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.     

Traffic signal timing problems with environmental and equity considerations

Traffic signal timings in a road network can not only affect total user travel time and total amount of traffic emissions in the network but also create an inequity problem in terms of the change in travel costs of users traveling between different locations. This paper proposes a multi‐objective bi‐level programming model for design of sustainable and equitable traffic signal timings for a congested signal‐controlled road network. The upper level of the proposed model is a multi‐objective programming problem with an equity constraint that maximizes the reserve capacity of the network and minimizes the total amount of traffic emissions. The lower level is a deterministic network user equilibrium problem that considers the vehicle delays at signalized intersections of the network. To solve the proposed model, an approach for normalizing incommensurable objective functions is presented, and a heuristic solution algorithm that combines a penalty function approach and a simulated annealing method is developed. Two numerical examples are presented to show the effects of reserve capacity improvement and green time proportion on network flow distribution and transportation system performance and the importance of incorporating environmental and equity objectives in the traffic signal timing problems. Copyright © 2013 John Wiley & Sons, Ltd.     

Traffic performance of shared lanes at signalized intersections based on cellular automata modeling

Shared lanes at signalized intersections are designed for use by vehicles of different movement directions. Shared lane usage increases the flexibility of assigning lane grouping to accommodate variable traffic volume by direction. However, a shared lane is not always beneficial as it can at time result in blockage that leads to both capacity and safety constraints. This paper establishes a cellular automata model to simulate traffic movements at signalized intersections with shared lanes. Several simulation experiments are carried out both for a single shared lane and for an approach with a shared lane. Simulation of a single shared lane used by straight‐through and right‐turn (as similar to left‐turn in the USA) vehicles suggests that the largest travel delay occurs when traffic volumes (vehicles/lane) of the two movement streams along the shared lane are at about the same level. For a trial lane‐group with a shared lane, when traffic volumes of the two movement streams are quite different, the shared lane usage is not efficient in terms of reduction in traffic delay. The simulation results are able to produce the threshold traffic volume to arrange a shared lane along an approach. Copyright © 2013 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 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.     

A reliability‐based network design problem

This paper presents a reliability‐based network design problem. A network reliability concept is embedded into the continuous network design problem in which travelers' route choice behavior follows the stochastic user equilibrium assumption. A new capacity‐reliability index is introduced to measure the probability that all of the network links are operated below their capacities when serving different traffic patterns deviating from the average condition. The reliability‐based network design problem is formulated as a bi‐level program in which the lower level sub‐program is the probit‐based stochastic user equilibrium problem and the upper level sub‐program is the maximization of the new capacity reliability index. The lower level sub‐program is solved by a variant of the method of successive averages using the exponential average to represent the learning process of network users on a daily basis that results in the daily variation of traffic‐flow pattern, and Monte Carlo stochastic loading. The upper level sub‐program is tackled by means of genetic algorithms. A numerical example is used to demonstrate the concept of the proposed framework.     

Investigations of interactions between bus rapid transit and general traffic flows

Bus rapid transit (BRT) is a popular strategy to increase transit attraction because of its high‐capacity, comfortable service, and fast travel speed with the exclusive right‐of‐way. Various engineering designs of right‐of‐way and the violation enforcement influence interactions between BRT and general traffic flows. An empirical assessment framework is proposed to investigate traffic congestion and lane‐changing patterns at one typical bottleneck along a BRT corridor. The BRT bottleneck consists of bus lane, BRT station, video enforcement zone, and transit signal priority intersection. We analyze oblique cumulative vehicle counts and oblique cumulative lane‐changing maneuvers extracted from videos. The cumulative vehicle counts method widely applied in revealing queueing dynamics at freeway bottlenecks is extended to an urban BRT corridor. In the study site, we assume four lane‐changing patterns, three of which are verified by the empirical measurements. Investigations of interactions between buses and general traffic show that abnormal behaviors (such as lane violations and slow moving of the general traffic) induce 16% reduction in the saturation rate of general traffic and 17% increase in bus travel time. Further observations show that the BRT station and its induced increasing lane‐changing maneuvers increase the downstream queue discharge flows of general traffic. The empirical results also contribute to more efficient strategies of BRT planning and operations, such as alternative enforcement methods, various lane separation types, and optimized traffic operations. Copyright © 2014 John Wiley & Sons, Ltd.     

Exploring the impact of walk–bike infrastructure,safety perception,and built-environment on active transportation mode choice: a random parameter model using New York City commuter data

This study estimates a random parameter (mixed) logit model for active transportation (walk and bicycle) choices for work trips in the New York City (using 2010–2011 Regional Household Travel Survey Data). We explored the effects of traffic safety, walk–bike network facilities, and land use attributes on walk and bicycle mode choice decision in the New York City for home-to-work commute. Applying the flexible econometric structure of random parameter models, we capture the heterogeneity in the decision making process and simulate scenarios considering improvement in walk–bike infrastructure such as sidewalk width and length of bike lane. Our results indicate that increasing sidewalk width, total length of bike lane, and proportion of protected bike lane will increase the likelihood of more people taking active transportation mode This suggests that the local authorities and planning agencies to invest more on building and maintaining the infrastructure for pedestrians. Further, improvement in traffic safety by reducing traffic crashes involving pedestrians and bicyclists, will increase the likelihood of taking active transportation modes. Our results also show positive correlation between number of non-motorized trips by the other family members and the likelihood to choose active transportation mode. The model would be an essential tool to estimate the impact of improving traffic safety and walk–bike infrastructure which will assist in investment decision making.     

A systematic analysis of multimodal transport systems with road space distribution and responsive bus service

A smart design of transport systems involves efficient use and allocation of the limited urban road capacity in the multimodal environment. This paper intends to understand the system-wide effect of dividing the road space to the private and public transport modes and how the public transport service provider responds to the space changes. To this end, the bimodal dynamic user equilibrium is formulated for separated road space. The Macroscopic Fundamental Diagram (MFD) model is employed to depict the dynamics of the automobile traffic for its state-dependent feature, its inclusion of hypercongestion, and its advantage of capturing network topology. The delay of a bus trip depends on the running speed which is in turn affected by bus lane capacity and ridership. Within the proposed bimodal framework, the steady-state equilibrium traffic characteristics and the optimal bus fare and service frequency are analytically derived. The counter-intuitive properties of traffic condition, modal split, and behavior of bus operator in the hypercongestion are identified. To understand the interaction between the transport authority (for system benefit maximization) and the bus operator (for its own benefit maximization), we examine how the bus operator responds to space changes and how the system benefit is influenced with the road space allocation. With responsive bus service, the condition, under which expanding bus lane capacity is beneficial to the system as a whole, has been analytically established. Then the model is applied to the dynamic framework where the space allocation changes with varying demand and demand-responsive bus service. We compare the optimal bus services under different economic objectives, evaluate the system performance of the bimodal network, and explore the dynamic space allocation strategy for the sake of social welfare maximization.     

Evaluating the effects of automated vehicle technology on the capacity of freeway weaving sections

Weaving sections, where a merge and a diverge are in close proximity, are considered as crucial bottlenecks in the highway network. Lane changes happen frequently in such sections, leading to a reduced capacity and the traffic phenomenon known as capacity drop. This paper studies how the emerging automated vehicle technology can improve the operations and increase the capacity of weaving sections. We propose an efficient yet effective multiclass hybrid model that considers two aspects of this technology in scenarios with various penetration rates: (i) the potential to control the desired lane change decisions of automated vehicles, which is represented in a macroscopic manner as the distribution of lane change positions, and (ii) the lower reaction time associated with automated vehicles that can reduce headways and the required gaps for lane changing maneuvers. The proposed model is successfully calibrated and validated with empirical observations from conventional vehicles at a weaving section near the city of Basel, Switzerland. It is able to replicate traffic dynamics in weaving sections including the capacity drop. This model is then applied in a simulation-based optimization framework that searches for the optimal distribution of the desired lane change positions to maximize the capacity of weaving sections. Simulation results show that by optimizing the distribution of the desired lane change positions, the capacity of the studied weaving section can increase up to 15%. The results also indicate that if the reaction time is considered as well, there is an additional combined effect that can further increase the capacity. Overall, the results show the great potential of the automated vehicle technology for increasing the capacity of weaving sections.     

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.     

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.     

Modeling and solving discrete network design problem with stochastic user equilibrium

In this paper, we address the discrete network design problem, which determines the addition of new roads to existing transportation network to optimize the transportation system performance. Road users are assumed to follow the traffic assignment principle of stochastic user equilibrium. A mixed‐integer nonlinear nonconvex problem is developed to model this discrete network design problem with stochastic user equilibrium. The original problem is relaxed into a convex mixed‐integer nonlinear program, whose solution provides a lower bound of the original problem. The relaxed problem is then embedded into two proposed global optimization solution algorithms to obtain the global optimal solution of the problem. Copyright © 2016 John Wiley & Sons, Ltd.     

A methodology to control urban traffic noise under the constraint of environmental capacity: A case study of a double-decision optimization model

This paper presents a novel methodology to control urban traffic noise under the constraint of environmental capacity. Considering the upper limits of noise control zones as the major bottleneck to control the maximum traffic flow is a new idea. The urban road network traffic is the mutual or joint behavior of public self-selection and management decisions, so is a typical double decision optimization problem.The proposed methodology incorporates theoretically model specifications. Traffic noise calculation model and traffic assignment model for O–D matrix are integrated based on bi-level programming method which follows an iterated process to obtain the optimal solution. The upper level resolves the question of how to sustain the maximum traffic flow with noise capacity threshold in a feasible road network. The user equilibrium method is adopted in the lower layer to resolve the O–D traffic assignment.The methodology has been applied to study area of QingDao, China. In this illustrative case, the noise pollution level values of optimal solution could satisfy the urban environmental noise capacity constraints. Moreover, the optimal solution was intelligently adjusted rather than simply reducing the value below a certain threshold. The results indicate that the proposed methodology is feasible and effective, and it can provide a reference for a sustainable development and noise control management of the urban traffic.     

A continuous-flow-intersection-lite design and traffic control for oversaturated bottleneck intersections

Oversaturation has become a severe problem for urban intersections, especially the bottleneck intersections that cause queue spillover and network gridlock. Further improvement of oversaturated arterial traffic using traditional mitigation strategies, which aim to improve intersection capacity by merely adjusting signal control parameters, becomes challenging since exiting strategies may (or already) have reached their “theoretical” limits of optimum. Under such circumstance, several novel unconventional intersection designs, including the well-recognized continuous flow intersection (CFI) design, are originated to improve the capacity at bottleneck intersections. However, the requirement of installing extra sub-intersections in a CFI design would increase vehicular stops and, more critically, is unacceptable in tight urban areas with closed spaced intersections. To address these issues, this research proposes a simplified continuous flow intersection (called CFI-Lite) design that is ideal for arterials with short links. It benefits from the CFI concept to enable simultaneous move of left-turn and through traffic at bottleneck intersections, but does not need installation of sub-intersections. Instead, the upstream intersection is utilized to allocate left-turn traffic to the displaced left-turn lane. It is found that the CFI-Lite design performs superiorly to the conventional design and regular CFI design in terms of bottleneck capacity. Pareto capacity improvement for every traffic stream in an arterial system can be achieved under effortless conditions. Case study using data collected at Foothill Blvd in Los Angeles, CA, shows that the new design is beneficial in more than 90% of the 408 studied cycles. The testing also shows that the average improvements of green bandwidths for the synchronized phases are significant.     

Categorization of the lane change decision process on freeways

Traffic operations for new road layouts are often simulated using microscopic traffic simulation packages. These traffic simulation packages usually simulate traffic on freeways by a combination of a car-following model and a lane change model. The car-following models have gained attention of researchers and are well calibrated versus data. The proposed lane change models are often representations of assumed reasonable behavior, not necessarily corresponding to reality. The current simulation packages apply solely one specific type of model for car-following or lane changing for all vehicles during the simulation. This paper investigates the decision process of lane changing maneuvers for a variety of drivers based on a two-stage test-drive. Participants are asked to take a drive on a freeway in the Netherlands in a camera-equipped vehicle. Afterwards, the drivers are asked to comment on their choices related to lane and speed choice, while watching the video. This paper reveals that different drivers have completely different strategies to choose lanes, and the choices to change lane are related to their speed choice. Four distinct strategies are empirically found. These strategies differ not only in parameter values, as is currently being modeled in most simulation packages, but also in their reasoning. Most remarkably, all drivers perceive their strategy as an obvious behavior and expect all other drivers to drive in a similar way. In addition to the interviews of the participants in the test-drive, 11 people who did not take part in the experiment were interviewed and questioned on lane change decisions. Moreover, the findings of this study have been presented to various groups of audience with different backgrounds (about 150 people). Their comments and feedback on the derived driving strategies have added some value to this study. The findings in this paper form a starting point for developing a novel lane change model which considers four different driving strategies among the drivers on freeway. This is a significant contribution in the area of driving behavior modeling, since the existing microscopic simulators consider only one type of lane change models for all drivers during the simulation. This could lead to significant changes in the way lane changes on freeways are modeled.     

Hybrid artificial neural network and locally weighted regression models for lane-based short-term urban traffic flow forecasting

ABSTRACT

In recent years, there has been considerable research interest in short-term traffic flow forecasting. However, forecasting models offering a high accuracy at a fine temporal resolution (e.g. 1 or 5?min) and lane level are still rare. In this study, a combination of genetic algorithm, neural network and locally weighted regression is used to achieve optimal prediction under various input and traffic settings. The genetically optimized artificial neural network (GA-ANN) and locally weighted regression (GA-LWR) models are developed and tested, with the former forecasting traffic flow every 5-min within a 30-min period and the latter for forecasting traffic flow of a particular 5-min period of each for four lanes of an urban arterial road in Beijing, China. In particular, for morning peak and off-peak traffic flow prediction, the GA-ANN 5-min traffic flow model results in average errors of 3–5% and most 95th percentile errors of 7–14% for each of the four lanes; for the peak and off-peak time traffic flow predictions, the GA-LWR 5-min traffic flow model results in average errors of 2–4% and most 95th percentile errors are lower than 10% for each of the four lanes. When compared to previous models that usually offer average errors greater than 6–15%, such empirical findings should be of interest to and instrumental for transportation authorities to incorporate in their city- or state-wide Advanced Traveller Information Systems (ATIS).     

Dynamic user equilibrium with side constraints for a traffic network: Theoretical development and numerical solution algorithm

This paper investigates a traffic volume control scheme for a dynamic traffic network model which aims to ensure that traffic volumes on specified links do not exceed preferred levels. The problem is formulated as a dynamic user equilibrium problem with side constraints (DUE-SC) in which the side constraints represent the restrictions on the traffic volumes. Travelers choose their departure times and routes to minimize their generalized travel costs, which include early/late arrival penalties. An infinite-dimensional variational inequality (VI) is formulated to model the DUE-SC. Based on this VI formulation, we establish an existence result for the DUE-SC by showing that the VI admits at least one solution. To analyze the necessary condition for the DUE-SC, we restate the VI as an equivalent optimal control problem. The Lagrange multipliers associated with the side constraints as derived from the optimality condition of the DUE-SC provide the traffic volume control scheme. The control scheme can be interpreted as additional travel delays (either tolls or access delays) imposed upon drivers for using the controlled links. This additional delay term derived from the Lagrange multiplier is compared with its counterpart in a static user equilibrium assignment model. If the side constraint is chosen as the storage capacity of a link, the additional delay can be viewed as the effort needed to prevent the link from spillback. Under this circumstance, it is found that the flow is incompressible when the link traffic volume is equal to its storage capacity. An algorithm based on Euler’s discretization scheme and nonlinear programming is proposed to solve the DUE-SC. Numerical examples are presented to illustrate the mechanism of the proposed traffic volume control scheme.     

Multilane first-order traffic flow model with endogenous representation of lane-flow equilibrium

In this study, we develop a multilane first-order traffic flow model for freeway networks. In the model, lane changing is considered as a stochastic behavior that can decrease an individual driver’s disutility or cost, and is represented as dynamics toward the equilibrium of lane-flow distribution along with longitudinal traffic dynamics. The proposed method can be differentiated from those in previous studies because in this study, the motivation of lane changing is explicitly considered and it is treated as a utility defined by the current macroscopic traffic state. In addition, the entire process of lane changing is computed macroscopically by an extension of the kinematic wave theory employing IT principle; moreover, in the model framework, the lane-flow equilibrium curve is endogenously generated because of self-motivated lane changes. Furthermore, the parsimonious representation enables parameter calibration using the data collected from conventional loop detectors. The calibration of the data collected at four different sites, including a sag bottleneck, on the Chugoku expressway in Japan reveals that the proposed method can represent the lane-flow distribution of any observation site with high accuracy, and that the estimated parameters can reasonably explain the multilane traffic dynamics and the bottleneck phenomena uphill of sag sections.