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In fire evacuation situations, at corridors, many evacuees are plagued by high density, low velocity, and long waiting time. Therefore, engineers have to consider the countermeasure preventing crowd accidents. For this purpose, the development of pedestrian simulators that are constructed with concrete physical parameters, such as the headway distance between pedestrians, velocity, and specific flow, is required. To acquire the evacuation behavior in corridors, we conducted well-controlled pedestrian walking experiments in a confined corridor with realistic architectural geometry and modeled the pedestrian behaviors. An experimental loop corridor was constructed to acquire stable pedestrian flows without distractions from bottlenecks or merging flows. We conducted five experiments with different density patterns with an average density ranging from 1.28 to 3.42 people/m2 and a maximum of 96 test participants. We found that when the headway distance is 0.55–1.15 m, the velocity increases linearly with increasing headway distance, similar to single-file experiments. When the density is higher than 2.35 people/m2, the pedestrians cannot walk at a constant speed, and they exhibit stop-and-go behavior. In this situation, the percentage of pedestrians who walk at a headway distance of approximately 0.4–0.5 m, which is the minimum headway distance, increases. In addition, the fundamental diagram between density and velocity is acquired at a density higher than 1.4 people/m2 as an inversely proportional function. The density dependence on the specific flow is a linear function. The maximum specific flow is acquired at the marginal minimum density where a linear relationship is maintained.

PurposeThe anticipated benefits of connected and autonomous vehicles (CAVs) include safety and mobility enhancement. Small headways between successive vehicles, on one hand, can cause increased capacity and throughput and thereby improve overall mobility. On the other hand, small headways can cause vehicle occupant discomfort and unsafety. Therefore, in a CAV environment, it is important to determine appropriate headways that offer a good balance between mobility and user safety/comfort.Design/methodology/approachIn addressing this research question, this study carried out a pilot experiment using a driving simulator equipped with a Level-3 automated driving system, to measure the threshold headways. The Method of Constant Stimuli (MCS) procedure was modified to enable the estimation of two comfort thresholds. The participants (drivers) were placed in three categories (“Cautious,” “Neutral” and “Confident”) and 250 driving tests were carried out for each category. Probit analysis was then used to estimate the threshold headways that differentiate drivers' discomfort and their intention to re-engage the driving tasks.FindingsThe results indicate that “Cautious” drivers tend to be more sensitive to the decrease in headways, and therefore exhibit greater propensity to deactivate the automated driving mode under a longer headway relative to other driver groups. Also, there seems to exist no driver discomfort when the CAV maintains headway up to 5%–9% shorter than the headways they typically adopt. Further reduction in headways tends to cause discomfort to drivers and trigger take over control maneuver.Research limitations/implicationsIn future studies, the number of observations could be increased further.Practical implicationsThe study findings can help guide specification of user-friendly headways specified in the algorithms used for CAV control, by vehicle manufacturers and technology companies. By measuring and learning from a human driver's perception, AV manufacturers can produce personalized AVs to suit the user's preferences regarding headway. Also, the identified headway thresholds could be applied by practitioners and researchers to update highway lane capacities and passenger-car-equivalents in the autonomous mobility era.Originality/valueThe study represents a pioneering effort and preliminary pilot driving simulator experiment to assess the tradeoffs between comfortable headways versus mobility-enhancing headways in an automated driving environment.

In this research, an optimal control-based Cooperative Adaptive Cruise Control (CACC) system is proposed. The proposed system is able to enforce a target time gap between platoon members and is formulated in the space domain instead of the time domain which is adopted by most optimal control-based CACC systems in the past. By having this change, its robustness against communication failure is greatly improved and thus minimum safety headway buffer is reduced which leads to better mobility. In addition, third-order vehicle dynamics are modeled into the proposed control in order to improve control precision when implemented in the field. Local stability and string stability are theoretically proven. The proposed system is evaluated by simulation. Results reveal that the proposed CACC system outperforms the state-of-the-art $\mathcal {H}_\infty $ synthesis-based controller and linear feedback-based controller. The benefit of fuel consumption reduction ranges from 0.35% to 16.11%, while the benefit of CO2 emission ranges from 0.48% to 12.40%. Furthermore, the proposed CACC improves local stability from 11.03% to 25.90%, and string stability by up to 23.82%. The computation speed of the proposed method is 1.26 ms (with prediction horizon as 1.5 s and resolution as 0.1 s) on a regular laptop which indicates the proposed system’s potential to be applied in real-time.

Although the implementation of a new Automatic Train Protection (ATP) system increases the safety level, it also exerts some impact on the blocking time in block sections, and consequently, on the headway between trains. At the same time, ATP systems introduce a train positioning system based on odometry calculation and reporting back to the trackside system. This paper describes the concept of using virtual blocks based on train position reporting in the ATP system for purposes of non-occupancy determination. Virtual blocks can be used to reduce headways on railway lines without increasing the number of trackside signalling devices. Preliminary capacity assessment was performed to calculate the average headway depending on the signalling system with reference to a case study.

This paper proposes a modeling framework to design an integrated mobility service system that is composed of a local demand-responsive transportation (DRT) component and a fixed-route transit network component. The region is partitioned into disjoint local zones, and a trip is characterized into an intra- or inter-zonal one based on whether its origin and destination belong to the same zone. The transit network provides backbone line-haul service to inter-zonal trips, while the DRT system targets intra-zonal trips as well as the first-mile and last-mile legs of inter-zonal trips. The system components can be broadly defined, and this paper considers, as examples, conventional non-shared taxi or ride-sharing for the DRT service, and regular bus, bus rapid transit (BRT), or metro for the backbone network. For quantitative analysis of the DRT services, new aspatial queuing network models are developed to capture various DRT operations for serving trips with randomly distributed origins and destinations (i.e., intra-zonal trips) and those with origins or destinations concentrated at a set of fixed transit stations (i.e., first- or last-mile trip legs) at the same time. Each queuing model is integrated with the transit network design model, through proper service region partition, to derive closed-form formulas for the agency and passenger costs. Then, we formulate constrained non-linear programs that simultaneously optimize the zone partition, the fleet size and repositioning operation for the local DRT service, as well as the spacing and headway of a grid transit network. We apply the proposed models to a variety of transit technologies and application scenarios, so as to demonstrate applicability of the models, and to show promising performance of the proposed systems.

Uncertainty during the course of a trip is regarded as a particularly disturbing phenomenon by public transport (PT) passengers and has been shown to have a substantial impact on travel behaviour. However, so far there has been little empirical evidence within contemporary research concerning the degree of mid- to long-term adaptation among PT passengers to changes in the principal cause of such uncertainty within PT transport systems: Lack of service departure reliability. While most studies to date have focussed on instantaneous or short-term behavioural responses, this paper presents results from a one-year panel dataset consisting of individuals’ trip itineraries derived from smart card transactions enriched by automatic vehicle location (AVL) data. We measured long-term line route usage and departure reliability, the latter in terms of headway regularity and schedule adherence, in two panel waves. Thus, we aimed for practical indicators that may be associated with specific line routes and origin–destination PT stop pairs used for recurring trips over time. Results from logistic regression indicate a consistent significant impact of changed headway regularity and punctuality change for line routes with relatively high departure frequency. However, there is a relative indifference to long-term reliability change by a significant share of individuals that have actual trade-offs between at least two line route options, possibly indicating satisficing behaviour among PT passengers. Implications on PT path choice forecasting and route planning are discussed.

The present study investigated that Headway (Isometric, Isotonic and Proprioception) exercises are effective for acute & chronic ankle sprain injury, which was observed through experimental research. Ninety-four amateur cricketers of age, 15-35 years (Control Injured, N=48; Headway Rehab Group N=46) with a confirmed acute or chronic ankle sprain, selected from four different cities of Punjab, Pakistan was evaluated through Star Excursion Balance Test (SEBT), Single Leg Balance test (SLB) and subject to a set of progressively increasing exercises on ground known as Headway rehab exercises which consisted of Isometric, Isotonic and proprioception protocols. Another group of the same level of cricketers (N=40) was managed parallel for comparisons. The Control Injured and Headway Rehab Group was left with 40 subjects each because during the course of Headway exercise eight and six subjects left the study due to their personal reasons. Comparisons of pre and post-exercise (Control Injured Group) values showed a significant increase (p

The rationality of the spacing strategy directly affects automated vehicle safety and road utilization. It is necessary to consider practical actuator constraints in vehicle platoon control systems to ensure the security and driving comfort. In this paper, an important actuator constraint and a more effective spacing strategy are embedded into the connected automated vehicle platoon control. A new consensus-based control approach with the input saturation and variable time headway (VTH) spacing strategy is proposed. The homogeneous time-varying communication delays are included into the consensus algorithm. By employing the Lyapunov-Krasovskii theorem and the Lyapunov-Razumikhin theorem, the global asymptotic stability conditions of the system under fixed topology and switching topology are derived, respectively. Numerical simulation results demonstrate the effectiveness of the proposed approach and the necessity of introducing the input saturation and VTH spacing strategy.

Increasingly, commercial vehicles are equipped with automated vehicle (AV) features such as adaptive cruise control systems. The AV feature can automatically control the headway between the current vehicle and the preceding vehicle in an adaptive manner. The automatic control may lead to significantly different car- following motions compared with those of human-driven vehicles, which challenges the applicability of classic traffic flow theory to emerging road traffic with AVs. To investigate the impacts of commercial AVs on traffic flow, this paper proposes a general methodology that combines both empirical experiments and theoretical models to construct a fundamental diagram (FD), i.e., the foundation for traffic flow theory for AV traffic. To demonstrate the empirical experiment settings, we collected high-resolution trajectory data with multiple commercial AVs following one another in a platoon with different headway settings. The field experiment results revealed that the traditional triangular FD structure remains applicable to describe the traffic flow characteristics of AV traffic. Further, by comparing the FDs between AVs and human-driven vehicles, it was found that although the shortest AV headway setting can significantly improve road capacity, other headway settings may decrease road capacity compared with existing human-driven-vehicle traffic. It was also found that headway settings may affect the stability of traffic flow, which has been revealed by theoretical studies but was first verified by empirical AV data. With these findings, mixed traffic flow FDs were derived by incorporating different headway settings and AV penetration rates. The method proposed in this paper, including experiment designs, data collection approaches, traffic flow characteristics analyses, and mixed traffic flow FD construction approaches, can serve as a methodological foundation for studying future mixed traffic flow features with uncertain and evolving AV technologies.

Bus bunching in public transport is the concentration of similar buses having different schedules to a common time point. The reason for this phenomenon is variations existing in the bus operation as earliness and lateness. Bus bunching has the consequence of reduced service reliability concerning both passengers and operators. A zero bunching state is vital for enhancing the usage of public transport where the buses operate with utmost schedule adherence. Two generally adopted strategies for solving bus bunching are a schedule-based strategy which provides slack time in a timetable to address late running and fixed departure time for the early operations, and a headway-based strategy that maintains headway between buses. Bus bunching due to multiple origins is a special case in which common tactics cannot effectively control a bunching tendency that arises at the entry point. The operation schedules of multiple origins must be so designed that a state of zero bus bunching can be ensured while buses from different origins reach the entry points. This article presents a model of a multiple-origins public transport network as a combination of origins, routes and entry points, developed in the search for achieving a zero bunching state in the operation beyond an entry point. The origins are modelled based on the entry-point variables. The routes are modelled based on the running time, departure time, arrival time, and dwell time. The entry points are modelled based on route and entry-point variables. Redesigning route schedules based on the entry-point characteristics and an appropriate slack time implementation are proposed and observed to be suitable for overcoming bunching in a multiple-origins bus operation.

In this study, the relation between macroscopic parameters (speed, flow, density, occupancy) and microscopic parameters (lateral clearance, average gap, space headway, lateral movement duration, ov...

Dari segi transportasi umum di kabupaten Mamuju belum tersedia, sehingga akses untuk masyarakat yang bermukim di desa – desa sangat sulit sebab hanya bisa dijangkau dengan kendaraan pribadi. Demikian juga halnya pegawai/karyawan pemerintah Provinsi Sulawesi Barat yang tidak mempunyai kendaraan pribadi untuk pergi ke kantor terkadang memakai transportasi ojek motor atau ikut dengan teman kantor. Hal inilah yang menjadi dasar pemikiran bahwa sangat diperlukan pengadaan transportasi umum di kota ini agar masyarakat mudah menjangkau kota untuk keperluan mereka termasuk pegawai/karyawan untuk pergi ke kantor. Adapun tujuan yang ingin dicapai dalam penelitian ini adalah (1) Untuk menentukan karakteristik sosial ekonomi dari karyawan, besarnya bangkitan perjalanan serta potensi penggunaan angkutan khusus karyawan pada pusat pemerintahan Provinsi Sulawesi Barat. Dan (2) Untuk menganalisis sistem operasional angkutan khusus karyawan yang dapat diterapkan pusat pemerintahan Provinsi Sulawesi Barat. Hasil penelitian menunjukkan bahwa (1) Potensi penggunaan angkutan khusus karyawan diperoleh stated preference pada 372 sampel. Dari hasil survei diatas kemudian diperoleh jumlah responden yang berminat menggunakan angkutan khusus karyawan adalah sebesar 284 orang atau 76,34% dari jumlah sampel yang di ambil sebesar 372 sampel. Dari hasil survei tersebut, maka dapat di estimasi jumlah penumpang yang akan dilayani angkutan khusus karyawan pada kawasan Kota Mamuju adalah sebesar 76,34% x 5.400 orang (jumlah seluruh populasi) = 4.122 orang dan (2) diperoleh trayek angkutan khusus karyawan yaitu Trayek M01 lintasan Mamuju-Simboro, Berdasarkan potensi jumlah penumpang pada masing-masing trayek ditetapkan headway 2 menit, dengan waktu siklusnya adalah 71,6 menit. Waktu pelayanan angkutan khusus karyawan didefinisikan sebagai total waktu pelayanan angkutan khusus karyawan dalam satu hari. Dalam penelitian ini, waktu pelayanan didesain selama 11 jam/hari yang terbagi dalam 3 shift. Shift I beroperasi mulai pukul 06.00 s/d 07.30 dilanjutkan dengan shift II yang beroperasi mulai pukul 15.30 s/d 17.00 dan shift III beroperasi sesuai dengan kebutuhan kegiatan keluar kantor yang dilakukan karyawan. Dengan kata lain, waktu pelayanan efektif kendaraan dalam sehari adalah 3 jam. Pelayanan angkutan khusus karyawan ini dikhususkan untuk karyawan yang bekerja pada pusat Pemerintahan Kota Mamuju.

In DC metro systems, the stray current may cause many challenges for the nearby metal structures and the AC power systems, such as the corrosion of the buried pipes and the grounding grids of substations. Therefore, calculating the stray current and analyzing the distribution characteristics of the stray current are necessary for the design of the buried pipelines and substations. To obtain the stray current, considering the through-type structure characteristics of the return current system and the traction power supply system, a multiple power supply sections simulation model (multiple-section model) of stray current is proposed. In the proposed model, the train is equivalent to two dc current sources, and the dynamic results can be completed. Through comparing the rail potentials of simulation results and the field test data of the Shenzhen metro line, the proposed model is verified. And based on the proposed model of the Shenzhen metro line, the stray current distributions are obtained and analyzed. The results indicate that the stray current distribution has a certain periodicity which is approximately equal to the headway time of the train.

The wide-spread application of automatic train operation (ATO) system on metro lines allows short service headways, high-density operations and high operation efficiency. This paper addresses real-time train control for ATO when faced with disturbances or disruptions in its operations. More specifically, the paper focuses on the design of integrated train dwell time regulation and speed profile generation in real-time and in response to dynamic changes in the operation environment. A nonlinear optimal control model is formulated in a rolling horizon scheme that incorporates three key operating elements: train timetable, passenger load and train speed profile. The objective is to simultaneously improve headway regularity and reduce the total energy consumptions. To satisfy the real-time control requirement for ATO system, a decomposition method based on the alternating direction method of multipliers (ADMM) is designed to divide the original optimization problem into many sub-problems, one for each train, which can then be computed in a distributed manner. Moreover, to address the non-convexity issue, a relax-round-polish process is developed to deal with the formulated nonlinear optimal control problem with convex objective over non-convex constraints in order to find the approximate solutions quickly for the embedded applications. The combined result is an ADMM-based heuristic algorithm. The effectiveness of the proposed model and solution algorithm is demonstrated using real-world data from the Changping Line of Beijing Metro. The results show that the proposed distributed and embedded optimization algorithm is able to significantly enhance the robustness and reliability of real-time train control in automated high-density metro lines.

Bus bunching is of particular concern and undesirable for both operators and passengers in high-frequency transit. In contrast to existing control methods, this paper proposes a novel control policy, namely, providing real-time bus crowding information (BCI) for passengers. It is believed that passengers would spontaneously distribute more evenly among buses and help to prevent bus bunching with the provision of BCI accompanying arrival time information due to the following mechanism. A proportion of passengers would be likely to wait a few more minutes for the next bus when the current bus is crowded and the next bus is more comfortable, and the boarding times of these passengers would make the next bus dwell longer and increase its headway from the previous bus. We formulate bus motion models incorporating passenger boarding choice under BCI to realize the policy in simulation experiments. The results demonstrate that the policy can reduce operation instability by approximately 20% in terms of bus headway and single-trip time. In addition, this policy can significantly reduce the in-vehicle crowdedness experienced by passengers by up to 25% at the cost of small increases in the mean journey time in some cases. The simulation experiments on a holding-controlled route also indicate that the proposed policy is able to coordinate with holding well. A sensitivity analysis further confirms that the policy’s performance is robust even if the passengers have low inclinations to choose the next bus. The policy of providing BCI in this paper is especially effective for bus routes with high passenger demand and may have great application potential in practice.

Motivated by the increasingly popular mixed traffic flow modeling, a novel heterogeneous continuum traffic flow model is proposed in this paper, which considers the differences of the driver's psychological headway and the driver's self-stabilizing effect on the optimal velocity related to the psychological headway. Leveraging the linear and nonlinear analysis approaches, the linear stability condition and the KdV-Burgers equation are yielded to describe the characteristic of traffic flow evolution. The bifurcation analysis on the proposed model is executed to discuss the existence and stability of Hopf bifurcation from a theoretical perspective. Numerical simulations are performed to verify the rationality of the abovementioned theory and explore the density evolution of heterogeneous traffic flow, including local cluster effect, fuel consumption and exhaust emissions and Hopf bifurcation, in which it is notable that the heterogeneous continuum traffic flow generates significantly different phenomena under different density conditions and the evolution of Hopf bifurcation in traffic flow is also involved.

The rollout of autonomous vehicles (AV) presents an invaluable opportunity to assess the user perception and experience of a new technology that is expected to disrupt the urban mobility system worldwide. To incorporate AV technologies into existing public transit systems, transit agencies need rigorous assessment and validation of AVs in real-world scenarios and transit environments. It has been a common practice lately by many transit agencies to deploy a driverless shuttle (DS) pilot program to assess how the AV technology can enhance transit service and improve users’ satisfaction. Despite the numerous DS pilot programs around the world, there is a lack of robust and comprehensive guidelines for ensuring the effectiveness of such programs in attaining reliable outcomes and insights. The objective of this paper is to synthesise lessons from DS pilot programs worldwide and develop a planning framework that will help policy-makers and transit agencies facilitate the incorporation of DS in transit systems. Over 25 completed or ongoing DS deployments were reviewed and critiqued to identify what constitutes a successful pilot program. Ultimately, while previous deployments received positive feedback from the public, there have been few pilots that experienced operating environments representative of actual ridership, traffic, and weather conditions of real transit services. From the selected case studies, it is evident that the technology is still in its infancy and it is recommended that future programs consider various operating traffic and environmental conditions, different route layouts and various speed and headway levels to evaluate more realistically the viability of replacing conventional buses with DSs. Other possible avenues of research include focusing pilot programs on more specific use-cases, such as providing demand responsive and first/last mile services in sparsely populated areas.

The fast development of communication technique builds an era of Internet of Everything. In the automobile world, Internet-Connected Vehicle (CV), also called IntelliDrive, will accelerate the autonomous driving era’s coming. And the traffic flow theory will undergo major changes as CV platoon becomes common way for our travel. As we know that the CV has different driving decision mechanisms from human-driven vehicles, such as an CV can receive more information and make much faster decision than a human-driven vehicle. Only if we fully understand the autonomous traffic flow’s characteristics, then we can improve the level of traffic engineering study and management in the future. On the thought of building autonomous traffic flow theory, we present CV platoon car-following model as the theoretical microscopic traffic flow model. The model is described by a mathematical differential-difference equation, which has a synthesized optimal velocity differential function and a full platoon with weighted relative velocity difference function. There are three main factors in the model, which are the optimal velocity difference impact factor p and action related vehicle number l , and weighted velocity difference sum coefficient λ . The model reflects the effects of front interactions between every two adjacent CV instead of the weighted average headway in the platoon. We deduce the model’s stability conditions with linear system stability theory and do some computer numerical simulations to verify our suppositions. Simulation results show that the more information broadcasting among CV, the more stable of the traffic flow system is. At last, we discuss our study’s contributions from the viewpoint of theoretical and practical value, and point out future research directions. In a word, the highlight of the paper is that we find the CV platoon system’s running mechanism by building an CV platoon car-following model under connected environment and give its linear stability condition, which is great value for advanced traffic management in autonomous driving era.

Motivated by the lack of microeconomic models that optimize time-dependent transit fares based on realistic demand formulations, this paper presents a microeconomic model for the design of a time-dependent transit pricing scheme considering elastic and spatiotemporally distributed demand. To model the spatial distribution of demand, a transit line with multiple origin–destination pairs is considered. To model the cyclical demand fluctuations, transit operations in one day are divided into multiple time periods. In the proposed model we optimize fares, headway, vehicle capacity, and maximum fleet size, with the objective of maximizing social welfare, subject to fleet size and vehicle capacity constraints. We find time-dependent pricing could avoid cross-subsidization among travelers in different time periods. Under both pricing schemes, the time-dependent headways satisfy the same optimality condition: the total rider waiting cost equals the total fixed cost on the supplier side. We also demonstrate that both resource constraints (vehicle capacity and fleet size) can be binding in multiple time periods, unlike the usual assumption in the literature that resource constraints are binding only in the period with the highest demand. Two extensions (considering a financial constraint and a variable roundtrip time) are also investigated. The developed models can be used to facilitate the design of time-dependent pricing schemes for practical applications.

Even before the start of the COVID-19 pandemic, bus ridership in the United States had attained its lowest level since 1973. If transit agencies hope to reverse this trend, they must understand how their service allocation policies affect ridership. This paper is among the first to model ridership trends on a hyper-local level over time. A Poisson fixed-effects model is developed to evaluate the ridership elasticity to frequency on weekdays using passenger count data from Portland, Miami, Minneapolis/St-Paul, and Atlanta between 2012 and 2018. In every agency, ridership is found to be elastic to frequency when observing the variation between individual route-segments at one point in time. In other words, the most frequent routes are already the most productive in terms of passengers per vehicle-trip. When observing the variation within each route-segment over time, however, ridership is inelastic; each additional vehicle-trip is expected to generate less ridership than the average bus already on the route. In three of the four agencies, the elasticity is a decreasing function of prior frequency, meaning that low-frequency routes are the most sensitive to changes in frequency. This paper can help transit agencies anticipate the marginal effect of shifting service throughout the network. As the quality and availability of passenger count data improve, this paper can serve as the methodological basis to explore the dynamics of bus ridership.

Problem. Currently, there is no universal approach to improve the efficiency of the urban public transport operation. Different methods are used during the estimation of public transport operation cost and the quality of services for the passengers. It makes actual the development of the target function which will allow assessing the carrier cost and passenger expenditures, and therefore find the balance between the interests of these parties of the transportation process. Thus, the alternative to the existing approaches can be created and then used to organize passenger transportation and improve transport enterprise management. Development of this alternative is the actual task as the new target function will open the horizon to improve the methods of organization of public transport operation. Goal. The new approach to optimize the costs of public transport operation needs to be tested for the appropriateness for the planning of passenger service in cities. Methodology. The developed target function was derived as the result of the analysis of the economic and social factors influencing the efficiency of the urban public transport operation. Results. The use of the developed target function allows finding the optimal values of cost components for the passenger and the carrier. Originality. The obtained function to optimize the performance of public transport allows reducing the costs of suboptimal use of vehicles capacity, suboptimal allocation of the vehicles to the routes and the irrational organization of vehicles operating on the routes. Practical value. The results of the research clarify the controlled and uncontrolled parameters of the public transport system operation.

In train rescheduling, the arrival and departure times of trains at stations are normally constrained by many operations rules that must be respected. Therefore, different methods were proposed to ...

Vehicle platooning is a perspective technique for intelligent transportation systems (ITS). Connected and automated vehicles (CAVs) use dedicated short-range communication (DSRC) to form a convoy, in which the following vehicles can receive the information from their preceding vehicles to achieve safe automated driving and maintain a short headway. Consequently, a vehicle platoon can improve traffic safety and efficiency, further reducing fuel consumption. However, emergency braking inevitably occurs when the platoon meets an accident or a sudden mechanical failure. It is more critical when the wireless communication got delays. Therefore, “how to predefine a minimum safe distance (MSD) considering communication delay” is a challenging issue. To this end, a series of field tests were carried out to measure the communication delay of IEEE 802.11p that is the underlying protocol of DSRC. Subsequently, MSD is modeled and analyzed when the platoon travels at accelerating, cruising, and decelerating states. More importantly, the results of field tests are applied in the models to investigate the impact of communication delay on MSD in practice. The simulation results verify that the proposed model can effectively maintain the platooning vehicles’ safety even if emergency braking happens with certain communication delays.

Emerging automated vehicle (AV) technologies are increasingly being deployed around the world and it is only a matter of time before the transportation landscape changes dramatically. Unfortunately, those changes cannot be well predicted due to the lack of empirical data. But adaptive cruise control (ACC) vehicles are common in the market and can be used to fill this gap. In this paper, we aim to characterize the empirical car-following behaviors of a commercial ACC system and understand how ACC behaves in different conditions and the underlying impact mechanism. It is found that for a single ACC: (i) the ACC response time is comparable to human drivers but much larger than the ACC controller time gap and it exhibits small variance, (ii) the ACC response can amplify or dampen an oscillation, (iii) after the oscillation, the stabilization process can exhibit overshooting or undershooting, and (iv) these CF behaviors depend largely on the ACC headway setting, speed level, and leader stimulus, which produce the impacts directly and/or indirectly through the mediation of earlier ACC behaviors. For a three-vehicle platoon, our main finding is that the change from one ACC vehicle to the next is progressive for oscillation growth, and regressive for deceleration, acceleration, and overshooting. This implies that in long platoons, oscillation amplitude tends to exacerbate very quickly, which forces ACC vehicles further upstream to apply very strong braking followed by a strong acceleration. This can cause significant overshooting and safety hazards.

The high proportion of motorcycles and lack of lane discipline at signalized intersections under mixed traffic conditions are the motivation to conduct this study. The discharge headway models are constructed at three (3) signalized intersections in the SARBAGITA urban area in Bali. The result shows that motorcycles affect saturation flow due to their shorter headway than light vehicles while increasing discharge headway of other vehicles. The discharge headway between pairs of heavy vehicles is longer than these of motorcycles due to their slower acceleration at signalized intersections. This study also found that the discharge headway plays a significant role in determining the saturation flow and capacity of a signalized intersection. If a heavy vehicle is one of the pairs, then it has the potential to have a headway exceeding the other vehicle pairs. This indicates, however, that the higher proportion of motorcycles at the signalized intersection approach does not necessarily mean shorter discharge headway. There may be other influencing factors, such as the riding behavior of motorcyclists. The dominance of motorcycles can affect the value of the saturated flow, but an increase in the proportion of heavy vehicles may reduce the effect of motorcycles on the saturation flows.

Public transport is affected by different types of randomness which impact the reliability they offer. The source of this randomness may come, for example, from casual uncertainty sources, such as accidents or protests, or from systematic uncertainty, related to service supply, such as dwelling time or travel time between consecutive stops. In addition to these sources of variability, an extra source of uncertainty experienced by users arises due to the public transport vehicle not being immediately available to avoid a wait of uncertain length. In a frequency-based system (without schedules), even under perfect regularity, users are not sure about the next vehicle's time of arrival. This article aims to find out the impact that reliability has on travellers’ public transport alternative choice. To do so, an experiment of stated preferences is carried out, where the design characteristics are four operational attributes: speed, frequency, headway regularity, and average demand. Every scenario is randomly generated, based on the operational characteristics of the specific scenario. This means the alternatives presented resemble real-life operation and they are different between respondents. A Hybrid Discrete Choice Model was estimated, which addresses preference heterogeneity by considering two latent attitudes: punctual behaviour and crowding aversion. Overall, results indicate that headway irregularity has a significant effect on travellers’ choices, both in terms of waiting time and passenger density. This confirms this attribute should not be ignored in any public transport model, especially when it comes to evaluate projects which improve the system’s reliability but not necessary its average level of service.

The advancements in cancer treatment have no significant effect on ovarian cancer [OC]. The lethality of the OC remains on the top list of gynecological cancers. The long term survival rate of the OC patients with the advanced stage is less than 30%. The only effective measure to increase the survivability of the patient is the detection of disease in stage I. The earlier the diagnosis, the more will be the chances of survival of the patient. But due to the absence of symptoms and effective diagnosis, only a few % of OC are detected in stage I. A valid, reliable having a high acceptance test is imperative to detect OC in its early stages. Currently, the most used approach for the detection of OC is the screening of CA-125 and transvaginal ultrasonography together. This approach has an efficacy of only 30-45%. A large number of biomarkers are also being explored for their potential use in the early screening of OC, but no success is seen so far. This review provides an overview of the biomarkers being explored for early-stage diagnosis of OC and increasing the current long-term survival rates of OC patients.

In recent years, there has been a steady increase in the volume of traffic. According to experts ' forecasts, the demand for product transportation will continue to increase. Meanwhile, the supply for the capacity of the lines is actually exhausted. Therefore, the most important task of railway transport in the near future will be to increase the carrying capacity and capacity.Increasing the carrying capacity of railway transport can be achieved by: increasing the average speed of trains, building additional tracks, increasing the length and weight of freight trains, reducing inter-train intervals, and organizational measures. To increase the average speed of trains, it is necessary to improve the quality of track maintenance and rolling stock, in addition, certain sections of the track will need to be reconstructed. These measures, including the construction of additional tracks, are long-term and will lead to significant material costs. Increasing the length and weight of freight trains leads to an increase in the number of accidents.The most effective way to increase the carrying capacity is to reduce the inter-train intervals in conjunction with a number of organizational measures.With the coordinate method of interval control, the programs and algorithms obtained on the basis of mathematical models must guarantee the safety of trains with minimal intervals.This fact confirms the need to conduct a set of studies in the field of methodology for ensuring safety and organization of train traffic by clarifying existing and developing new mathematical models of train movement in relation to the specifics of the coordinate method of interval regulation.

Framed by MCDA, our study examines diachronic changes in gender representation in five New Headway Elementary (NHE) editions. Our findings demonstrate that NHE’s gender representation is establishe...

PurposeThis paper aims to explore the characteristics of capability exchange within internationalizing small and medium enterprises (SMEs) of the Portuguese metallurgic and metal-mechanic sectors.Design/methodology/approachMultiple case research instrumentalizes a (manifest) content analysis based upon qualitative data gathered from the interviewing of the strategic apex of four multinational enterprises, codified in the light of the well-known Weber protocol.FindingsThe results uncover the existence of a multi-diffusional approach with a bi-directional regime of transferability, where reciprocal transference is non-simultaneous. Operational rigidities are asserted to be stifling the diffusion of capabilities across subsidiaries and hindering higher economies of learning.Research limitations/implicationsThe current paradigm of international capabilization of the sector requires substantial enhancements in its design for the benefit of the firm’s international competitiveness, growth and wealth.Originality/valueOrganizational capabilities are a determinant of competitiveness. Hitherto, the phenomena of (capabilities) mobility and transferability are still acknowledged as a clear gap. This study opens, therefore, avenues on international capabilization in relation to the modeling and testing of global dynamic capabilities and its replicability across industries.

The advent of Connected and Autonomous Vehicles (CAVs) and Mobile Internet technologies is reshaping the public transport sector. Autonomous buses are equipped with varying advanced sensors, and hold great promises to enhancing the responsiveness and flexibility of public transit system. In the context of CAVs, transit operators can not only optimize service headway but also adjust bus capacity to meet the time-varying passenger demand. Anticipated benefits of introducing autonomous buses to the existing transit systems include safety improvement, driver cost reduction, and optimal routing. Bus electrification is another global trend to replace traditional diesel buses for energy savings. Electric buses are advantageous to both operators and passengers due to low greenhouse gas emission, maintenance cost, as well as noise pollution. In recent years, demand responsive public transport (DRPT) services (e.g. customized bus, microtransit) receive huge success thanks to the development of Mobile Internet. Unlike traditional bus services or the fixed-route transit service that relies on passive recipients, fixed stops, and schedules, DRPT can provide personalized service for specific clients through interactive information platform (Internet or smartphone). The aforementioned new types of public transit services significantly improve service quality, reduce energy consumption, and ultimately attract more ridership. To fully explore the benefits of personalized, electric and autonomous transit systems, new analytical models and data-driven methods for transit planning and operation are needed. The authors have selected 15 articles for review in this special issue. A summary of these articles is outlined below.

Intraindividual variability is a fundamental behavioural characteristic of aging but has been examined to a very limited extent in driving. This study investigated intraindividual variability in driving simulator measures in healthy drivers of different ages using the coefficient of variation (COV) as a variability measure. Participants were healthy volunteers who were regular drivers, who were divided into a “young” group, a “middle-aged” group, and an “old” group. They drove in two environments (rural, 72 drivers; urban, 60 drivers), under conditions of moderate and high traffic load, without and with distraction (conversation). Significant differences in COV were observed in the rural condition for headway distance and lateral position as a function of traffic load, with high traffic (without and with distraction) resulting in increased COV of headway and decreased COV of lateral position. Significant differences in COV were observed in the urban condition for headway distance only, with high traffic (without and with distraction) resulting in increased COV of headway. No age effects were found for any of the driving conditions. The results indicate that traffic load affected headway distance and lateral position in opposite directions in all three age groups: high traffic resulted in increased variability of headway in both rural and urban conditions but in decreased variability of lateral position in the rural conditions compared to moderate traffic irrespective of distraction. The study indicates that driving conditions affect the intraindividual variability of driving measures in selective ways, which may be linked to the extent of automatization of the driving variables and to adaptive changes to traffic condition challenges.

Waiting time at transit stops is found to be an influential policy variable for a passenger's decision on whether to undertake a given transit service. With regard to policy framework for improvement of operational service headway of a transit service and thereby its waiting time, the necessity to have knowledge on its critical value becomes inevitable. The critical value of waiting time for passengers waiting at transit stops is that duration beyond which passengers are found to be no more interested to wait for a that transit service. The paper demonstrates an approach for estimating the critical value of waiting time at urban transit stops with reference to public transport services such as city bus and shared-auto operational in Bhubaneswar, India. The critical value of waiting time is estimated from the point on cumulative distribution curve of waiting time frequency distribution, at which the maximum rate of change of the slope of curve occurs. The work assumes two positively skewed distributions such as gamma and log-normal for observed distributional pattern of waiting time. The work identifies that gamma distribution is comparatively fitting the observed data better than log-normal distribution. The study reveals that the critical value of waiting time for city bus passengers is about twice than that of shared auto passengers. Though, the study presents new information on critical values of waiting time with reference to an urban area of a developing country, it also demonstrates an experience on application of probability distribution functions for understanding distributional pattern of waiting time.

As an emerging energy-efficient management approach, the essential idea of subway regenerative energy optimization is to maximize the absorption of energy generated from train deceleration by adjusting train schedules. In the extant literature, performance evaluation and optimization rely on synthetic data (e.g., computer simulations) and train energy-efficient operation (EEO) strategy. However, when compared to real automatic train operation (ATO) data, the above-mentioned method exhibits significant errors. In this work, we develop a new optimization method driven by real ATO data for maximizing subway regenerative energy based on the following three steps: first, we provide a high-frequency ATO data-driven method for simulating the amount of regenerative energy absorption; second, we propose a concept of uniformity to measure the homogeneous degree of headway distribution; third, we formulate a headway optimization model to maximize the regenerative energy absorption under uniformity constraint. To handle the high complexity of the ATO data-driven objective function (e.g., non-monotonicity, non-convexity, multi-modality), we propose an improved genetic algorithm with multiple crossover and mutation operators to search for near-optimal solutions, in which an adaptive operator selection mechanism with reduction process on ATO data is considered for speeding up the regenerative energy simulation and optimization. The effectiveness of the proposed method is confirmed by using the real ATO data of Beijing Subway Changping line. Our numerical study reveals that, benchmarked with the uniform headway distribution (the policy that is presently in use), our proposed approach achieves a relative improvement of 7.75% at off-peak hours and 42.44% at peak hours for the regenerative energy absorption; and we show that such a significant performance improvement is obtained by allowing a small level of scheduling flexibility (less than 6% relaxation on uniformity level).

Considering Chinese FDI in sub-Saharan Africa (SSA), the paper attempts to verify if the long-existing ‘flying geese’ paradigm (FGP) might be used to clarify the headway of Chinese migrating geese ...

Although researchers have done effective work at describing the inequities that plague schools, they have been less successful at making headway in addressing them, largely because their work remains disconnected from the schools that have to try to use the research. Through research-practice partnerships, researchers are able to stay in touch with the educators on the ground, craft research questions with their actual problems in mind, and help them take action in response to the research. Daniel Potter, Erin Baumgartner, and Ruth N. López Turley describe how, through the Houston Education Research Consortium, researchers from Rice University launched an equity project to uncover inequities within Houston-area schools and track their progress in addressing them. And, because of the ongoing relationship, they were able to launch a research project looking into how the COVID-19 pandemic affected students and produce results while schools where they were still relevant.

The recent development of advanced communication and data collection technologies enables a wide range of possibilities for systematic planning, operation, and control of urban rail transit systems in many megacities. While traditional methods consider tactical transit timetabling and operational circulation planning as two independent stages, this study aims to propose an optimization model and solution scheme to fully integrate these two supply-side stages in response to passenger demand dynamics. We first construct a new formulation through two coupled space-time network representations, namely, the transit space-time network and passenger space-time network, with many embedded constraints. In detail, the transit space-time network covers constraints involving train fleet size, deadheading and holding operations, headway requirements, and running and dwell times; meanwhile, the passenger space-time network is used to represent passenger traveling processes and the resulting trajectories. A coupled network-based flow optimization model is accordingly established to minimize passenger total travel time with a fixed train fleet size. To handle large-scale problem instances, we first adopt a constraint splitting technique to form two subsets of Lagrangian multipliers corresponding to individual passenger decision constraints and train capacity constraints. A dual decomposition scheme is then developed to iteratively coordinate the adjustment of Lagrangian multipliers and solve the related two subproblems. Specifically, the passenger subproblem is solved by a passenger loading algorithm, and the train subproblem is decomposed and solved by the alternating direction method of multipliers. The effectiveness of the proposed model and solution approach is evaluated on a real-world case study based on the Batong Line in the Beijing subway network.

This research aimed to compare the saturation flow rates of an urban at-grade signalized intersection under different climatic conditions in order to optimize the traffic light control system of this intersection. Data collection was performed with a video camera. The case studied was the intersection of Sattari-Mokhberi Intersection, in Tehran. The road surface conditions occurring in this intersection were divided into three classes: dry, wet, and snowy. Modeling and simulations were performed with the help of the software Vissim and Synchro. Model calibration was performed using the parameters “desired speed” and “acceleration/deceleration at zero speed”. Data analysis was performed using descriptive statistics and inferential statistics, including analysis of variance (ANOVA), Kolmogorov–Smirnov test, and Tukey and Scheffe tests. The saturation flow for dry, wet, and snowy road conditions was estimated to 1967, 1722, and 1607, respectively. Also, the relationship between saturation headway and sight distance in meters was modeled linearly and logarithmically. The analysis of videos showed that the mean desired speed in wet and snowy road conditions was, respectively, 23% and 36% lower than in normal conditions. The mean desired acceleration at zero speed in wet and snowy road conditions was, respectively, 24% and 30% lower than normal. The simulation results showed a 15% reduction in the total delay of the intersection after the implementation of weather-responsive schedules. The results of this research show that the benefits of adjusting the schedule of traffic lights based on weather are more pronounced in snowy conditions than in rainy conditions.

Reliability is understood in public transport as the certainty travellers have regarding the level of service they will experience when travelling. The travel time, waiting time, or the comfort level they will experience inside the vehicle are some of the most important reliability attributes. Reliability is usually neglected from travel behavioural models, since there is a lack of studies addressing its impact in travellers’ choices. This study proposes an in-depth analysis and characterization of travel time reliability in a public transport system using passive data only, which every day is getting more popular worldwide. The study is comprised of two parts, taking Transantiago (the public transport system of Santiago, Chile) as a study case, as it is a good representation of a frequency-based public transport system. In the first part a statistical and graphical analysis of travel times is conducted, focusing on characterizing headway and travel time reliability of public transport services as well as the effect of dedicated infrastructure, based on smartcard transactions and GPS information. In the second part an aggregate mode choice model based on revealed data is developed to analyse the effect of travel time reliability on travellers’ preferences. Overall, this study provides evidence of significant differences among headway variability and in-vehicle travel time dispersion different public transport modes. The standard deviation (a measure of dispersion) can be quite high for bus trips, while in the case of metro is smaller than 4 min independent of trip length. Regarding the aggregate public transport mode choice model, the coefficient of variation of headways is a key attribute to explain modal preferences. It was found that average bus users would accept traveling ~ 5 min longer to completely avoid headway irregularity. All these results were obtained by analysing passive-data from AFC and AVL systems only, which represents a novel approach for choice modelling. Transport modellers should consider the impact of service reliability to improve route choice and passenger assignment models, and better represent users’ perceptions and behaviour.

In this research, a feasible mechanism is developed to determine the optimum number of bus rapid transit (BRT) stations as well as their respective locations along the service corridor. To accomplish this, a mathematical model is developed and optimized by using three different evolutionary algorithms, namely particle swarm optimization (PSO), genetic algorithm (GA), and differential evolution (DE), and the results are compared. The total cost function is composed of two main costs namely the operator’s cost, i.e., related to costs on service provider’s end, and the user’s cost, i.e., related to costs on commuters’ end. A functional numerical example with the commuters’ demand is worked out by minimizing the cost function, which demonstrates the applicability of the framework. In our case study, PSO outclassed GA and DE on the basis of convergence rate. Since our work has proved the robustness of PSO as compared to GA and DE, we conducted our sensitivity analysis keeping PSO as our benchmark algorithm to study the influence of various parameters on the optimal cost. The computational experiments reveal that the optimal cost is substantially affected by the variations in the commuters’ demand, commuters’ walking speed, and value of the users’ access and in-vehicle time. On the contrary, the acceleration/deceleration delays at a bus station, bus operating cost, and headway have an inconsiderable impact on the optimal cost.