling of traffic flow applying the dynamic flow-density relation alleviates parameter calibration problems stemming from the static flow-density relation. [ABSTRACT FROM AUTHOR]