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Solving the practical train timetabling problem under complex real-life train operation environment is challenging. This article addresses the train timetabling problem considering the variant para...

Headway of vehicles during platoon dispersion at signalized intersection is one of the critical microscopic traffic characteristics in traffic flow theory. The distribution of the discharge headways of vehicles also has a significant impact on the traffic generation process in most of the microsimulation approaches. However, few studies have investigated the vehicle discharge headway for interrupted flow at signalized intersections under mixed traffic conditions. The present study uses data collected from 20 intersections in six cities for comprehensive analysis of discharge headway. A box-and-whiskers plot is generated for discharge headway to quantify its reasonable profile. The diagram shows that headway of vehicles decreases with the queue dispersion. A stable headway can be observed after the fifth vehicle position of a queue, giving a saturation headway of 2.05 s per vehicle. Six types of continuous distribution are tested to model the discharge headway distribution. A statistical investigation is also performed to verify the best-fitted model for each vehicle position in a queue. The ranking of a best-fitted distribution is done for each vehicle position as per the statistical significance. This study demonstrates the discharge headway characteristics and distribution at each vehicle position, which can be useful for traffic flow analysis and especially for improving microsimulation models.

The regulation of a monopolistic public transit operator whose marginal cost is unknown to the regulator is studied in this paper. We contribute to the transit regulation literature by presenting an incentive-compatible (IC) regulatory policy with consideration of the decision interactions between the regulator and transit operator under asymmetric information. The regulator only has some subjective prior probability distribution for the unknown marginal cost before designing regulatory policies (i.e., probability of permitting operations, maximum fare, maximum headway, and subsidy amount) to maximize the expected social welfare over the unknown cost. The operator with privately held cost information optimizes its fare and headway decisions subject to regulatory policies. The proposed IC policy is derived analytically, which gives the operator no incentive to misrepresent its cost. We compare regulations under symmetric information versusasymmetric information, and measure the deadweight loss due to the information asymmetry. The proposed IC policy is also compared with a benchmark policy, which is based on the cost expected by the regulator, to demonstrate its superiority. We find: (1) solutions under asymmetric information can be reproduced by solving the regulation problem under symmetric information with an enlarged marginal cost; (2) a regulator adopting the benchmark policy may set fare and headway limits above the levels selected by a profit-maximizing monopolistic operator. This study improves the state of the artin public transit regulation by presenting an effective tool for designing IC regulatory policies.

The cost associated with the waiting time that passengers incur in a public transit network is one of the main components of total transit travel cost. The cost of a unit of waiting time per passen...

This paper proposes a bi-objective multi-period bus headway setting problem while considering the influence of electronic bus station boards on passengers’ choice behaviour. A non-dominated sorting...

Textbooks used in foreign language instruction cannot be simply separated from cultural contexts because the mere study of the abstract system of language does not equip learners with the required ...

Purpose This study aims to propose a speed guidance model of the CV environment to alleviate traffic congestion at intersections and improve traffic efficiency. By introducing the theory of moving block section for high-speed train control, a speed guidance model based on the quasi-moving block speed guidance (QMBSG) is proposed to direct platoon including human-driven vehicles and connected vehicles (CV) through the intersection coordinately. Design/methodology/approach In this model, the green time of the intersection is divided into multiple block intervals according to the minimal safety headway. Connected vehicles can pass through the intersection by following the block interval using the QMBSG model. The block interval is assigned dynamically according to the traveling relation of HV and CV, when entering the communication range of the intersection. To validate the comprehensive guidance effect of the proposed model, a general evaluation function (GEF) is established. Compared to CVs without speed guidance, the simulation results show that the GEF of QMBSG model has an obvious improvement. Findings Compared to CVs without speed guidance, the simulation results show that the GEF of QMBSG model has an obvious improvement. Also, compared to the single intersection speed guidance model, the GEF value of the QMBSG model improves over 17.1%. To further explore the guidance effect, the impact of sensitivity factors of the CVs’ environment, such as intersection environment, communication range and penetration rate (PR) is analyzed. When the PR reaches 75.0%, the GEF value will change suddenly and the model guidance effect will be significantly improved. This paper also analyzes the impact of the length of block interval under different PR and traffic demands. It is found that the proposed model has a better guidance effect when the length of the block section is 2 s, which facilitates traffic congestion alleviation of the intersection in practice. Originality/value Based on the aforementioned discussion, the contributions of this paper are three-fold. Based on the traveling information of HV/CV and the signal phase and timing plans, the QMBSG model is proposed to direct platoon consisting of HV and CV through the intersection coordinately, by following the block interval assigned dynamically. Considering comprehensively the indexes of mobility, safety and environment, a GEF is provided to evaluate the guidance effect of vehicles through the intersection. Sensitivity analysis is carried out on the QMBSG model. The key communication and traffic parameters of the CV environment are analyzed, such as path attenuation, PR, etc. Finally, the effect of the length of block interval is explored.

The estimation of the free flow speed (FFS) distribution is important for capacity analysis, determination of the level-of-service, and setting speed limits. Subjective time headway thresholds have been commonly used to identify vehicles travelling under free flow speed conditions i.e., vehicles whose speeds are not influenced by the vehicle in front. Since, the headway a driver operates under the free flow state is subjective and varies from driver to driver, such approaches can introduce biases in the FFS estimation. Therefore, in this paper a parametric probabilistic latent approach is proposed based on discrete choice utility theory to estimate the FFS distribution on urban roads and simultaneously the probability that drivers perceive their state as constrained by the vehicle in front. This methodology is used to estimate the impacts of road characteristics and Posted Speed Limit (PSL) changes on the FFS distribution using an extensive dataset of speed observations from urban roads with varying characteristics. The results show that the simultaneous estimation of the free flow speed distribution and the state the driver is in (e.g., free or constrained) is feasible. The analysis indicates that the FFS is influenced by several road characteristics such as land use, on-street parking and the presence of sidewalks. The PSL change impacts not only the distribution of the free flow vehicles but also the speed distribution of the constrained vehicles. The constrained probabilities vary depending on the PSL change with higher probabilities for lower speed limits.

Optimal velocity (OV)-based car-following model can be easily applied to the transportation system composed of intelligent connected vehicle (ICV) via vehicle-to-vehicle (V2V) communication, since this model only requires space headway and velocity differences of preceding vehicles. However, the sudden velocity changes of the leading vehicle will decrease the control performance of following vehicles. Particularly, the farther the distance between the following vehicle and the leading vehicle is, the worse the control performance of the following vehicle is. Besides this problem, the nonlinear information of OV-based car-following models is often not fully utilized due to the linearization for the convenience of stability analysis and controller design. To address these problems, the factors related to velocity sudden changes are taken into account for each ICV simultaneously and compensated by the proposed feedforward compensator. Based on the compensator, a finite-time traffic flow controller is designed for each ICV to smooth the space headway in traffic flow subject to sudden velocity changes and make full use of the nonlinear information of OV-based model. Finally, the theoretical analysis via Lyapunov approach and the numerical simulations are carried out to verify the effectiveness of the proposed method.

Humanitarian disasters are highly dynamic and uncertain. The shifting situation, volatility of information, and the emergence of decision processes and coordination structures require humanitarian organizations to continuously adapt their operations. In this study, we aim to make headway in understanding adaptive decision-making in a dynamic interplay between changing situation, volatile information, and emerging coordination structures. Starting from theories of sensemaking, coordination, and decision-making, we present two case studies that represent the response to two different humanitarian disasters: Typhoon Haiyan in the Philippines, and the Syria Crisis, one of the most prominent ongoing conflicts. For both, we highlight how volatile information and the urge to respond via sensemaking lead to fragmentation and misalignment of emergent coordination structures and decisions, which, in turn, slow down adaptation. Based on the case studies, we derive propositions and the need to continuously align laterally between different regions and hierarchically between operational and strategic levels to avoid persistence of coordination-information bubbles. We discuss the implications of our findings for the development of methods and theory to ensure that humanitarian operations management captures the critical role of information as a driver of emergent coordination and adaptive decisions.

Electrical task balancing counts have advanced fundamentally, from distorted figurings like initially start things out serve, to bio-impelled and AI estimations like Q-learning and genetic computations. The main objective of any task altering computation is to constrain the number of execution cycles expected to absolutely and satisfactorily execute a given course of action of endeavors. During this work, we reviewed the unmistakable endeavor altering count which relies upon an improved differential headway (IDE) strategy. The proposed assessment endeavors to accept the shifted nuances of Electrical endeavor modifying, which join task length, task satisfaction time, virtual machine arrangement, and task cut-off time. Also, the arranged estimation is shaped holder all around arranged, which ensures that the scheduler works satisfactorily on a compartment circumstance to upgrade the efficiency of the electrical plan. We study these systems and discover the most straightforward one for assessment and review.

With the rising energy prices and increasing environmental awareness, the energy efficiency of metro transit system has attracted much attention in recent years. This study proposes a two-step optimisation method to optimise speed profile and timetable, aiming to reduce the operational energy consumption of metro transit system. First, a coasting point searching algorithm is designed to reduce tractive energy consumption by optimising speed profile and running time distribution scheme. Then, a mixed-integer linear programming model is constructed to maximise the overlap time between the accelerating and braking phases by optimising headway and dwell time, in order to improve the utilisation of regenerative braking energy (RBE). Furthermore, numerical simulations are presented based on the data from a Guangzhou Metro Line. The results show that the tractive energy consumption can be reduced by 8.46% and the utilisation of RBE can be improved by 11.6%.

The headway-based control method is usually used to regulate the bus headways and improve reliability of public transit. In general, the holding control strategy is applied at the control point, because enough space for dwell longer at the control point is required, while the stop-skipping control strategy can be used at any bus stop. However, in the headway-based control method, too much stop-skipping will bring longer waiting time and make the passengers impatient. The number and distribution of control points for stop-skipping are not considered in previous self-equalizing bus headway control works. Therefore, in this paper, the control points selection rules for stop-skipping involving their number and distribution on the bus route are discussed. A second by second discrete system is formulated to describe the bus operation. In the proposed control method, the threshold value for activating stop-skipping strategy is raised, avoiding provoking much additional waiting time because of boarding rejected. In the numerical analysis, a set of cases are conducted to evaluate the performance of control method under different number and distribution of control points for stop-skipping. The numerical results show that distribution of control points for stop-skipping has a greater influence on the public transit than the number.

Recent advances in artificial intelligence and wireless communication technologies have created great potential to reduce congestion in urban networks. In this research, we develop a stochastic analytical model for optimal control of communicant autonomous vehicles (CAVs) at smart intersections. We present the automated network fundamental diagram (ANFD) as a macro-level modeling tool for urban networks with smart intersections. In the proposed cooperative control strategy, we make use of the headway between the CAV platoons in each direction for consecutive passage of the platoons in the crossing direction through non-signalized intersections with no delay. For this to happen, the arrival and departure of platoons in crossing directions need to be synchronized. To improve system robustness (synchronization success probability), we allow a marginal gap between arrival and departure of the consecutive platoons in crossing directions to make up for operational error in the synchronization process. We then develop a stochastic traffic model for the smart intersections. Our results show that the effects of increasing the platoon size and the marginal gap length on the network capacity are not always positive. In fact, the capacity can be maximized by optimizing these cooperative control variables. We analytically solve the traffic optimization problem for the platoon size and marginal gap length and derive a closed-form solution for a normal distribution of the operational error. The performance of the network with smart intersections is presented by a stochastic ANFD, derived analytically and verified numerically using the results of a simulation model. The simulation results show that optimizing the control variables increases the capacity by 138% when the error standard deviation is 0.1 s.

Owing to environmental concerns, the energy-efficient subway train scheduling problem is necessary in subway operation management. This paper designs an approximate dynamic programming (DP) approach for energy-efficient subway train scheduling problem with time-dependent demand. The train traffic model is proposed with the dynamic equations for the evolution of train headway, train passenger loads, and the energy consumption along the subway line. For the dynamic changing of the onboard passengers with time, the total train energy usage is modeled as the sum of energy consumptions from the traction system and auxiliary facilities. A nonlinear DP problem is formulated to generate a near optimal timetable to realize the tradeoff among the utilization of trains, passenger waiting time, service levels, and energy consumption. To overcome the curse of dimensionality in this optimization problem, we construct an approximate DP framework, where the conceptions of states, policies, state transitions, and reward function are introduced. And this algorithm is able to converge to a good solution with a short time compared to the genetic algorithm and differential evolution algorithm. Finally, the numerical experiments are given to demonstrate the effectiveness of the proposed model and algorithm.

Aiming at solving a typical problem of past research using accident experience statistics of being unable to adapt to changing traffic flows, this paper provides an evaluation method of the risk of vehicle rear-end collisions at red-light-camera (RLC) intersections based on theoretical probabilities. Taking advantage of trajectory data of vehicles at the two similar intersections, which are Cao’an Road and Lvyuan Road with RLCs and Cao’an Road and Anhong Road without RLCs in Shanghai, a binary logit (BL) model of stop-and-go decision-making is established. Using the model and adjusting the headway and potential travel time, we can perform simulation and analysis of rear-end collisions. The result shows that this method is feasible to analyse the influence of RLCs on rear-end collisions. The analysis indicates that RLCs can cause higher speeds for vehicles passing the RLC intersection and more abnormal driving behaviors, which increase the difficulty of stop-and-go decision-making. RLCs do not always lead to an increase of rear-end collisions. For vehicles close to or far from intersection at the decision-making time, RLCs will significantly reduce the possibility of rear-end collisions; however, for vehicles in the potential travel time of 2 s∼3 s, RLCs will increase the probability of rear-end collisions.

This paper is concerned with the communicative approach in learning a foreign language including the problems that followed the empirical appliciation of this approach, especially in the domain of learning English as a foreign language, as well as the attempts to identify and overcome its limitations. The analytical aspect of learning has been given the central attention here, which is why the theoretical review is followed by considering the justification and necessity of its inlusion using the Headway coursebooks as an example. The analysis has covered three particular levels of learning mirrored in the titles: Headway Intermediate , Headway Upper-intermediate and Headway Advanced , which corresponds with the standardised levels from B1 to C1 in Europe. Our discussion is concentrated primarily on teaching English as a second language at the university level, so the analytical approach is looked upon mainly in the context of teaching students at different departments of philology. But the implications of using this model reach much further than university teaching as Headway coursebooks have been used both in private and state schools throughout Serbia, as well as around the world. A very consistent insistence on using the analytical approach is a special characteristic of these coursebooks and certainly something that sets them apart from many other similar coursebooks available on the market. The pedagogical and methodological aspects of this approach are such that leave space to the teacher to make use of the advantages of occasional contrastive analysis with the two languages – English and the native language of the student (and/or the first foreign language) – drawing attention to those areas of English which have proved most difficult regardless of what particular native language the student speaks. This is why the analytical approach has shown to be of such crucial importance as well as encouraging the student to see that acquiring language skills is neccesarily related to how well he understands the inner logic and mechanisms of the language itself. Last but not least, it gives the student a possibility to see learning as a meaningful process – one in which this competence has proved to be a neccesary and an extremely significant aspect.

According to the models which are commonly used in practice, the capacity of roundabouts depends on the value of critical headway. Critical headway size depends on numerous objective factors, primarily on geometric characteristics of the intersection. However, research so far have shown that beside characteristics of the intersection, value of critical headway depends on many other factors, primarily on driver behavior. Driver behavior is the result of the action of numerous factors that depend on the influence of local environment, habits, mentality, etc. For that very reason, determination of the value of this traffic flow parameter in local research is recommended in many models. Within this paper, the results related to the value of critical headway determined by research which are conducted in Bosnia and Herzegovina are presented. The presented value of critical headway can be used for objective determination of roundabout capacity in our region.

Driving simulation is an efficient, safe, and data-collection-friendly method to examine driving behavior in a controlled environment. However, the validity of a driving simulator is inconsistent when the type of the driving simulator or the driving scenario is different. The purpose of this research is to verify driving simulator validity in driving behavior research in work zones. A field experiment and a corresponding simulation experiment were conducted to collect behavioral data. Indicators such as speed, car-following distance, and reaction delay time were chosen to examine the absolute and relative validity of the driving simulator. In particular, a survival analysis method was proposed in this research to examine the validity of reaction delay time. The result indicates the following: (1) most indicators are valid in driving behavior research in the work zone. For example, spot speed, car-following distance, headway, and reaction delay time show absolute validity. (2) Standard deviation of the car-following distance shows relative validity. Consistent with previous researches, some driving behaviors appear to be more aggressive in the simulation environment.

Purpose The purpose of this paper is to explore the impact of the mixed traffic flow, self-stabilization effect and the lane changing behavior on traffic flow stability. Design/methodology/approach An extended two-lane lattice hydrodynamic model considering mixed traffic flow and self-stabilization effect is proposed in this paper. Through linear analysis, the stability conditions of the extended model are derived. Then, the nonlinear analysis of the model is carried out by using the perturbation theory, the modified Kortweg–de Vries equation of the density of the blocking area is derived and the kink–antikink solution about the density is obtained. Furthermore, the results of theoretical analysis are verified by numerical simulation. Findings The results of numerical simulation show that the increase of the proportion of vehicles with larger maximum speed or larger safe headway in the mix flow are not conducive to the stability of traffic flow, while the self-stabilization effect and lane changing behavior is positive to the alleviation of traffic congestion. Research limitations/implications This paper does not take into account the factors such as curve and slope in the actual road environment, which will have more or less influence on the stability of traffic flow, so there is still a certain gap with the real traffic environment. Originality/value The existing two-lane lattice hydrodynamic models are rarely discussed in the case of mixed traffic flow. The improved model proposed in this paper can better reflect the actual traffic, which can also provide a theoretical reference for the actual traffic governance.

Connected cruise control (CCC), as an approach to regulate vehicle’s longitudinal motion in car-following platoon scenarios, can improve the safety and efficiency of the traffic flow. In order to make it available for extensive information sharing among vehicles, wireless vehicle-to-vehicle (V2V) communication is exploited in the vehicular platoon. However, time delays caused by wireless communication may result in significant degradation of system stability. In this article, considering arbitrary V2V communication delays, an optimal longitudinal control algorithm is proposed for the CCC vehicle with the goal of minimizing the deviations of vehicle’s headway and velocity. In the proposed scheme, the vehicular platoon is modeled as a discrete-time system based on vehicle’s error dynamics, and the optimal-state feedback control problem is designed as a cost function represented by a sum of platoon states in a quadratic form. A backward recursion method is used to iteratively derive the optimal control strategy, namely the acceleration for CCC vehicle, based on the current platoon states and previous control signals. In addition, the stability analysis shows that the system is asymptotically mean square stable under the control of the proposed algorithm. Finally, numerical simulations indicate that the proposed algorithm provides better system performance and stability.

This study estimated composite headway distributions consisting of follower and non-follower headway elements and used the follower percentage obtained as the estimated parameters of those distributions to evaluate the quality of service (QOS) of traffic flow on Japanese intercity expressways under uncongested conditions. Analysis of pulse data obtained by vehicle detectors at multiple points with differing geometric structures showed that follower percentage is influenced by lane traffic volume, vehicle pair, and lane operation. Use of follower percentage also enabled clear and quantitative comparison and evaluation of the QOS of traffic flow for different lane operation formats, which could not be adequately expressed by such conventional macroscopic indices as average speed and traffic density. This indicates that follower percentage is a suitable performance measure for evaluating the QOS of traffic flow.

Recently, simulation models have been widely used around the world to evaluate the performance of different traffic facilities and management strategies for efficient and sustainable transportation systems. One of the keys factors for ensuring the reliability of the models in reflecting local conditions is the calibration and validation of microsimulation models. The majority of the existing calibration efforts focus is on the experimental designs of driver behaviour and lane-changing parameters. Towards this end, this paper describes the necessary procedure for the calibration and validation of a microscopic model using the VISSIM software, during peak hours. The procedure is applied on Muscat Expressway in the Sultanate of Oman. The calibration parameters and the measure-of-effectiveness are identified by using multi-parameter sensitivity analysis. The optimum values for these parameters are obtained by minimising errors between simulated data and field data. In our proposed model, we used traffic volume and travel speed for model calibration, as well as average travel time for validation of the calibrated model. The achieved results showed that driving characteristics significantly impacted the merging/diverging traffic flow ratio in the merging area, the link length and the distance between on-ramps and off-ramps, as well as the percentage of heavy vehicles. The results also showed that having both the advanced merging and cooperative lane-change settings active, along with safety distance reduction factor, necessary lane change, minimum headway (front/rear), and emergency stop, had a significant influence on simulation precision, especially at on-ramps and off-ramps. Finally, our proposed model can be utilized as a base for future traffic strategy analysis and intelligent transportation systems evaluation to help decision makers with long-term and sustainable development decisions.

It is a common practice for transit lines with fluctuating passenger demands to use demand-driven bus scheduling to reduce passenger waiting time and avoid bus overcrowding. However, current literature on the demand-driven bus scheduling generally assumes fixed bus capacity and exclusively optimizes bus dispatch headways. With the advent of connected and autonomous vehicle technology and the introduction of autonomous minibus/shuttle, the joint design of bus capacity and dispatch headway holds promises to further improving the system efficiency while reducing operating and passenger costs. This paper formulates this problem as an integer nonlinear programming model for transit systems operating with mixed human-driven and autonomous buses. In such mixed operating environment, the model simultaneously considers: (1) dynamic capacity design of autonomous bus, i.e., autonomous buses with varying capacity can be obtained by assembling and/or dissembling multiple autonomous minibuses; (2) trajectory control of autonomous bus, i.e., autonomous bus can dynamically adjust its running time as a function of its forward and backward headways; and (3) stop-level passenger boarding and alighting behavior. The objective of the model is designed to balance the trade-off between the operating costs of dispatching different types of bus and the costs of increased passenger waiting time due to inadequate bus dispatching. The model is solved using a dynamic programming approach. We show that the proposed model is effective in reducing passenger waiting time and total operating cost. Sensitivity analysis is further conducted to explore the impact of miscellaneous factors on optimal dispatching decisions, such as penetration rate of autonomous bus, bus running time variation, and passenger demand level.

Women have made considerable progress in terms of their entrance into the legal profession, such that they are advancing towards parity with men on the High Court benches in Nigeria. This study is ...

The effects of a package intervention including prompts, goal setting, feedback, education, and behavioral self-monitoring to increase following headway (decrease tailgating) of three young drivers...

The paper presents a new methodology for computing e-bikes equivalents at urban signalized intersections to meet the road spatial demand of e-bikes. By analyzing the measured traffic data of two-phase and four-phase signalized intersections, it is determined that the delay method and the headway method are not applicable to the e-bike Passage Car Equipment (PCE) calculation at intersections. An improved PCE calculation model based on the number of conflict events, speed and traffic volume calculated was established. It is determined that the PCE of left-turning, straight-through and right-turning of e-bikes at two-phase and four-phase signalized intersections are 0.27, 0.34, 0.25 and 0.29, 0.34, 0.27 respectively, and that the variation trend of PCE each turning directions at intersections is different from that of motor vehicles. By analyzing the generation mechanism of the PCE values, it is found that the proposed PCE values of each turning directions have changed reasonably. Compared to the pre-improved model, the traffic capacity calculated by the PCE proposed in this paper is found to be closer to the actual capacities.

Randomness affecting the operation of public transport systems generates significant increments in waiting times. A strategy to deal with this randomness is bus injection, in which buses are kept in specific points along the route ready to be dispatched when an event such as an extremely long headway occurs. In this work, a stochastic model based on the second moment of the headways distribution is developed to determine if one or more buses are worth reserving for injection in a public transport service. A single stop approach is initially used to determine an expression for the optimal headway threshold triggering the injection. Then, a model for the complete service is developed and used to determine when the empty bus should be injected within the headway once the decision to inject it has been taken. We show that the bus should be injected approximately when 57% of the headway has passed. Simulations with real data are used to test the proposed model, proving its accuracy in terms of measuring the impact on waiting times. The results show that reserving a bus to be injected can be better than operating the entire fleet continuously.

Purpose Practitioners and researchers have reached a consensus that supply chain analytics is a strong determinant for desirable organizational outcomes such as supply chain performance and agility. The purpose of this paper is to examine a configural combination (i.e. causal recipes) subsuming supply chain data analytics, firmsize, age and annual sales to predict supply chain agility based on knowledge-based theory. Design/methodology/approach Survey data (n = 215) were obtained from firms operating in the United Arab Emirates. Consequently, fuzzy sets qualitative comparative analysis (fsQCA) technique was applied to the data to establish causal recipes that are necessary and sufficient to achieve high scores of supply chain agility. Findings Results from fsQCA support the major tenets of complexity theory that several configural combinations (i.e. supply chain data analytics, firm size, firm age and annual sales) are sufficient and necessary conditions for achieving higher scores of supply chain agility. Originality/value This study is first of its kind in understanding the association between supply chain data analytics and agility with fsQCA technique. This research also offers a headway for supply chain managers in identifying configural combinations of antecedents manifesting high scores for supply chain agility. Implications for theory and practice are illustrated as well as future research course.

In this paper, an adaptive neuro-fuzzy predictor-based control (ANFPC) approach with integrated automotive radar and vehicle-to-vehicle (V2V) communication for the design of the cooperative adaptive cruise control (CACC) system is presented, which concerns not only the safety and riding comfort of a vehicle but also enhances its fuel efficiency. This paper consists of two main parts: preceding vehicle state estimation and following vehicle controller. First, the prospective information of the preceding vehicle, such as position, velocity, and acceleration, can be derived through radar sensor, and the control force of the preceding vehicle can be transmitted to the following vehicles through V2V communication. A Takagi–Sugeno fuzzy model is then utilized to estimate the preceding vehicle model, and the predicted state sequence of the preceding vehicle can be obtained. Second, based on these predicted data, the following vehicle is controlled by the proposed ANFPC scheme to maintain each vehicle within the desired distance headway and thus achieve string stability of vehicle platooning and fuel efficiency. The experimental results on the CarSim environment show that the proposed control strategy for the CACC system can significantly reduce the fuel consumption while ensuring driving comfort and safety.

This paper presents the results of a study of the effect of the characteristics of the traction power-supply system on the indicator of the energy supply of electric rolling stock. The power-supply indicator of the electric locomotive is described as a function of the indicators of the load capacity of a traction power system and operational indicators of the transportation process: the mass of trains, speed, headway, and a number of others. Statistical methods and results of the evaluation of the effectiveness of the use of traction resources for the territorial branch of the operating domain on the basis of rolling stock quality indicators have been presented. The organizational structure and model of the management of traction resources taking into account the inclusion of the functions of the relationship with the territorial directorates of Transenergo have been presented.

Within the headway distance constraints, the potential for reduction of energy consumption by hybrid electric vehicles (HEVs) with connectivity could be achieved by optimizing the ego vehicle motion. This paper proposes a look-ahead traffic information-based real-time model predictive control scheme to minimize total monetary cost of HEVs. A chain Gaussian process approach is employed to estimate the probability distribution of future increments of vehicle number over a look-ahead horizon from vehicle-to-vehicle and vehicle-to-infrastructure information. The future motion of preceding vehicles could be predicted by the evolution of the traffic density model and velocity tracking model. The above problem is formulated as a nonlinear optimal control problem with predicted disturbance input and dynamic constraints. Optimal solutions are derived through Pontryagin's maximum principle. The effectiveness of the proposed control scheme is evaluated on a traffic-in-the-loop powertrain simulation platform by integrating a commercial traffic platform and an enterprise-level powertrain simulator.

In order to improve the safety, stability, and efficiency of lane change operating, this paper proposes a multivehicle-coordinated strategy under the vehicle network environment. The feasibility of collaborative lane change operation is established by establishing a gain function based on the incentive model. By comparing lane change gain with lane keeping gain, whether it is feasible to perform the collaboration under current conditions can be judged. Based on the model predictive control (MPC), a multiobjective optimization control function for cooperative lane change is established to realize the distributed control. A novel two-stage cooperative lane change framework is proposed, which divides the lane change process into the lane change phase and the longitudinal headway adjustment phase. It is significant to solve the difficult numerical problem caused by the dimension of collision-avoidance constraints and the nonlinearity of vehicle kinematics. In the first stage, the subject vehicle completes lane change operation. Both longitudinal and lateral movements of the vehicle are considered to optimize the acceleration and the error of following distance at this stage; in the second stage, the operation of adjusting longitudinal headway between vehicles in the target lane is completed, and at this period, only the longitudinal motion of the vehicle is considered to optimize the vehicle acceleration error. The rolling optimization time domain algorithm is used to solve the optimization control problem step by step. Finally, based on the US NGSIM open-source traffic flow database, the accuracy and feasibility of the proposed strategy are verified.

The Adaptive cruise control (ACC) systems have been actively studied for the safety enhancement and commercialized for the last five decades. The ACC has been designed not only speed and headway distance controller, but also transition maneuver. In this study, an integrated control algorithm for the ACC is proposed to maintain the speed and the headway distance simultaneously without the transitional strategy. The proposed control algorithm also adjusts the set speed depending on the curvature of the road in coordination with the Lane Keeping (LK) system. The controller is designed based on the constant acceleration model for the real time performance. The proposed algorithm is validated in simulations first and the experimental verification is performed.

This paper derives the square root bus dispatch optimization developed by Newell from consumer surplus rather than the original cost minimization function. We then extend the model to consider disp...

Bus bunching resulting from initially small headway irregularities is a widely-known and studied problem. A variety of headway-prediction approaches, as well as corrective strategies, have been developed to identify and correct headway irregularity in real time. Instead of predicting an exact value for future headways, this study explores a probabilistic predictive methodology to forecast whether or not a bus will be bunched during its dwelling at a downstream stop, using a logistic regression model based on GPS records of buses at least k stops upstream to allow for sufficient time to possibly implement control strategies. A case study is conducted on a circular bus route in Kyoto City. Compared to two headway-based prediction approaches using linear regression and support vector machine, the superior performance of the proposed tool in detecting bunching is illustrated by Receiver Operator Characteristic (ROC) analysis. The high reliability in long-term prediction gives adequate time for operators to employ countermeasures. Besides, the proposed method provides operators with tradeoff options. We find that a bunching-averse operator can obtain 95% “sensitivity”, that is the ratio of correctly identified bunching events, at the cost of decreasing “specificity”, which is the ratio of correct non-bunching predictions over all events. This is true even if the prediction horizon is more than 10 stops.

Debates about how the contribution and worth of communication can be measured and evaluated have been raging in the academic and practitioner fields for several decades (Gregory & Watson, 2008; Likely & Watson, 2013; Macnamara, 2015; McCoy, 2016; Watson, 2012). Indeed, as Gregory and White reflect, at times it appears that these debates Seem like a car, stuck in mud or snow, trying to move forwards. The engine revs, the wheels spin, exhaust fumes and friction smoke clouds the scene, but – in the end – the car remains stuck. So, too, the evaluation debate: a great deal of discussion, but no forward movement. (2008, p. 307) However, just as with the car, so with measurement and evaluation shifts in context can facilitate traction. The snow is cleared away, someone comes along to give it a push and the car makes headway. In the measurement and evaluation arena the increasing demand that communication demonstrates the efficiency and effectiveness of its contribution, especially post the economic crisis of 2008 (Macnamara, 2015, McCoy, 2016), along with a number of industry and academic proposals outlined below and in Chapter 5.5, seem to be advancing progress. It is a prize worth pursuing, because as numerous academics have noted, evaluation appears to be the ‘holy grail’ for public relations (L’Etang 2008; Noble, 2011, Watson & Noble, 2014).

This study attempts to incorporate spatial heterogeneity into the optimal design of paired-line hybrid transit systems, which aims to strike a better balance between accessibility and efficiency by leveraging the flexibility of a demand adaptive service. A simple trip production and distribution model is introduced to differentiate the central business district (CBD) of a city from its periphery. To cope with the heterogeneous demand pattern, the transit system is also configured differently inside and outside the CBD, for both its fixed route and demand adaptive services. Allowing the supply heterogeneity complicates transit users’ route choice modeling considerably. As a result, user costs must be estimated separately for six subregions that constitute the feasible set of the fixed route headway. Each subregion corresponds to a unique route choice behavior, hence leading to a distinctive design model that is formulated as a mixed integer program and solved by a commercial solver. Results of numerical experiments show that concentrating demand in CBD significantly reduces the average system cost, and this benefit increases as the average demand density becomes larger. Also, recognizing demand heterogeneity and responding to it with a tailored design could be highly beneficial. However, this benefit diminishes as the average demand density increases.

Motion prediction for the leading vehicle is a critical task for connected autonomous vehicles. It provides a method to model the leading-following vehicle behavior and analysis their interactions. In this study, a joint time-series modeling approach for leading vehicle trajectory prediction considering different driving styles is proposed. The proposed method enables a precise and personalized trajectory prediction for the leading vehicle based on limited inter-vehicle communication signals, such as the vehicle speed and acceleration of the front vehicles. Three different driving styles are first recognized based on an unsupervised clustering algorithm, namely, Gaussian Mixture Model (GMM). The GMM generates a specific driving style for each vehicle based on the speed, acceleration, jerk, time, and space headway features of the leading vehicle. The feature importance of driving style recognition is also evaluated based on the Maximal Information Coefficient (MIC) algorithm. Then, a personalized joint time series modeling (JTSM) method based on the Long Short-Term Memory (LSTM) Recurrent Neural Network model (RNN) is proposed to predict the front vehicle trajectories. The JTSM contains a common LSTM layer and different fully connected regression layers for different driving styles. The proposed method is tested with the Next Generation Simulation (NGSIM) data on the US101, and I-80 highway dataset. The JTSM is tested for making predictions one to five seconds ahead. Results indicate that the proposed personalized JTSM approach shows a significant advantage over the baseline algorithms.

This paper presents a vehicle-type-specific headway distribution analysis at toll plazas under mixed traffic conditions. The aim of the paper is to provide headway distribution models that may be used for traffic flow analysis and traffic management at tollbooths. Seven classes of vehicle and a total of 49 combinations of leader–follower vehicles were considered, out of which 11 combinations were considered for studying the headway distribution model based on the frequency of arrival of such vehicle combinations at tollbooths. The results showed that vehicle classes requiring a headway of 5–25 s followed a log-normal distribution whereas, for higher headway ranges of 15–40 s, the generalised extreme value showed the best fit. For the small car category, the Wakeby distribution showed a better result than conventional distributions. The findings of this study may be useful for developing toll plaza microscopic simulation models, which could be used for assessing and improving the performance and efficiency of tollbooths.

The “customized train” is a train operated by the customized service of the passengers. The departure time, total travel time, and the travel classes are decided by passengers’ wishes. Successful operation of customized trains (CT) has a great significance to the future development in the relationship between the railway enterprise and the passenger service. In order to establish a comprehensive method for the CT operation plan, the paper proposes an intention survey method to obtain the passenger travel wishes data. Then, according to the existing timetable, the alternative set of CTs is built. The CT should satisfy the constraints of the passenger demand, the stop, and the train travel time. Based on the alternative set, a bilevel programming model for the maximum operation revenue of the CTs and minimum adjustment cost of existing timetable is established according to the passengers’ travel demands. The model also considers the constraints of actual travel time, arrival headway, departure headway, maximal adjustment time and capacity, and so on. The adjustment strategies for the train operation confliction are established. Finally, the method is proven through the analysis of actual cases, which can provide decision-making basis for future railway enterprises when operating the customized trains.

Advances in communications technology have made the development of connected and automated vehicle (CAV) applications that may potentially replace traditional, gantry operated lane control signals (LCSs) possible. This paper develops the concept of a prototype CAV-enabled LCS application and provides a preliminary assessment of the potential improvement it offers over traditional LCS. Real-world data obtained from an LCS on I-66 in Northern Virginia was used to calibrate and validate a baseline simulation model. Further, the current lane control scenarios utilized in the Northern Virginia LCS were identified and relevant data resulting from implementation of those scenarios were collected to model the LCS in a simulation environment. The performance of real-world LCS was then compared to a prototype CAV-enabled LCS application developed in this research. The CAV-enabled LCS application consistently outperformed the traditional LCS with increased throughput and speeds. On average, an increase of 18.4%, 9.6% and 12.8% in throughput was observed for three selected scenarios under the best case of a 1 sec headway. Furthermore, the CAV-enabled LCS application was also found to reduce volatility, represented by variation in acceleration and deceleration regimes, by an average of 25.6% and 49.6%. The reduction in turbulence in the traffic stream may indicate potential improved safety with the CAV system.

Forward collision warning (FCW) systems function by alerting drivers to upcoming hazards ahead and have been shown to help drivers respond more quickly under emergency situations. As FCW directly affects how vehicles interact longitudinally with one another, it may also influence car-following behavior such as reaction time, which has been little researched. To investigate these effects, driving data were collected from the Shanghai Naturalistic Driving Study. Five data-collecting vehicles were equipped with Mobileye® systems, which included an FCW function with headway display and warning system. Participants drove the vehicles for two months, with the Mobileye® system activated the second month only. From the 161,055 km of naturalistic driving data collected from 60 drivers, 3,000 car-following events were selected, and the effects of FCW on car-following headway and reaction time, and on the parameter values of the Gazis-Herman-Rothery (GHR) model were examined. Results showed that (1) drivers tended to maintain shorter headway with FCW enabled, while the proportion of time in short headways did not increase; (2) FCW reduced car-following reaction time when the lead vehicle was accelerating and when the relative speed between the lead and following vehicle was large; and (3) a reduction in the space headway exponent of the GHR was observed when FCW was enabled, indicating that drivers follow more closely with FCW because the system increases drivers’ sensitivity to changes in following gaps. Results of this study suggest that an FCW system with a headway monitoring function may increase traffic efficiency and stability without degrading safety.

The problem of operating exclusive bus corridors that have segments with bidirectional lanes is treated. On these lanes, only one direction of movement is allowed when a bus is present. Such construct requires less road space, which is a scarce resource in dense urban areas, and thus may be the only feasible alternative for the installation of exclusive bus corridors. The system model includes limits on bus passenger capacity. The control method for real-time operation integrates bus headway corrections and bus priority through signalized intersections, while enforcing mutual exclusion of opposing buses on the bidirectional lanes. Effectively, the control avoids bus bunching over the entire corridor and coordinates the passage of opposing buses on bidirectional lanes. The objective is to minimize the total waiting time of passengers, both onboard and at stops. Simulation results indicate the applicability of the integrated holding and priority bidirectional lane control method.

The airport rail link (ARL) was launched in 2010 as a premium rail transit service between the inner city of Bangkok and the airport. In 2014, the express service was canceled due to its unpopularity and transformed into the commuter service. In 2017, the new extended service concept was introduced under the three airport links project. Under this new concept, both ARL and high-speed trains will run on the city line section between Don Mueang and Suvarnabhumi Airports. This paper focuses on the use of a microsimulation model to identify the challenge of mixed-service operations, with regular and express trains running on the city line section. The simulation model allows investigation of hypothetical situations and construction of feasible timetables. The model can identify sections where special attention is needed, such as speed reductions, extended dwell times, or delayed departures. During the peak hour, the results suggest that the regular ARL should run with a 10-min headway and the high-speed one line with a 20-min headway, as an alternative solution. This results in fewer train numbers and less additional running time. Simulations indicate that the high-speed train is not efficient, as it consumes 2–3 times higher energy, while offering little time saving compared with the ARL city train. In addition, the Suvarnabhumi Airport extension track layout needs to be carefully considered, since the Suvarnabhumi Station area is a bottleneck liable to disruption.

With the aim of supporting future traffic needs, an account of how to reconstruct an existing cyclic timetable by inserting additional train services will be given in this paper. The Timetable-based Extra Train Services Inserting (TETSI) problem is regarded as an integration of railway scheduling and rescheduling problem. The TETSI problem therefore is considered involving many constraints, such as flexible running times, dwell times, headway and time windows. Characterized based on an event-activity graph, a general Mixed Integer Program model for this problem is formulated. In addition, several extensions to the general model are further proposed. The real-world constraints that concerning the acceleration and deceleration times, priority for overtaking, allowed adjustments, periodic structure and frequency of services are incorporated into the general model. From numerical investigations using data from Shanghai-Hangzhou High-Speed Railway in China, the proposed framework and associated techniques are tested and shown to be effective.

We developed a new car-following model to investigate the effects of driver anticipation and driver memory on traffic flow. The changes of headway, relative velocity, and driver memory to the vehicle in front are introduced as factors of driver’s anticipation behavior. Linear and nonlinear stability analyses are both applied to study the linear and nonlinear stability conditions of the new model. Through nonlinear analysis a modified Korteweg-de Vries (mKdV) equation was constructed to describe traffic flow near the traffic near the critical point. Numerical simulation shows that the stability of traffic flow can be effectively enhanced by the effect of driver anticipation and memory. The starting and breaking process of vehicles passing through the signalized intersection considering anticipation and driver memory are presented. All results demonstrate that the AMD model exhibit a greater stability as compared to existing car-following models.