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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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

Weaving areas are one of the major highway facilities that have long been investigated by researchers. Their capacities are currently estimated based on the density 27 pc/km/ln. There is no specific reason why this method can produce accurate estimates. In addition, no data collection has been performed to validate them. This study develops a generalized capacity estimation model for weaving areas, which is applicable to the entire range of configurations of weaving areas, and compares the resulting capacity estimates to field estimates. The proposed methodology is based on gap acceptance theory and linear programming techniques. Speed and flow data over several days were obtained and analyzed to extract the capacity of three study sites along the QE Expressway, Toronto. It was found that, for the three study sites, the proposed methodology provides capacity estimates that are closer to the field-observed capacity values than the Highway Capacity Manual (2000) estimates. [ABSTRACT FROM AUTHOR]

Transportation agencies are becoming more aware of the seriousness of traffic delay caused by urban freeway rehabilitation and are experimenting with the use of intelligent transportation systems to control traffic demand in construction work zones (CWZ). This case study presents the process, evaluation, and public reaction to the implementation of an automated work zone information system (AWIS), as well as an Internet public outreach program, to mitigate traffic delays during the reconstruction of a section of Interstate-15 (I-15) near Devore in Southern California. The project consisted of a 4.5-km stretch of high traffic volume concrete pavement that was rebuilt during two 9-day closures (one for each direction) using continuous construction operations. The approach produced up to 18% reduction in peak-hour traffic demand through the CWZ, which reduced maximum delays from 90 to 50 min producing a $3.6 million benefit in potential road user cost savings. The intelligent systems also contributed to reversing initial public reluctance toward the accelerated rehabilitation approach. The study will help transportation agencies efficiently configure and operate AWIS in combination with public outreach for highway rehabilitation under high traffic volume. [ABSTRACT FROM AUTHOR]

The Highways Agency's National Traffic Control Centre (NTCC) became fully operational in November 2003. The services provided by the control centre are key to satisfying the objectives of providing better information to travellers and ensuring more reliable journeys. This paper describes the policy context within which the control centre has been delivered; the means by which it collects data on conditions on England's motorway and all-purpose trunk road network; how those data are analysed; and the means by which information is disseminated to the general public. These services are providing the catalyst for the development of traffic information delivery tools by the Agency and private sector information providers. [ABSTRACT FROM AUTHOR]

In this paper, two definitions about traffic congestion are proposed. We describe the traffic congestion spreading with the SEIR model of a complex small-world network. In addition, the relationships among the congestion factor, the number of average infection, the average recover rate and the infection rate are given by simulations in general traffic congestion conditions. [ABSTRACT FROM AUTHOR]

Highway maintenance, like rehabilitation or resurfacing, on four-lane, two-way highways usually requires closing one or two lanes to set up a work zone. In this paper we evaluate several alternatives defined by the number of closed lanes, fractions of traffic diverted to alternate routes, and crossover of diverted traffic to opposite lanes. A methodology is developed to minimize the total cost, including agency cost, user cost, and accident cost, by optimizing work zone length for each alternative and finding optimal diversion fraction, while considering the characteristics of the detour route bypassing the work zone. Finally, guidelines for selecting the best alternative for different characteristics of traffic flows, roads, and maintenance processes are developed by deriving thresholds among alternatives. [ABSTRACT FROM AUTHOR]

The two models FOTO (Forecasting of Traffic Objects) and ASDA (Automatische Staudynamikanalyse: Automatic Tracking of Moving Traffic Jams) for the automatic recognition and tracking of congested spatial–temporal traffic flow patterns on freeways are presented. The models are based on a spatial–temporal traffic phase classification made in the three-phase traffic theory by Kerner. In this traffic theory, in congested traffic two different phases are distinguished: “wide moving jam” and “synchronized flow”. The model FOTO is devoted to the identification of traffic phases and to the tracking of synchronized flow. The model ASDA is devoted to the tracking of the propagation of moving jams. The general approach and the different extensions of the models FOTO and ASDA are explained in detail. It is stressed that the models FOTO and ASDA perform without any validation of model parameters in different environmental and traffic conditions. Results of the online application of the models FOTO and ASDA at the TCC (Traffic Control Center) of Hessen near Frankfurt (Germany) are presented and evaluated. [Copyright &y& Elsevier]

In city network, the state of the traffic flow which is in front of each intersection is random and disorder. It usually leads to some traffic problems. In this paper, we propose a new technique to control such dynamical state of the traffic flow on a main road. A type of the control signal has been designated at a given site (signal point) in front of each intersection. Under the effect of the control signal, the velocities of the vehicles which pass the signal point will be changed. Our method is tested for the "unified" CA traffic model which is the marriage of the NaSch model and the BML model. The simulation results demonstrate that using this control strategy, when the traffic light is green, the disorder state of the traffic flow which is in front of each intersection can be suppressed, and the periodic state of the traffic flow will occur. [ABSTRACT FROM AUTHOR]

It is essential to predict traffic flow rates dynamically and accurately for traffic engineers to efficiently control traffic flows and reduce traffic delays. This paper introduces a method for prediction o f freeway traffic flows. The method combines the combination of the Kalman control theory and the times series theory into a tool for traffic flow prediction. It is illustrated that the combination method provides more accurate traffic flow prediction than using either one of the two theories individually. With the prediction model, the traffic flow on a given freeway in the next time interval (five to 15 minutes) can be predicted using traffic data at the current and past time intervals. Dynamic traffic predictions with the developed model can be performed for individual lanes as well as for all the lanes of each travel direction. It is also shown that a dynamic prediction of traffic flow rate with this prediction model would also constitute a dynamic prediction of traffic congestion if the traffic capacity was given. [ABSTRACT FROM AUTHOR]

Problems related to highway traffic operation and congestion management can be alleviated with the use of modern intelligent transportation systems (ITSs). Advanced Traveler Information Systems (ATIS) is one of the emerging technologies that will help travelers plan routes and schedules of their trips so as to redistribute the traffic over the highway network. Such redistribution will try to maximize the use of available highway capacity. Collections of real-time data and short-term predictions of traffic volumes are among the critical needs of an ATIS. This article studies characteristics of different traffic volume time series. In particular, time-series analysis is applied to the prediction of daily traffic volumes. The daily traffic volume is estimated by using the previous 13 daily traffic volumes. The study involves a comparison of statistical and neural network techniques for time series analysis. The analysis is applied to different types of road groups according to the trip purpose and trip length distribution. It is hoped that this study will provide a better understanding of various issues involved in the short-term prediction of traffic volumes on different types of highways. [ABSTRACT FROM AUTHOR]

In this paper we formulate a basic model for two-dimensional timedependent traffic flow. The model is designed specifically to relate to the morning peak period of commuter traffic, for which the underlying ideas are relatively unencumbered. The time variation of the point value of the 'travel intensity at a given time point' is considered and also the global 'wave movement' that peak hour traffic will exhibit—the peak hour will not be entirely synchronous at all points over the city. It is found that under stanrdard assumptions as to rouling and the location of trip end points, a strong peak hour occurs in the form of a shock wave. The effect of changes to the routing system and trip-end distribution is also considered. [ABSTRACT FROM AUTHOR]

Virtually all proposed systems for highway automation have at least one mode in common-steady-state car following. The nature of this mode is extremely important, as it can determine the upper limit of flow capacity of an automated highway. This limit is explored for a linear headway controller, and a fundamental relation between the effective vehicle response time and the permissible traffic stream density is obtained. The required intervehicular spacing with a linear headway controller is shown to be proportional to the effective vehicle time constant for small-signal inputs; thus, one can achieve small spacings and high flow rates by reducing this parameter to I see or less. However, the vehicle is then highly responsive to small changes in lead-vehicle speed- possibly resulting in both passenger discomfort and poor fuel economy. These shortcomings can be avoided by using a linear velocity controller for automatic car following. [ABSTRACT FROM AUTHOR]