Modeling delay at signalized intersections with channelized right‐turn lanes considering the impact of blockage

This paper presents a probabilistic delay model for signalized intersections with right‐turn channelization lanes considering the possibility of blockage. Right‐turn channelization is used to improve the capacity and to reduce delay at busy intersections with a lot of right‐turns. However, under heavy traffic conditions the through vehicles will likely block the channelization entrance that accrues delay to right‐turn vehicles. If the right‐turn channelization gets blocked frequently, its advantage in reducing the intersection delay is neglected and as a result the channelization lane becomes inefficient and redundant. The Highway Capacity Manual (HCM) neglects the blockage effect, which may be a reason for low efficiency during peak hours. More importantly, using HCM or other standard traffic control methods without considering the blockage effects would lead to underestimation of the delay. To overcome this issue, the authors proposed delay models by taking into account both deterministic and random aspects of vehicles arrival patterns at signalized intersections. The proposed delay model was validated through VISSIM, a microscopic simulation model. The results showed that the proposed model is very precise and accurately estimates the delay. In addition, it was found that the length of short‐lane section and proportion of right‐turn and through traffic significantly influence the approach delay. For operational purposes, the authors provided a step‐by‐step delay calculation process and presented approach delay estimates for different sets of traffic volumes, signal settings, and short‐lane section lengths. The delay estimates would be useful in evaluating adequacy of the current lengths, identifying the options of extending the short‐lane section length, or changing signal timing to reduce the likelihood of blockage. Copyright © 2016 John Wiley & Sons, Ltd.     

A macroscopic traffic model for highway work zones: Formulations and numerical results

This study presents a multilane model for analyzing the dynamic traffic properties of a highway segment under a lane‐closure operation that often incurs complex interactions between mandatory lane‐changing vehicles and traffic at unblocked lanes. The proposed traffic flow formulations employ the hyperbolic model used in the non‐Newtonian fluid dynamics, and assume the lane‐changing intensity between neighboring lanes as a function of their difference in density. The results of extensive simulation experiments indicate that the proposed model is capable of realistically replicating the impacts of lane‐changing maneuvers from the blocked lanes on the overall traffic conditions, including the interrelations between the approaching flow density, the resulting congestion level, and the exiting flow rate from the lane‐closure zone. Our extensive experimental analyses also confirm that traffic conditions will deteriorate dramatically and evolve to the state of traffic jam if the density has exceeded its critical level that varies with the type of lane‐closure operations. This study also provides a convenient way for computing such a critical density under various lane‐closure conditions, and offers a theoretical basis for understanding the formation as well as dissipation of traffic jam.     

Lane‐based optimization of traffic equilibrium settings for area traffic control

Area traffic control is an important element in Intelligent Transportation System (ITS). This paper extends the lane‐based optimization method to a traffic equilibrium network, which improves the operational performance of signal‐controlled network. We formulate a decomposition approach to simultaneously optimize the lane markings and signal settings for a signal‐controlled network that comprises two levels of optimization. At the junction level, the lane markings, control sequence, and other aspects of the signal settings are optimized for individual junctions, whereas at the network level, the group‐based signal settings are optimized to take into account the re‐routing characteristics of travelers and signal coordination effects that are based on a TRANSYT traffic model, which is a well‐known procedure for evaluating the performance of signal‐controlled networks. We use a numerical example to demonstrate the effectiveness of the proposed methodology.     

An applicatoin of an optimal traffic control during lane closure periods of a two‐lane road

On two‐lane roadways, when provision should be made for alternative one‐way movement (for construction or maintenance), the traffic characteristics differ from normal operation in which no lane is closed. The purpose of this study is to derive optimal strategies for controlling, by means of traffic signals, the one lane operation (in two‐way roadways). In this study, strategies to determine the optimal length of the closed one‐lane section during construction and maintenance work are established. This length minimizes the objective function representing the tradeoff between delay cost and operational cost. Using the length value obtained by the proposed model, plus a timing methodology, the overall cost of operating the closed highway section can be minimized. The sensitivity analysis of the optimal solution for the section length is examined with respect to the input variables. This analysis shows that for very low traffic flow values (less than 100 vph per direction), the solution is very sensitive to fuel price changes, while for greater flow values, the solution is insensitive to this change. Similar results are obtained for changes in the worker's wage which is part of both the operational and the delay cost. That is, the section's length is sensitive to wage changes at low traffic flow and insensitive otherwise. Based on the results presented in this study, it is possible to establish a guideline for the section's length determination. The control measure can emerge from a pair of traffic signals that can be installed at both ends of the closed highway segment. This traffic control system is also described in the study in terms of its components and operational features and advantages.     

Characterization and comparison of traffic flow on reversible roadways

Reversible traffic operations have become an increasingly popular strategy for mitigating traffic congestion associated with the directionally unbalanced traffic flows that are a routine part of peak commute periods, planned special events, and emergency evacuations. It is interesting that despite its widespread and long‐term use, relatively little is known about the operational characteristics of this form of operation. For example, the capacity of a reversed lane has been estimated by some to be equal to that of a normal lane while others have theorized it to be half of this value. Without accurate estimates of reversible lane performance it is not possible to confidently gauge the benefits of reversible roadways or model them using traffic simulation. This paper presents the results of a study to measure and evaluate the speed and flow characteristics of reverse‐flow traffic streams by comparing them under various operating conditions and locations. It was found that, contrary to some opinions, the flow characteristics of reverse‐flowing lanes were generally similar to normally flowing lanes under a variety of traffic volume, time‐of‐day, location, and type‐of‐use conditions. The study also revealed that drivers will readily use reversible lanes without diminished operating speeds, particularly as volumes increase. Copyright © 2010 John Wiley & Sons, Ltd.     

Macroscopic modeling of lane‐changing for two‐lane traffic flow

We propose a macroscopic model of lane‐changing that is consistent with car‐following behavior on a two‐lane highway. Using linear stability theory, we find that lane‐changing affects the stable region and the propagation speeds of the first‐order and second‐order waves. In analyzing a small disturbance, our model effectively reproduces certain non‐equilibrium traffic‐flow phenomena—small disturbance instability, stop‐and‐go waves, and local clusters that are affected by lane‐changing. The model also gives the flow‐density relationships in terms of the actual flow rate, the lane‐changing rate, and the difference between the potential flow rate (the flow rate that would have occurred without lane‐changing) and the actual flow rate. The relationships between the actual flow rate and traffic density and between the lane‐changing rate and traffic density follow a reverse‐lambda shape, which is largely consistent with observed traffic phenomena.     

A novel approach for assessing the LOS for two‐lane intercity highways under heterogeneous traffic conditions

Performance of two‐lane intercity highways has been evaluated in terms of level of service (LOS) by different researchers. Different follower‐related performance measures, namely, the number of followers (NF), percent followers (PF), follower density (FD) and the number of followers as a proportion of capacity (NFPC) are examined in the present study to define LOS. Data are collected from five sites located in different parts of India. While almost all the past studies used 3‐s headway rule to identify followers suggested by US Highway Capacity Manual, a new methodology is proposed in the current study to identify the followers by analysing speed difference (SD) and the gap between two consecutive vehicles. It is observed that vehicles travel in non‐following condition after a critical gap threshold value of 10 s. By using a SD limit of ?4 km/h to +10 km/h and a gap value of 10 s, followers are identified across all the study sites. Thereafter, different critical gap values ranging from 1.9 s to 4.3 s are observed at the study sites beyond which the probability of not following would increase. Variation in two‐way traffic volume is found to be the main contributory factor which affects the critical gap values. Among all of the performance measures, NFPC shows a strong correlation with two‐way traffic volume followed by FD under heterogeneous traffic condition. Finally, different threshold values of LOS ranges for two‐lane intercity highways are provided by carrying out cluster analysis with the help of NFPC and FD. Copyright © 2017 John Wiley & Sons, Ltd.     

A Cooperative Intelligent Transport Systems (C‐ITS)‐based lane‐changing advisory for weaving sections

Weaving sections, a common design of motorways, require extensive lane‐change manoeuvres. Numerous studies have found that drivers tend to make their lane changes as soon as they enter the weaving section, as the traffic volume increases. Congestion builds up as a result of this high lane‐changing concentration. Importantly, such congestion also limits the use of existing infrastructure, the weaving section downstream. This behaviour thus affects both safety and operational aspects. The potential tool for managing motorways effectively and efficiently is cooperative intelligent transport systems (C‐ITS). This research investigates a lane‐change distribution advisory application based on C‐ITS for weaving vehicles in weaving sections. The objective of this research is to alleviate the lane‐changing concentration problem by coordinating weaving vehicles to ensure that such lane‐changing activities are evenly distributed over the existing weaving length. This is achieved by sending individual messages to drivers based on their location to advise them when to start their lane change. The research applied a microscopic simulation in aimsun to evaluate the proposed strategy's effectiveness in a one‐sided ramp weave. The proposed strategy was evaluated using different weaving advisory proportions, traffic demands and penetration rates. The evaluation revealed that the proposed lane‐changing advisory has the potential to significantly improve delay. Copyright © 2016 John Wiley & Sons, Ltd.     

Information metrics for improved traffic model fidelity through sensitivity analysis and data assimilation

We develop theoretical and computational tools which can appraise traffic flow models and optimize their performance against current time-series traffic data and prevailing conditions. The proposed methodology perturbs the parameter space and undertakes path-wise analysis of the resulting time series. Most importantly the approach is valid even under non-equilibrium conditions and is based on procuring path-space (time-series) information. More generally we propose a mathematical methodology which quantifies traffic information loss.In particular the method undertakes sensitivity analysis on available traffic data and optimizes the traffic flow model based on two information theoretic tools which we develop. One of them, the relative entropy rate, can adjust and optimize model parameter values in order to reduce the information loss. More precisely, we use the relative entropy rate as an information metric between time-series data and parameterized stochastic dynamics describing a microscopic traffic model. On the other hand, the path-space Fisher Information Matrix, (pFIM) reduces model complexity and can even be used to control fidelity. This is achieved by eliminating unimportant model parameters or their combinations. This results in easier regression of parametric models with a smaller number of parameters.The method reconstructs the Markov Chain and emulates the traffic dynamics through Monte Carlo simulations. We use the microscopic interaction model from Sopasakis and Katsoulakis (2006) as a representative traffic flow model to illustrate this parameterization methodology. During the comparisons we use both synthetic and real, rush-hour, traffic data from highway US-101 in Los Angeles, California.     

Impact of heavy vehicles on surrounding traffic characteristics

This work examines the impact of heavy vehicle movements on measured traffic characteristics in detail. Although the number of heavy vehicles within the traffic stream is only a small percentage, their impact is prominent. Heavy vehicles impose physical and psychological effects on surrounding traffic flow because of their length and size (physical) and acceleration/deceleration (operational) characteristics. The objective of this work is to investigate the differences in traffic characteristics in the vicinity of heavy vehicles and passenger cars. The analysis focuses on heavy traffic conditions (level of service E) using a trajectory data of highway I‐80 in California. The results show that larger front and rear space gaps exist for heavy vehicles compared with passenger cars. This may be because of the limitations in manoeuvrability of heavy vehicles and the safety concerns of the rear vehicle drivers, respectively. In addition, heavy vehicle drivers mainly keep a constant speed and do not change their speed frequently. This work also examines the impact of heavy vehicles on their surrounding traffic in terms of average travel time and number of lane changing manoeuvres using Advanced Interactive Microscopic Simulator for Urban and Non‐Urban Networks (AIMSUN) microscopic traffic simulation package. According to the results, the average travel time increases when proportion of heavy vehicles rises in each lane. To reflect the impact of heavy vehicles on average travel time, a term related to heavy vehicle percentage is introduced into two different travel time equations, Bureau of Public Roads and Akçelik's travel time equations. The results show that using an exclusive term for heavy vehicles can better estimate the travel times for more than 10%. Finally, number of passenger car lane changing manoeuvres per lane will be more frequent when more heavy vehicles exist in that lane. The influence of heavy vehicles on the number of passenger car lane changing is intensified in higher traffic densities and higher percentage of heavy vehicles. Large numbers of lane changing manoeuvres can increase the number of traffic accidents and potentially reduce traffic safety. The results show an increase of 5% in the likelihood of accidents, when percentage of heavy vehicles increases to 30% of total traffic. Copyright © 2014 John Wiley & Sons, Ltd.     

Development of realistic shortest path algorithm considering lane changes

Lane changes occur as many times as turning movements are needed while following a designated path. The cost of a route with many lane changes is likely to be more expensive than that with less lane changes, and unrealistic paths with impractical lane changes should be avoided for drivers' safety. In this regard, a new algorithm is developed in this study to find the realistic shortest path considering lane changing. The proposed algorithm is a modified link‐labeling Dijkstra algorithm considering the effective lane‐changing time that is a parametric function of the prevailing travel speed and traffic density. The parameters were estimated using microscopic traffic simulation data, and the numerical test demonstrated the performance of the proposed algorithm. It was found that the magnitude of the effect of the effective lane‐changing time on determining the realistic shortest path is nontrivial, and the proposed algorithm has capability to exclude links successfully where the required lane changes are practically impossible. Copyright © 2015 John Wiley & Sons, Ltd.     

A microscopic analysis of speed deviation impacts on lane-changing behavior

Driving behavior models that capture drivers’ tactical maneuvering decisions in different traffic conditions are essential to microscopic traffic simulation systems. This paper focuses on a parameter that has a great impact on road users’ aggressive overtaking maneuvers and directly affects lane-changing models (an integral part of microscopic traffic simulation models), namely, speed deviation. The objective of this research is to investigate the impacts of speed deviation in terms of performance measures (delay time, network mean speed, and travel time duration) and the number of lane-change maneuvers using the Aimsun traffic simulator. Following calibration of the model for a section of urban highway in Tehran, this paper explores the sensitivity of lane-changing maneuvers during different speed deviations by conducting two types of test. Simulation results show that, by decreasing speed deviation, the number of lane changes reduces remarkably and so network safety increases, thus reducing travel time due to an increase in network mean speed.     

Accident cost saving and highway attributes

Two semi-logarithmic regression models are developed to estimate accident rates and accident costs, respectively, for rural non-interstate highways in the state of Iowa. Data on 21,224 accidents occurring between 1989 and 1991 on 17,767 road segments are used in the analysis. Seven road attributes of these road segments are included as predictor variables. Applying the resulting regression models to a rather typical highway upgrade situation, the present value of the accident cost saving is computed. The sensitivity of the estimated cost saving to values for fatal, personal injury, and property damage only accidents is tested.Because factors other than road characteristics greatly influence accident costs, the models developed in this research explain a limited amount of the variance in these costs among road segments. Results of the analysis indicate that the most important attribute associated with accident costs is average daily traffic per lane, followed by conditions requiring passing restrictions and the sharpness of curves. Varying the values for the three categories of accidents shows that results are far more sensitive to the value of personal injuries than fatalities. The feasibility of using predictive models of accident costs in benefit-cost analyses of highway investments is demonstrated.     

A multi-criteria decision support methodology for implementing truck operation strategies

This study proposes a multi-criteria decision support methodology to enable the prioritization of potential alternative transportation system operations strategies and then demonstrates the effectiveness of the methodology using a case study involving truck operations. The primary feature of this methodology is its ability to help policymakers consider economic, public, and private sector standpoints simultaneously. The economic criterion is cost to the public sector where four criteria related to truck impacts on the transportation system are incorporated. These are traffic congestion, safety hazards, air pollution, and pavement damage. In addition, reliability and productivity are regarded as metrics representing the private sector viewpoint since they can significantly affect profitability. The methodology combines qualitative and quantitative aspects of these standpoints. In order to demonstrate the applicability of this methodology, a corridor with some of the highest truck traffic in the US is selected as a case study and three forms of left lane restrictions for trucks are considered. For qualitative analysis, survey data were collected from two groups classified as public agency and transportation industry professionals who are experts in trucking. In addition, a micro traffic simulation model was used to produce various performance measurements that can describe quantitative impacts. As a result, the methodology provides a rational argument for prioritizing potential alternative truck strategies.     

Design and evaluation of an automated highway system with optimized lane assignment

Highway automation entails the application of control, sensing and communication technologies to road vehicles, with the objective of improving highway performance. It has been envisioned that automation could increase highway capacity by a factor of three. The purpose of this paper is to develop a methodology for predicting highway capacity and comparing alternative automation concepts. It extends earlier research on optimal lane assignment on an automated highway to dynamic networks. A path-based linear program is formulated and solved through a column generation method. The algorithm has been applied to networks with as many as 20 on and off ramps, 80 segments, 4 lanes and 12 time periods.     

A hybrid controller for autonomous vehicles driving on automated highways

This paper addresses the problem of the hybrid control of autonomous vehicles driving on automated highways. Vehicles are autonomous, so they do not communicate with each other nor with the infrastructure. Two problems have to be dealt with: a vehicle driving in a single-lane highway must never collide with its leading vehicle; and a vehicle entering the highway at a designated entry junction must be able to merge from the merging lane to the main lane, again without any collision. To solve these problems, we equip each vehicle with a hybrid controller, consisting of several continuous control laws embedded inside a finite state automaton. The automaton specifies when a given vehicle must enter the highway, merge into the main lane, yield to other vehicles, exit from the highway, and so on. The continuous control laws specify what acceleration the vehicle must have in order to avoid collisions with nearby vehicles. By carefully designing these control laws and the conditions guarding the automaton transitions, we are able to demonstrate three important results. First, we state the initial conditions guaranteeing that a following vehicle never collides with its leading vehicle. Second, we extend this first result to a lane of autonomous vehicles. Third, we prove that if all the vehicles are equipped with our hybrid controller, then no collision can ever occur, and all vehicles either merge successfully or are forced to drop out when they reach the end of their merging lane. Finally, we show the outcome of a highway microsimulation modelled after the Katy Corridor near Houston, Texas: our single-lane highway can accommodate 4000 vehicles per hour with neither drop-outs nor traffic congestion. It is entirely programmed in SHIFT, a hybrid systems simulation language developed at UC Berkeley by the PATH group. This shows that SHIFT is a well suited language for designing safe control laws for autonomous highway systems, among others.     

Delay-based passenger car equivalents for trucks at signalized intersections

This paper presents a new methodology for computing passenger car equivalents at signalized intersections that is based on the delay concept. Unlike the commonly used headway-based methods that consider only the excess headway consumed by trucks, the delay-based approach fully considers the additional delay heavy vehicles cause on traffic stream. Delay-based passenger car equivalents are not constant, but depend on traffic volume, truck type and truck percentage. The field data indicated that the passenger car equivalents increase as the traffic volume and the percentage of heavy vehicles increase. The field data were used to calibrate TRAF-NETSIM simulation model that was used to cover a broad range of traffic conditions. Mathematical models to estimate the equivalencies were developed. The passenger car equivalent for single unit trucks vary from 1.00 to 1.37, and for combination trucks 1.00–2.18 depending on traffic volume and truck percentage. The passenger car equivalents are highly correlated with traffic volume and, to some degree, with percentage of heavy vehicles. Although the PCE of 1.5 recommended in the 1985 HCM seems to be more reasonable than the 2.0 recommended in the 1994 and 1997 HCM, both overestimate the impact of single unit trucks. For combination trucks, the 1997 HCM overestimates the capacity reduction effects of the trucks in most cases.     

A kinematic wave theory of lane-changing traffic flow

Frequent lane-changes in highway merging, diverging, and weaving areas could disrupt traffic flow and, even worse, lead to accidents. In this paper, we propose a simple model for studying bottleneck effects of lane-changing traffic and aggregate traffic dynamics of a roadway with lane-changing areas. Based on the observation that, when changing its lane, a vehicle affects traffic on both its current and target lanes, we propose to capture such lateral interactions by introducing a new lane-changing intensity variable. With a modified fundamental diagram, we are able to study the impacts of lane-changing traffic on overall traffic flow. In addition, the corresponding traffic dynamics can be described with a simple kinematic wave model. For a location-dependent lane-changing intensity variable, we discuss kinematic wave solutions of the Riemann problem of the new model and introduce a supply–demand method for its numerical solutions. With both theoretical and empirical analysis, we demonstrate that lane-changes could have significant bottleneck effects on overall traffic flow. In the future, we will be interested in studying lane-changing intensities for different road geometries, locations, on-ramp/off-ramp flows, as well as traffic conditions. The new modeling framework could be helpful for developing ramp-metering and other lane management strategies to mitigate the bottleneck effects of lane-changes.