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The performance of transit signal priority (TSP) with conflicting priority requests highly depends on the serving sequence of multiple TSP requests. A series of existing methods have been developed to determine the priority level of requests. However, most of these methods focused on isolated intersections or a small number of intersections, which are not applicable to complex, dynamic and nonlinear urban traffic networks. In this regard, we propose a multi-agent TSP control method at the network level considering conflicting priority requests. Fuzzy inference is used to manage signal control. We further develop a specific control algorithm. The performance of the proposed method is verified by a case study with a sizeable traffic network with 20 intersections and 49 links. Simulation results demonstrate that the proposed method outperforms other three benchmarking methods under different traffic demands and bus departure frequencies. It is worth-noting that the improvement becomes more notable with the increase of traffic demands and the reduction of bus departure frequencies.

Travel reliability is the most essential determinant for operating the transit system and improving its service level. In this study, an optimization model for the electric transit route n...

Climate change affects the species spatio-temporal distribution deeply. However, how climate affects the spatio-temporal distribution pattern of related species on the large scale remains largely unclear. Here, we selected two closely related species in Taxus genus Taxus chinensis and Taxus mairei to explore their distribution pattern. Four environmental variables were employed to simulate the distribution patterns using the optimized Maxent model. The results showed that the highly suitable area of T. chinensis and T. mairei in current period was 1.964×105km2 and 3.074×105km2, respectively. The distribution area of T. chinensis was smaller than that of T. mairei in different periods. Temperature and precipitation were the main climate factors that determined the potential distribution of the two species. The centroids of T. chinensis and T. mairei were in Sichuan and Hunan province in current period, respectively. In the future, the centroid migration direction of two species was almost opposite. T. chinensis would shift towards southwest, while T. mairei towards northeast. Our results revealed that the average elevation distribution of T. chinensis was higher than that of T. mairei. This study sheds new insights into the habitat preference and limiting environment factors of the two related species and provides a valuable reference for the conservation of these two endangered species.

Tea oil obtained fromCamellia oleifera is a high-quality vegetable oil rich in squalene, a triterpenoid bioactive substance with several demonstrated health benefits. WRKY transcription factors in ...

Climate change affects the species spatio-temporal distribution deeply. However, how climate affects the spatio-temporal distribution pattern of related species on the large scale remains largely unclear. Here, we selected two closely related species in

Computer-Aided Civil and Infrastructure Engineering To prevent bus bunching, a dynamic headway control method in the V2I (vehicle to infrastructure) environment for a high-frequency route with bus lane is developed. Bus operating speed guidance on the mid-blocks and intersection signal adjustment are two main strategies in the proposed method. A forecasting model of bus travel time under the dynamic control method is developed. The objective function is set up by taking into account differences between actual bus headways and dispatching headways, and the scaling ratios of intersection cycle lengths. The optimization model is solved using genetic algorithm. The proposed method is applied to a real bus route in Meihekou city, China, and compared with the current control plan as well as holding strategy. Results show that the proposed method can reduce bus headway deviations in all investigating periods; negative impacts on cars can be limited by setting reasonable values for the parameters.

Many studies have examined the association between the built environment, residential self-selection, and travel behavior. However, few studies have quantified the relative contribution of the built environment itself. Using the 2012 Nanjing Household Travel Survey data, this study applied hierarchical clustering and propensity score weighting to study the effects of the built environment and residential self-selection on travel behavior. First, residents’ household locations were classified into four built environment patterns using hierarchical clustering based on six built environment variables by loosely following the “5Ds” (i.e., density, diversity, design, destination accessibility, and distance to transit). Second, a powerful machine learning method, generalized boosted model (GBM), was employed to obtain propensity scores. Propensity score weighting, which is more effective for multiple treatments than matching or stratification, was used to control for residential self-selection. Lastly, the observed effect (OBE), the average treatment effect on the population (ATE), and the built environment proportion (BEP) were calculated for the walking trip frequency, bicycle trip frequency, public transit trip frequency, and vehicle kilometers traveled (VKT) of six pairs of built environment patterns. The results show that a high-density, mixed-use, walkable, and transit-accessible built environment is associated with more walking trips and lower VKT but has no impact on bicycle trips and has an inconsistent impact on public transit trips. The effects of some built environment variables on bicycle and public transit trips are tangled. The residential self-selection effect has the greatest impact on VKT (BEP: 48%–77%), followed by the walking trip frequency (BEP: 62%–74%) and the public transit frequency (BEP: 90%–107%).

Accessibility is important for road network planning and design, especially the accessibility of freeway entrances and exits, which reflects the convenience of travelers using freeways and the rationality of the connection between urban roads and freeways. Based on the path information of navigation map software, a new comprehensive travel impedance model to dynamically analyze the accessibility of freeway entrances and exits was proposed. The dynamic accessibility of freeway entrances and exits in Zhengzhou was studied using the proposed comprehensive impedance model, and the calculation results were analyzed. The accessibility of freeway entrances and exits is characterized by dynamic changes, the accessibility during the off-peak evening period is the highest, while that during the morning peak period and evening peak period is lower. The results of the comprehensive impedance model are roughly consistent with reality. From a location perspective, regardless of the period of time, the accessibility of freeway entrances and exits in the central and surrounding areas of Zhengzhou is always at a lower level, and during the off-peak afternoon period, the accessibility of the eastern part of the city is notably higher than that of the western part. Additionally, the accessibility of freeway entrances and exits is closely related to the traffic status of the road network and the characteristics of regional land use. The information can provide feedback for planning road networks and provide a reference for road network planning and traffic facility design.

The rapid development of cities puts forward higher requirements for the resilience of the road network. As one of the unfavorable weathers, rainfall has a great impact on the operation of road traffic. Using weather and vehicle speed data of a city in China, this paper compares and analyzes changes in traffic operation indicators such as the standard speed and the percentage reduction of the standard speed under different rainfall intensities. Results indicate that under the same rainfall conditions and time period, the traffic operation of the elevated road is least affected by rainfall, and the traffic operation of underpass tunnels and flat roads is more affected by rainfall. With the increase of rainfall intensity, the reduction percentage of the standard speed of the underpass tunnel shows an increasing trend; however, it is less affected in light rain and moderate rain, and more affected in heavy rain and rainstorm. With the increase of rainfall intensity, the standard speed of the elevated road has no obvious change trend, and it is less affected by light rain and moderate rain, but more by rainstorm. In each time period, the standard speed reduction percentage of flat roads shows an obvious increasing trend with the increase of rainfall intensity.

Accessibility plays an important role in the field of transportation. In previous studies, due to the limitation of data sources, the research on dynamic accessibility is limited. In recent years, the emergence of new data sources provides possibilities for the dynamic accessibility. This paper summarizes four classic accessibility evaluation models, including the space separation measure, cumulative opportunities measure, potential accessibility measure, and space–time prism. Moreover, this paper introduces the limitations of traditional data sources and analyzes the characteristics of new data sources such as floating car data, smart cards data, mobile phone recording data, and navigation map (API) data. A comprehensive overview of the application of different data sources in transportation accessibility is also developed. Finally, this review study shows opportunities and challenges for transportation accessibility studies.

Modern roundabouts are widely used at intersections with light traffic, generally providing safety and other advantages. However, large entry delays are often observed at roundabouts with unbalanced flow patterns, even though the entry traffic flow is not high. A metering signal-based strategy is examined to mitigate the above problems. A mathematical optimisation model is formulated firstly with the objective of minimising the total entry delay, subject to the metering signal thresholds. Then a solution algorithm based on VISSIM simulation is developed. Finally, a case study is carried out to testify the feasibility and applicability of the proposed model. Extended scenarios analyses under different levels of approach volume, different demand combinations and different proportions of right-turn vehicles (left-side driving) are also conducted. Results show that the methodology can effectively improve the operational performance, and a delay reduction of up to 25.7% can be expected using the metering signal-based strategy. This can provide a criterion for the use of metering at the roundabout.

In the past two decades, the waiting area has been widely used in many large cities in China as an effective strategy to increase the capacity of at-grade signalized intersections, especially during peak hours. Unfortunately, despite its popularity and prevalence, there does not exist any quantitative technical/design standards for formulating the implementation of waiting area and evaluating its performance. It is an unconventional design from practice and its theoretical investigation is actually after it is implemented in numerous signalized intersections. In this regard, this paper presents an overview of existing research and applications with a focus on the traffic operations and performance evaluation of the waiting area in at-grade signalized intersections. We first emphasize the design and its integration with signal phasing. Then performance analysis is introduced. This is followed by a few critical remarks and directions of the future work.

With rapid urbanization, problems such as traffic congestion and air pollution have become increasingly serious in urban areas. Therefore, governments and transport planners in Chinese cities are devoting efforts to implement urban development policies and encourage the use of non-motorized modes (walking and cycling). Mode share of biking trips may be retained and possibly increased if safe and convenient urban road facilities for users are created. Therefore, this paper utilizes the survey data from Zhengzhou city to examine the relationship between the attributes of road infrastructure and the user-perceived friendliness of cycling, by using the logistic regression model. Results indicate that urban road grades, types of barriers, lane width, etc., have important impacts on the friendliness of the biking mode.

In order to alleviate traffic congestion and environmental pollution, many cities in China have gradually adopted traffic demand management strategies. Driving restriction policies of motorized vehicles are widely implemented. Zhengzhou City implemented the even–odd number restriction policy from 4 December to 31 December 2017. Thereafter, from 1 January 2018, the tail number of license plate restriction policy was utilized. Under this background, an online questionnaire about commuters’ trip characteristics before and after the driving restriction is designed. Using the survey data, commuters’ acceptance of driving restriction policies and the influence of restriction policies on their travel mode choices are investigated. Results show that under the even–odd number restriction policy, most commuters’ travel modes are transferred to private electric bicycles or bicycles, buses or subways; while under the tail number of license plate restriction policy, most commuters’ travel modes are transferred to cars-hailing service, buses or subways. Besides, most commuters prefer the driving restriction policy with two tail number of license plate per day. Because new energy vehicles are not included in driving restriction policies, some commuters tend to buy a second car with new energy.

Electric vehicles have been well recognized by many as a solution to reduce greenhouse emissions, improve mobility, and decrease energy consumption in the transportation system. In this paper, we propose a novel wireless charging scheme for electric vehicles. The proposed scheme deploys partial wireless charging lane to intersections, so as to utilize the slow movement of vehicles at traffic lights for recharging. Furthermore, an eco-driving control strategy for electric vehicles at intersections with wireless charging, i.e., W-eco-driving, is developed, aiming to decrease the total energy consumption and increase traffic efficiency. With the aid of connected and automated vehicles technology, driving and surrounding data are accessible in real-time. Then electric vehicles can be controlled using the W-eco-driving strategy accurately. The proposed strategy is finally validated based on a specific intersection configuration. Both single electric vehicle control and electric vehicle platooning are discussed in test examples. We also investigate the influences of wireless charging power, location and length. Numerical results show that the wireless charging scheme with W-eco-driving is able to increase the driving range and decrease the travel cost simultaneously. The total travel cost can be saved up to 16% by following W-eco-driving. We further provide some suggestions about the construction of wireless charging lanes in the vicinity of signalized intersections. Compared with the pursuit of a long wireless charging lane, it is more important to put it in a proper position in the early stage of construction.

Summary A schedule consisting of an appropriate arrival time at each time control point can ensure reliable transport services. This paper develops a novel time control point strategy coupled with transfer coordination for solving a multi-objective schedule design problem to improve schedule adherence and reduce intermodal transfer disutility. The problem is formulated using a robust mixed-integer nonlinear programming model. The mixed-integer nonlinear programming model is equivalently transformed into a robust mixed-integer linear programming model, which is then approximated by a deterministic mixed-integer linear programming model through Monte Carlo simulation. Thus, the optimal scheduled arrival time at each time control point can be precisely obtained using cplex. Numerical experiments based on three bus lines and the mass rapid transit system in Singapore are presented, and the results show that the schedule determined using the developed model is able to provide not only reliable bus service but also a smooth transfer experience for passengers. Copyright © 2016 John Wiley & Sons, Ltd.

The corrosion durability of bridge cables in operation is prominent. This study proposes an active protection method to apply impressed current cathodic protection (ICCP) to bridge cable parallel wires. The weight loss method, scanning electron microscopy, electrochemical test, and acoustic emission (AE) signal characteristic analysis were used to study the test method for electrochemical corrosion protection of cable parallel wires using rainwater conduction. Results show that cable wires are corroded on the surface and inside, whereas the cable wires with ICCP show different changes. The cable wires are effectively protected in the environment where a sodium chloride solution is used to simulate rainfall. In the AE test of the cable wires after corrosion using a signal generator, the main frequency of the AE signal gradually increases with the increase in corrosion degree. The high corrosion degree of the cable wires induces dispersion. The characteristics of AE signal can reflect the corrosion degree of the cable wires, and ICCP can decrease the corrosion rate of the cable wires.

It is well acknowledged that the seasonality (dry or rainy seasons) has significant impacts on crashes. Being able to differentiate the crashes that occur because of poor surface conditions (i.e., when the road is wet) is important for the economical use of available resources, as these segments of roads may only require signage and/or resurfacing. However, this effect is always ignored in the traditional black spot identification (BSID) techniques. This paper proposes an improved BSID model by taking into account the wet/dry crash rate ratio. Comparative study based on a high-speed motorway and a relatively low-speed urban arterials road is carried out. Results indicate that the proposed model has good applicability. The impact of rainfall has been minimized on the results of a BSID analysis.

© 2017 Kuang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. In this paper, we aim to examine the relationship between traffic flow and potential conflict risks by using crash surrogate metrics. It has been widely recognized that one traffic flow corresponds to two distinct traffic states with different speeds and densities. In view of this, instead of simply aggregating traffic conditions with the same traffic volume, we represent potential conflict risks at a traffic flow fundamental diagram. Two crash surrogate metrics, namely, Aggregated Crash Index and Time to Collision, are used in this study to represent the potential conflict risks with respect to different traffic conditions. Furthermore, Beijing North Ring III and Next Generation SIMulation Interstate 80 datasets are utilized to carry out case studies. By using the proposed procedure, both datasets generate similar trends, which demonstrate the applicability of the proposed methodology and the transferability of our conclusions.

When a bus is late and behind schedule, the stop-skipping scheme allows the bus vehicle to skip one or more stops to reduce its travel time. The deadheading problem is a special case of the stop-skipping problem, allowing a bus vehicle to skip stops between the dispatching terminal point and a designated stop. At the planning level, the optimal operating plans for these two schemes should be tackled for the benefits of bus operator as well as passengers. This paper aims to propose a methodology for this objective. Thus, three objectives are first proposed to reflect the benefits of bus operator and/or passengers, including minimizing the total waiting time, total in-vehicle travel time and total operating cost. Then, assuming random bus travel time, the stop-skipping is formulated as an optimization model minimizing the weighted sum of the three objectives. The deadheading problem can be formulated via the same minimization model further adding several new constraints. Then, a Genetic Algorithm Incorporating Monte Carlo Simulation is proposed to solve the optimization model. As validated by a numerical example, the proposed algorithm can obtain a satisfactory solution close to the global optimum.

The design of urban bus transit systems aims to determine a network configuration with a set of bus lines and associated frequencies that achieve the targeted objective. This paper presents a methodology framework to formulate and solve the bus transit network design problem (TNDP). It first proposes a TNDP taking into account the travel time stochasticity. A robust optimization model is formulated for the proposed problem, which aims to minimize the sum of the expected value of the operator cost and its variability multiplied by a weighting value. A heuristic solution approach, based on k-shortest path algorithm, simulated annealing algorithm, Monte Carlo simulation, and probit-type discrete choice model, is subsequently developed to solve the robust optimization model. Finally, the proposed methodology is applied to a numerical example. (C) 2013 American Society of Civil Engineers.

The time control point strategy is often adopted by bus operators in China and Singapore to provide more reliable transit service. It is thus important to design a schedule, in which bus drivers should devote their efforts to catch up a scheduled arrival time at a predetermined time control point on a bus route because passengers can definitely benefit from a reliable bus route schedule. This paper first proposes a novel reliable bus route schedule design problem by taking into account the bus travel time uncertainty and the bus drivers’ schedule recovery efforts. It proceeds to develop a robust optimization model for the proposed problem, which aims to minimize the sum of the expected value of the random schedule deviation and its variability multiplied by a weighting value. A Monte Carlo simulation based solution method is subsequently designed to solve the robust optimization model. Finally, a numerical example based on a real bus route in Suzhou city of China is carried out to demonstrate the strength of the robust optimization model. We find that the optimal scheduled travel time (or slack time) depends on bus drivers’ schedule recovery behavior and on decision makers’ scheduling philosophies.

Real survey data are of considerable significance for transit planners and operators to assess the performance of a bus route and then improve its level of service. Automatic vehicle location (AVL) system is a convenient tool to collect a large amount of real data from buses. This paper aims to propose a methodology to evaluate the operational performance of a bus route based on AVL data. First, several statistical indexes are selected for the evaluation, including percentile travel times, coefficient of variation (COV) of travel times, and average commercial speed and travel time distribution. Moreover, spatial and temporal features of travel time variation and transit regulation indexes are analyzed. Then the bus route with transit signal priority and dedicated bus lane in Suzhou, China, is taken as a case study to validate the proposed methodology. Numerical tests indicate that the most influential feature of travel time is its spatial and temporal patterns, which vary across segments and time-of-day intervals. Bus lane violation and route repetition may undermine the efficiency of priority measures. In addition, the schedule design has important impacts on the adherence and headway regularity.

Electric vehicles are believed to be an effective solution for reducing greenhouse gas emissions. Despite extensive study on the attributes and characteristics of electric vehicles and their charging infrastructure design, the development and network modelling of electric vehicles are still evolving and limited. This article provides a comprehensive review of electric vehicle studies and identifies existing research gaps in the aspects of theories, modelling approaches, solution algorithms and applications. This article first describes the electric vehicles’ concepts, market share, characteristics and charging infrastructures. Then, the studies on traffic assignment problem with electric vehicles in the network and limited charging facilities are particularly discussed. We conclude that it is of great importance to take into account electric vehicles’ special characteristics (e.g. range limit) in predicting their routing behaviour and charging infrastructure design networks.

Because of the combination explosion problem, it is difficult to use probability analytical method to calculate the system reliability of large networks. The paper develops a stochastic simulation (Monte Carlo-based) method to study the system reliability and component probabilistic importance of the road network. The proposed method considers the characteristics of the practical road network as follows: both link (roadway segment) and node (intersection) components are emphasized in the road network; the reliability for a link or node component may be at the in-between state; namely, its reliability value is between 0 and 1. The method is then implemented using the object-oriented programming language C++ and integrated into a RARN-MGG (reliability analysis of road network using Monte Carlo, GIS, and grid) system. Finally, two numerical examples based on a simple road network and a large real road network, respectively, are carried out to characterize the feasibility and to demonstrate the strength of the stochastic simulation method.

The optimization of public transit network, with relevant to passengers, operators and department managers, which involved in many aspects including service, cost and performance, is the typical problem encountered in the construction of "transit metropolis". In order to solve the problem, this paper is mainly built a optimization model of the public transit network based on operational reliability analysis model and the analysis of the bus operational reliability and influencing factors, starting from three angles including the bus stations, bus lines and the transit network. Taken Swiss Road Network as an example, in contrast to the method of the paper (Yan, 2012), the feasibility analysis proves that the optimization method of the public transit network is 1 Foreword The operational reliability of public transit is the property of the urban public transit vehicles operating system, which can be used to study the system for the reaction of the random and uncertain external environment, and also reflects an important aspect of the quality of public transport services. Improving the public transit system reliability can enhance the public Transit system capacity , develop passenger efficiency and even attract passengers to choose the bus as an transportation tool. At present, the research of bus operational reliability is mainly in terms of network topology, service levels and capacity, among which the network topology is the key. The concept of reliability is originated from the complex systems theory (Ali,1998), refers to the probability of the system to achieve function within a predetermined time and condition. The process of transfer passengers in the urban transit includes from the starting point to walk to the bus station, waiting in a bus station, with buses operating, transferring from the bus station and walking to the destination. According to the intersection of the process occurs with urban transit, the reliability of the urban transit is divided into waiting time reliability, transfer reliability, operational reliability (2003). According to the operating characteristics of the public transit network, the operational reliability of public transport can be

Walking and cycling are important component in the urban transportation, residents’ life and leisure activities, especially in the medium and small cities. Improving the pedestrian and cycling environment is important, and the pedestrian and cycling planning plays an important role in the process. A pedestrian and cycling planning is introduced in this paper, taking Xuancheng, a medium-sized city as an example. Basing on the analysis of the existing conditions and issues of walking and cycling in Xuancheng, and considering the requirement of residents and the visions of upper level plannings, the planning goals including safety, priority and vibrancy are proposed as well as five objects to support these goals. Then, the planning strategies and actions including structure planning, differentiation district control, important district improvement, public transit access and advanced design guidelines are introduced in detail. At last, some suggestions are given to the planning implementation and management.

The scientific determination of bus headway is very important for bus transit in rural areas. The problem of setting bus headway on a transit network under deterministic conditions with time varying demand for service and operation cost is formulated as a mathematical programming problem. This paper first proposes a bus headway problem by taking into account the operators' profit and passengers' cost. It proceeds to develop a multi-objective optimization model for the proposed problem, which aims to minimize the social cost in terms of waiting time, inconvenience due to crowding in the bus, and operation cost. The genetic algorithm is subsequently designed to solve this optimization model. Finally, a numerical example based on a real route in Wujin city of China is carried out to demonstrate the strength of this optimization model. The results show that the model and the algorithm are feasible and effective.

Data envelopment analysis(DEA) is an optimization-based technique widely used to measure relative efficiencies of public transit agencies. This paper evaluates the performance of bus routes within a public transit system using the BCC model of DEA. We construct a concept framework of performance evaluation and select appropriate input and output indexes to compute the operation efficiency and service effectiveness of each bus route. Function-achievement is then analyzed and bus routes which need to be optimized and regulated are screened out. Twelve bus routes of Suzhou are selected for the practical application.