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The use of the Internet of things (IoT) devices is growing rapidly in the current industrial market. Integrating these devices into the network system has subjected the information to Cybersecurity attacks putting the market of IoT technology at risk. As a result, accurate protection algorithms and efficient monitoring systems need to be developed. This paper proposes a new framework design relays on a stochastic measurement of determining parameters based on a novel adaptive deep learning (ADL) algorithm for industrial manufacturing such as transportation, energy. The new framework will be designed to incorporate an element of randomness as opposed to deterministic frameworks. The implemented method considered the network forensic systems and intrusion detection (ID); therefore, the prediction model is set up to alert the administrator about the system status. The framework is proposed based on five prioritized protection stages. The developed model tested on the Bot-IoT dataset, which is well-structured and valid for training, as confirmed by literature. The result has shown the ability to simulate the IoT network traffic along with risk assessment against different types of attacks by using the ADL algorithm. The new framework will be designed to improve computational efficiency by being able to adjust their structure based on the inputs. The research contributions are that it will help in the development of an algorithm which can minimize traffic accidents, improve traffic flow, minimize energy wastes, and save costs of controlling traffic flow. Findings show that using this new algorithm has 100% accuracy, which makes it an excellent choice for the detection of threats and errors. [ABSTRACT FROM AUTHOR]

Beijing is China's national capital, a major economic center, and home to nearly 22 million people. The city currently suffers from serious traffic congestion and extreme air pollution. Beijing's metropolitan government is currently considering implementation of a congestion charging system intended to discourage the use of private motor vehicles and encourage a shift to public transportation. Nearly 1500 Beijing-area business managers responded to a survey asking their opinions about the system. The data was analyzed using multinomial logit modeling and cluster analysis to identify the major sources of support and non-support for the proposed system, and to create profiles of "typical" businesses that support, are neutral to, or oppose the system. These results indicate that support for the system is highest among small businesses located in the city's central business district, where there is significant traffic congestion and good access to public transportation. Support is weakest among large businesses located in outer suburbs with relatively limited public transit. Business managers' level of understanding of congestion charging and the extent to which they think it will successfully reduce traffic congestion and improve air quality were major factors in support or non-support for the proposed system. The results indicate that providing clear and credible information about the way the proposed system will work, how the revenue from congestion charging will be used, and the transportation and environmental benefits of the system are essential to gaining support from the business community. [ABSTRACT FROM AUTHOR]

A promising methodology is proposed to estimate reliable annual average daily traffic (AADT) volumes for no-surveyed road sections using probe volumes collected by a vehicle global positioning system (GPS). This research was inspired by the obvious concept that probe counts are a direct portion of AADT from the viewpoint of vehicle trip behavior. The method converts the probe volume of target road section to AADT using the nonlinear relationship between geographical neighborhoods composed of observed AADT volumes and annual average daily probe volumes. The relationship is determined with a locally weighted power-curve model. A feasibility of the proposed method was demonstrated through a case study using real-world data. Analysis results show that the proposed method is a practical and cost-effective way to estimate reliable AADT for unmeasured road segments. This indicates that there exists a strong relationship between AADT values and vehicle-GPS probe values from the trip characteristics of a road network. [ABSTRACT FROM AUTHOR]

With the progress of society and the acceleration of urbanization, the problem of multimedia assisted urban traffic is becoming increasingly apparent. Intelligent transportation system arises at the historic moment, but the road traffic information data accumulation of intelligent transportation system is quite large, and the information analysis is complex. Usually, there are huge amounts of data stored in the database of the traffic system, thus we need to analyze and manage the data with scientific methods. As the visualized tools, the multimedia based analysis for the on-time data conditions should also be integrated, therefore, how to effectively model the scenario is challenging. In this paper, we introduce and analyze the structure and related model of recurrent neural network, and apply RNN to traffic big data mining model. According to the characteristics of traffic flow, this paper analyzes the causes of the error data in the process of traffic data collection, and puts forward the corresponding processing methods. The proposed model uses the TensorFlow for development, and applies the proposed deep learning model to implement traffic data mining, and we use charts to visually show the prediction results. Experimental results show that proposed algorithm can effectively mine large traffic multimedia data and has good robustness. At the same time, the prediction accuracy has reached 97.36%. [ABSTRACT FROM AUTHOR]

This paper proposes a subway energy regeneration model, based on control stops and train departures throughout his trip, with the use of energy from the regenerative braking in the drive system. The goal is to optimize the power consumption and improve efficiency, in view of sustainable management. Applying genetic algorithm to get the better of the trains' traffic configuration, the research develops and tests the Traction Control Algorithm for Subway Energy Regeneration (ACTREM), using the Scilab program. To analyze the performance of ACTREM control algorithm in enhancing energy efficiency, there were fifteen simulations of applying ACTREM on line 4—Yellow subway in São Paulo. These simulations showed the ACTREM efficiency to generate automatically diagram schedules optimized for energy savings in metro systems, considering the system's operational constraints such as maximum each train capacity, total wait time, total travel time and interval between trains. The results show that the proposed algorithm can save 9.5% of the energy and does not cause significant impacts on the transportation system capacity passengers and also suggest possible continuity studies. [ABSTRACT FROM AUTHOR]

Traffic surveillance is an important issue in intelligent transportation systems. Efficient and accurate vehicle detection is one challenging problem for complex urban traffic surveillance. As such, this paper proposes a new vehicle detection method using spatial relationship GMM for daytime and nighttime based on a high-resolution camera. First, the vehicle is treated as an object composed of multiple components, including the license plate, rear lamps and headlights. These components are localized using their distinctive color, texture, and region feature. Deriving plate color converting model, plate hypothesis score calculation and cascade plate refining were accomplished for license plate localization. Multi-threshold segmentation and connected component analysis are accomplished for rear lamps localization. Frame difference and geometric features similarity analysis are accomplished for headlights localization. After that, the detected components are taken to construct the spatial relationship using GMM. Finally, similar probability measures of the model and the GMM, including GMM of plate and rear lamp, GMM of both rear lamps and GMM of both headlights are adopted to localize vehicle. Experiments in practical urban scenarios are carried out under daytime and nighttime. It can be shown that our method can adapt to the partial occlusion and various lighting conditions well, meanwhile it has a fast detection speed. [ABSTRACT FROM AUTHOR]

Introduction: The planning of transport infrastructures in France has been marked by three major developments: the European reform concerning the opening of rail transport to competition, the privatisation of semi-public motorway concession-holding companies, and the use of public-private partnership contracts. This article proposes examining the following research question: how to plan a series of infrastructure projects within an uncertain context? The methodology: (i) analyses whether the objectives (traffic, travel time, safety, cost, socio-economic profitability, financial profitability) of the 12 motorway and HSL projects built since the 1990s have been attained with the new planning procedure (such as risk management methods, financial risk assessment, impact assessment, public consultation) (ii) compares the additional costs and delays for three HSL projects according to their type of financing and whether or not they have used these planning procedures. Results: The analysis shows that traffic levels are lower than forecasts for 8 projects. The cost is greater than the forecasts for all infrastructures. The socio-economic profitability and the financial profitability are also lower than forecasts for approximately two-thirds of the projects. Conclusion: The social, political, institutional and environmental risks are generally well identified and treated by the client, no matter whether public or private.. The risk of additional cost is less well covered. The traffic risk remains a topical issue. Anticipating risks is liable to produce other risks, such as overcosts or opposition. It seems necessary to deepen the traffic forecast studies and to develop the multi criteria analysis method that can take account of the different points of view from the consultation. [ABSTRACT FROM AUTHOR]

This paper models the relationship between vehicle miles traveled (VMT) on local and collector roads with an objective to predict local road VMT by using collector road VMT. Through a continuous approximation method typically used for vehicle routing, it first analytically reveals this relationship mainly as a function of roadway density ratios between multiple roadway classifications. This structural relationship suggests regression equations using density ratios or logarithmic values of them as the explanatory variables. The use of regression equations enables to account for varying spatial distributions of roadways and demand through parameter calibration. The proposed regression equations are proved good fits through computer simulation using distinct community road network topologies. In addition, practical data from Hennepin County of Minnesota, U.S.A. that encompasses Minneapolis indicates that our developed regression equations can work well. [ABSTRACT FROM AUTHOR]

This study investigates different methods to visualise uncertainty in static representations of probabilistic traffic models predictions on road-networks. Although various graphical cues may be used to represent uncertainty it is not a priori clear which of them are most suited for this purpose, since their legibility, intelligibility and the degree to which they interfere with other graphical elements in a representation differ widely. Several graphical uncertainty representations were therefore developed and analysed in expert sessions. A selection of the initial set of uncertainty visualisations was further evaluated in a cognitive alternative task-switching experiment. The results show that graphical representations are able to convey uncertainty information relatively accurately, while some uncertainty visualisations outperform others. It depends on the model and scenario which representation is most suited for a given application. This paper presents an overview of possible graphic uncertainty representations and the considerations involved when applying them to uncertainty in traffic model visualisations. [ABSTRACT FROM AUTHOR]

Ensuring a minimum operational level of road networks in the presence of unexpected incidents is becoming a hot subject in academic circles as well as industry. To this end, it is important to understand the degree to which each single element of the network contributes to the operation and performance of a network. In other words, a road can become an "Achilles-heel" for the entire network if it is closed due to a simple incident. Such insight of the detrimental loss of the closure of the roads would help us to be more vigilant and prepared. In this study, we develop an index dubbed as Achilles-heel index to quantify detrimental loss of the closure of the respective roads. More precisely, the Achilles-heel index indicates how many drivers are affected by the closure of the respective roads (the number of affected drivers is also called travel demand coverage). To this end, roads with maximum travel demand coverage are sorted as the most critical ones, for which a method-known as "link analysis"-is adopted. In an iterative process, first, a road with highest traffic volume is first labeled as "target link," and second, a portion of travel demand which is captured by the target link is excluded from travel demand. For the next iteration, the trimmed travel demand is then assigned to the network where all links including the target links run on the initial travel times. The process carries on until all links are labeled. The proposed methodology is applied to a largesized network of Winnipeg, Canada. The results shed light on also bottleneck points of the network which may warrant provision of additional capacity or parallel roads. [ABSTRACT FROM AUTHOR]

As to large-scale logistics transportations, road transport plays the primary role and route planning is often used to find the shortest path to save cost. However beside fuel consumption, many other costs on the road, such as tolls contribute a lot to the road transport cost, so cutting down the total cost while maintaining efficiency is very important for logistic businesses in many cases where the shortest path may be not the really optimal route. Based on Geographic Information System, one of the key technologies of intelligent traffic system, such as Google Maps, this paper presents a transportation optimization framework which integrates the cost computation including tolls into route planning with time constraints. It can reduce the total cost for long distance shipment and intra-city short distance freight as well while still satisfying the time constraints, which is very crucial for areas with many toll gates with diverse toll policies in China. The experiment verifies usability and validity of the present tool. [ABSTRACT FROM AUTHOR]

In common with the rest of the developed world, road traffic noise has been a public policy issue in Australia for many years. From attitudinal studies relating to noise in the environment, it is consistently shown that the higher annoyance scores for noise heard within the home result from road traffic noise. Governments in Australia, at all levels, have responded with a range of traffic noise management measures. At the federal government level these have primarily related to reducing noise at the source, namely the vehicle. State governments have developed traffic noise policies to guide the design for major roads and to control the planning of new noise-sensitive areas adjacent to major road corridors. Local governments have also considered traffic noise and introduced local traffic management measures on roads they control. This paper reviews and discusses the approaches in the different policies in current use in Australian states and territories for the management of road traffic noise. [ABSTRACT FROM AUTHOR]

Tolls have increasingly become a common mechanism to fund road projects in recent decades. Therefore, improving knowledge of demand behavior constitutes a key aspect for stakeholders dealing with the management of toll roads. However, the literature concerning demand elasticity estimates for interurban toll roads is still limited due to their relatively scarce number in the international context. Furthermore, existing research has left some aspects to be investigated, among others, the choice of GDP as the most common socioeconomic variable to explain traffic growth over time. This paper intends to determine the variables that better explain the evolution of light vehicle demand in toll roads throughout the years. To that end, we establish a dynamic panel data methodology aimed at identifying the key socioeconomic variables explaining changes in light vehicle demand over time. The results show that, despite some usefulness, GDP does not constitute the most appropriate explanatory variable, while other parameters such as employment or GDP per capita lead to more stable and consistent results. The methodology is applied to Spanish toll roads for the 1990-2011 period, which constitutes a very interesting case on variations in toll road use, as road demand has experienced a significant decrease since the beginning of the economic crisis in 2008. [ABSTRACT FROM AUTHOR]

This paper presents a transportation spatio-temporal system that efficiently converts traffic video data into vehicular motion information in spatio-temporal databases for a variety of transportation applications. The proposed transportation spatio-temporal system interpolates the vehicle trajectory data (i.e., time, location, and speed), which are extracted from video, and integrates them with spatial road information for storage of dynamic transportation environments. The proposed transportation spatio-temporal system can mitigate data storage and retrieval issues related to storing large amounts of traffic video. Moreover, users can manage and operate multiform and multidimensional traffic data in a spatio-temporal transportation environment. The proposed approach is demonstrated for typical transportation applications. The experimental results show that the proposed transportation spatio-temporal system has excellent potential for addressing issues related to storage of large amounts of traffic video data. [ABSTRACT FROM AUTHOR]

The paper proposes the microscopic travel demand model continuous target-based activity planning (C-TAP) that generates multi-week schedules by means of a continuous planning approach with an open planning horizon. C-TAP introduces behavioral targets to describe people's motivation to perform activities, and it uses a planning heuristic to make on-the-fly decisions about upcoming activities. The planning heuristic bases its decisions on three aspects: a discomfort index derived from deviations from agents' past performance with regard to their behavioral targets; the effectiveness of the immediate execution; and activity execution options available in the near future. The paper reports the results of a test scenario based on an existing 6-week continuous travel diary and validates C-TAP by comparing simulation results with observed behavioral patterns along several dimensions (weekday similarities, weekday execution probabilities of activities, transition probabilities between activities, duration distributions of activities, frequency distributions of activities, execution interval distributions of activities and weekly travel probability distributions). The results show that C-TAP has the capability to reproduce observed behavior and the flexibility to introduces new behavioral patterns. [ABSTRACT FROM AUTHOR]

This paper addresses the highway pavement rehabilitation scheduling and toll pricing issues over a planning horizon. In the highway system concerned, two types of agents are considered, namely highway operator and road users. Two models, which account for different highway regulatory regimes (i.e. public and private), are proposed. In the public regulatory model, the government aims to maximize total discounted social welfare of the transportation system over the planning horizon by determining the optimal pavement rehabilitation schedule and toll level. In the private regulatory regime, a profit-driven private operator seeks to optimize the pavement rehabilitation schedule and toll level to maximize its own discounted net profit over the planning horizon. The proposed models treat the interactions between the highway operator and the road users in the system as a bi-level hierarchical problem in which the upper level is a multi-period pavement rehabilitation scheduling and toll pricing problem, while the lower level is a multi-period route choice equilibrium problem. A heuristic solution algorithm that combines a greedy approach and a sensitivity analysis based approach is developed to solve the proposed bi-level multi-period optimization models. An illustrative example is used to show the applications of the proposed models. The findings show that the highway regulatory regime, pavement deterioration parameter and the roughness-induced vehicle operating cost can significantly affect the pavement rehabilitation schedules and the toll level as well as the performance of transportation system in terms of total life-cycle travel demand, net profit and social welfare. [ABSTRACT FROM AUTHOR]

In a transportation hub complex (THC) in China, ticket entrance gates and station exits are common bottlenecks. Although road traffic in China follows right-hand traffic rules, the influence of right-hand traffic rules on the movement characteristics of pedestrians passing through such facility bottlenecks have been investigated rarely. In this article, simulation experiments are conducted to investigate the effect of THC bottle-necks on pedestrian movement characteristics given the existence of right-hand road traffic rules. Based on the use of a combination of histograms of oriented gradients and support vector machine algorithms, the movement behavior of pedestrians passing through multiple parallel bottlenecks are extracted. A total of 21 scenarios are considered in this simulation experiment, consisting of two-opening and three-opening parallel bottlenecks, where the width of each opening and width of the barriers between adjacent openings are varied. This study provides fundamental data for pedestrian flow passing through multiple parallel bottlenecks, data that can help identify important parameters for the design and improvement of many kinds of pedestrian flow management facilities. Results from the study also will be useful for the development and verification of evacuation models. [ABSTRACT FROM AUTHOR]

Background, aim, and scope An inclusion of traffic noise effects could change considerably the overall results of many life cycle assessment (LCA) studies. However, at present, noise effects are usually not considered in LCA studies, mainly because the existing methods for their inclusion do not fulfill the requirement profile. Two methods proposed so far seem suitable for inclusion in generic life cycle inventory (LCI) databases, and a third allows for inter-modal comparison. The aim of this investigation is an in-depth analysis of the existing methods and the proposition of a framework for modeling road transport noise emissions in LCI in accordance to the requirement profile postulated in part 1. Materials and methods This paper analyzes three methods for inclusion of traffic noise in LCA (Danish LCA guide method, Swiss EPA method, and Swiss FEDRO method) in detail. The additional basis for the analysis are the Swiss road traffic emission model "SonRoad," traffic volume measurements at 444 sites in the Swiss road network, vehicle-type-specific noise measurements in free floating traffic situations in Germany, and noise emission measurements from different tires. Results The Danish LCA guide method includes a major flaw that cannot be corrected within the methodological concept. It applies a dose-response function valid for average noise levels of a traffic situation to maximum noise levels of single vehicles. The Swiss FEDRO method is based on an inappropriate assumption since it bases distinctions of specific vehicles on data that do not allow for such a distinction. Noise emissions cannot be distinguished by the make and type of a vehicle since other factors, especially the tires, are dominant for noise emissions. Several problems are also identified in the Swiss EPA method, but they are not of a fundamental nature. Thus, we are able to base a new framework for vehicle and context-sensitive inclusion of road traffic noise emissions in LCI on the Swiss EPA method. We show how specific vehicle classes can be distinguished, how the influence of different tires can be dealt with, and what temporal and spatial aspects of traffic need to be distinguished. Discussion While the Danish LCA guide method and the Swiss FEDRO method are not suitable for our purpose, the Swiss EPA method can be used as a basis to better meet the requirement profile identified in Part 1 of this paper. The proposed method for consistent, contextsensitive modeling of noise emissions from road transports in LCI meets all the requirements except that it is restricted to road transport. Conclusions We show limitations of the existing methods and approaches for improving them. Our proposed model allows for a more specific consideration of the various vehicles and contexts in terms of space and time and thus in terms of speed and traffic volume. This can be used on one hand for a consistent, context sensitive assessment of different vehicles in different traffic situations. On the other hand, it also allows for an inclusion of noise in LCA of transports on which only very little is known. This new LCI model meets five of the six requirements postulated in Part 1. Recommendations and perspectives In a next step, additional noise emissions due to additional traffic needs to be calculated based on the proposed framework and national or regional traffic models. Furthermore, the consideration of noise from different traffic modes should be addressed. The approach presented needs to be extended in order to make it also applicable for rail and air traffic noise, and the methods need to be implemented in LCI databases to make them easily available to practitioners. Furthermore, suitable impact assessment methods need to be identified or developed. They could base on the proposals made in the Swiss EPA and in the Swiss FEDRO methods. [ABSTRACT FROM AUTHOR]

The efficiency of traffic flows in urban areas is known to crucially depend on signal operation. Here, elements of signal control are discussed, based on the minimization of overall travel times or vehicle queues. Interestingly, we find different operation regimes, some of which involve a “slower-is-faster effect”, where a delayed switching reduces the average travel times. These operation regimes characterize different ways of organizing traffic flows in urban road networks. Besides the optimize-one-phase approach, we discuss the procedure and advantages of optimizing multiple phases as well. To improve the service of vehicle platoons and support the self-organization of “green waves”, it is proposed to consider the price of stopping newly arriving vehicles. [ABSTRACT FROM AUTHOR]

Abstract  This paper describes a system for detecting and estimating the properties of multiple travel lanes in an urban road network from calibrated video imagery and laser range data acquired by a moving vehicle. The system operates in real-time in several stages on multiple processors, fusing detected road markings, obstacles, and curbs into a stable non-parametric estimate of nearby travel lanes. The system incorporates elements of a provided piecewise-linear road network as a weak prior. Our method is notable in several respects: it detects and estimates multiple travel lanes; it fuses asynchronous, heterogeneous sensor streams; it handles high-curvature roads; and it makes no assumption about the position or orientation of the vehicle with respect to the road. We analyze the system’s performance in the context of the 2007 DARPA Urban Challenge. With five cameras and thirteen lidars, our method was incorporated into a closed-loop controller to successfully guide an autonomous vehicle through a 90 km urban course at speeds up to 40 km/h amidst moving traffic. [ABSTRACT FROM AUTHOR]

The present study aims to compute the temporal and spatial distribution of road traffic induced noise pollution in an urban environment by monitoring and mapping. The study area was the entire Asansol city of West Bengal, India. A total of 35 locations were selected for collection of data, classified as industrial, commercial, residential, sensitive and mixed areas according to the national regulatory standards. Noise recordings were conducted during morning and night hours. Day time Leq level ranged between 51.2 and 89.0 dB(A), whereas it ranged between 43.5 and 81.9 dB(A) during night. The average Ldn value was 73.28 ± 8.51 dB(A) (Range: 55.1-87.3); The traffic noise index was 80.62 ± 15.88 dB(A) (Range: 49.4-115.8). The computed data were mapped by utilization of Geographic information system methodology that allowed the visualization and identification of the extent and distribution of sound pollution across the study area. This proves to be an ideal tool for carrying out noise impact assessments in urban settings. The study reveals that present noise level in all the locations exceeds the prescribed limit. Based on the finding, it can be mentioned that the population in this industrial town are exposed to significantly high noise level, which is caused mostly due to road traffic. The study reveals that vulnerable establishments like schools and hospitals are subjected to significantly high noise level throughout the day and immediate mitigatory measures are required to alleviate the problem. [ABSTRACT FROM AUTHOR]

The lack of effective and efficient schedule-based pathfinding algorithms for transit networks has limited the application of GIS in transit trip planning services. This paper introduces a schedule-based path finding algorithm for transit networks. Based on a pattern-centered spatiotemporal transit network model, the algorithm searches the network by following route patterns. A pattern is a spatial layout of a route in transit terminology. A route usually has many patterns to serve various locations at different times. This path search algorithm is significantly different from traditional shortest path algorithms that are based on adjacent node search. By establishing a set of lemmas and theorems the paper proves that paths generated by the PFS algorithm are schedule-coordinated fastest paths for trips with given constraints. After analyzing computation and database query complexities of the algorithm the paper indicates that the PFS is efficient in computation and database query. Finally, effectiveness and efficiency of the algorithm are demonstrated by implementations in GIS-based online transit trip planners in Wisconsin, US. [ABSTRACT FROM AUTHOR]

By introducing relative velocities of arbitrary number of cars ahead into the full velocity difference models (FVDM), we present a forward looking relative velocity model (FLRVM) of cooperative driving control system. To our knowledge, the model is an improvement over the similar extension in the forward looking optimal velocity models (FLOVM), because it is more reasonable and realistic in implement of incorporating intelligent transportation system in traffic. Then the stability criterion is investigated by the linear stability analysis with finding that new consideration theoretically lead to the improvement of the stability of traffic flow, and the validity of our theoretical analysis is confirmed by direct simulations. In addition, nonlinear analysis of the model shows that the three waves: triangular shock wave, soliton wave and kink-antikink wave appear respectively in stable, metastable and unstable regions. These correspond to the solutions of the Burgers equation, Korteweg-de Vries (KdV) equation and modified Korteweg-de Vries (mKdV) equation. [ABSTRACT FROM AUTHOR]

The article reports on the reliability and emergency issues in transportation network analysis. The main sources of uncertainty include demand and supply variation which is caused by the day-to-day fluctuation of the travel demand or by the variation in the travelers' behaviors. Its impact on the economy affects efficiency of the logistics and transport system or a threat to national security and safety.

This paper develops a sensitivity analysis for the continuum traffic equilibrium problem of a city with several competing facilities. In the city, the customers’ origins are continuously dispersed. We assume that the customer demand is dependent on the total cost of patronizing these facilities. Specific travel cost–flow relationships are considered. The choice of facility in the continuum transportation system follows a user equilibrium principle in which from each origin, no customer can reduce their individual cost to patronize any of the facilities by unilaterally changing route or facility. The problem can be formulated as a minimization problem that is subject to a set of constraints and solved with a finite element method. The sensitivity analysis is based on the implicit function theorem at the equilibrium solution. A numerical example is presented to illustrate the applications of these sensitivity analysis results. [ABSTRACT FROM AUTHOR]

The need for acquiring the current-year traffic data is a problem for transport planners since such data may not be available for on-going transport studies. A method is proposed in this paper to predict hourly traffic flows up to and into the near future, using historical data collected from the Hong Kong Annual Traffic Census (ATC). Two parametric and two non-parametric models have been employed and evaluated in this study. The results show that the non-parametric models (Non-Parametric Regression (NPR) and Gaussian Maximum Likelihood (GML)) were more promising for predicting hourly traffic flows at the selected ATC station. Further analysis encompassing 87 ATC stations revealed that the NPR is likely to react to unexpected changes more effectively than the GML method, while the GML model performs better under steady traffic flows. Taking into consideration the dynamic nature of the common traffic patterns in Hong Kong and the advantages/disadvantages of the various models, the NPR model is recommended for predicting the hourly traffic flows in that region. [ABSTRACT FROM AUTHOR]

Improving train traffic control can be a cost-efficient way to improve train traffic punctuality and increase utilization of existing and future railway infrastructure. However, performance in train traffic control tasks currently involves working on a technical level in order to regulate the traffic flow. Working in a preventive manner is poorly supported and train traffic controllers are usually restricted to just solving problems as they occur. This often results in unnecessarily long delays and decreased timeliness of train traffic. The main objective of this paper is to describe a proposed control strategy and a case study, which evaluates the control strategy and the prototype tool derived from the research. By shifting the control paradigm to a high-level control strategy, many of today’s problems may be avoided, with benefits of the reduction in delays, improved timeliness and better utilization of the infrastructure. Twenty-one train traffic controllers participated in a case study, with a simulated prototype environment. The majority of the participating train traffic controllers were positive to the new concepts and ideas. Many of the important aspects of the proposed control strategy can be investigated with the simulation, but due to the complexity of train traffic some issues must be evaluated in an operative environment. [ABSTRACT FROM AUTHOR]

The objective of this paper is to introduce the innovative transport policies of Seoul that have recently been planned and implemented. In this paper, the various transport policies of Seoul are classified and explained according to two important paradoxes that are highlighted by Downs and Thomson, and Edgeworth. These paradoxes describe how to break the vicious circle of car and public transport use by restraining car use and encouraging the use of public transport, and thus indicate how traffic congestion problems might be solved. [ABSTRACT FROM AUTHOR]

For some decades now, transport researchers have put considerable efforts into developing what is called activity-based approaches for modelling urban travel demand. The basic idea is that travel demand is derived from people’s desires to take part in different activities. In particular, the interrelationships among different activities with respect to temporal and spatial constraints are in focus. It means that such models treat the activities and the travelling of the households with respect to where and when the activities can be carried out and how they may be scheduled, given characteristics of the households and potential opportunities, the transport networks and various institutional constraints. We discuss what demands we see on future travel demand models, with a focus on urban analysis. This discussion is somewhat biased towards what role activity-based models could play in meeting these demands. We then review in some detail three prominent and distinctly different representatives of operational activity-based models to give an indication of what new modelling possibilities they offer. Theoretical appeal, empirical validity, usefulness for planning, need for data and easiness of implementation are discussed. In the final section we draw some conclusions about the prospects of these models and of their descendants. [ABSTRACT FROM AUTHOR]

A new method for performing Dynamic Traffic Assignment (DTA) is presented which is applicable in real time, since the solution is based on feedback control. This method employs the design of nonlinear H∞ feedback control systems that is robust to certain class of uncertainties in the system. The solution aims at achieving user equilibrium on alternate routes in a network setting. Simulation results are provided for a sample simple network to show the effectiveness of this method. [ABSTRACT FROM AUTHOR]

A model of long-distance railway freight traffic with multiple intermediate stations and a given system of monitoring was described. [ABSTRACT FROM AUTHOR]

Transportation systems exist to improve individual accessibility. However, emerging applications of GIS in transportation (GIS-T) and intelligent transportation system (ITS) focus on throughput (the amount of system flow) rather than accessibility. Throughput is related but not equivalent to accessibility. Sensitive transportation planning requires rigorous, realistic and tractable accessibility measures. This paper reports on the development of GIS software that implement space-time accessibility measures (STAMs). The STAMs reflect the benefits that individuals receive from the transportation system. They are easily interpreted, particularly with respect to changes in accessibility. The STAMs also consider the locations and travel velocities dictated by the transportation system as well as individuals’ daily activity schedules. Tractable computational procedures allow calculation of the STAMs for detailed, urban-scale transportation networks. A prototype ArcInfo$^\circledR$-linked software system that runs on Windows NT$^\circledR$ or Sun Solaris$^\circledR$ platform implements the STAMs with user-friendly interfaces and project management tools. [ABSTRACT FROM AUTHOR]

The evolution of GIS-T is characterized in three stages: the map view, the navigational view, and the behavioral view. The static nature of the map view favors applications related to inventory and description, and raises difficult questions of accuracy and interoperability. The navigational view adds concerns for connectivity and planarity, and the storage of time-dependent attributes. Navigation also raises issues of representation related to scale, including the need for lane-level connectivity. The behavioral view stems from the work of Hägerstrand, treating transportation events as dynamic and occurring within the largely static transportation space. Appropriate representations for the behavioral view have still to be worked out. In all three cases the legacies of prior technologies and perspectives are still evident. The paper presents a series of research challenges, dealing with standards, representation, unambiguous communication, economic models, response to new technologies, and application of knowledge gained from GIS-T and ITS research to other fields. [ABSTRACT FROM AUTHOR]

This paper gives the definitions of transport telematics and intelligent transport systems (ITS), and describes the basic pre-conditions, situation and market of ITS as well as its applications (products and services) in Europe. Availability of navigable digital maps is emphasized as a major premise. Strategic aspects and key issues for ITS development are explained. Current weaknesses and prospects for ITS services in 20 years are discussed. It is concluded that ITS will make a major contribution to the sustainable development of our society, because it increases our mobility without additional environmental burdens. [ABSTRACT FROM AUTHOR]

The transportation impacts of center-based telecommuting for 24 participants (representing 69 person-days of travel and 295 trips) in the California Neighborhood Telecenters Project are analyzed. Comparing non-telecommuting (NTC) day to telecommuting (TC) day travel shows that person-trips did not change significantly, whereas vehicle-trips increased significantly (by about one trip) on TC days. Both PMT and VMT decline significantly on TC days: by an average of 68 miles (74%) and 38 miles (65%), respectively. When these savings are weighted by the frequency of telecommuting, overall reductions in PMT and VMT come to 19% and 17%, respectively, of total weekday travel. Commute trips increase slightly (by 0.5 trips) but significantly, mainly due to lunch-time trips made home from the telecenter. Total non-commute travel does not increase, but there is a significant shift from other modes to driving alone on TC days. Commute mode split on NTC days is not affected by telecommuting. Travel on TC days tends to be compressed into fewer hours. Higher numbers of return home, eat meal, shopping, and social/recreational trips are made on TC days, in exchange for a reduction (to zero) in the number of change mode trips. [ABSTRACT FROM AUTHOR]

An analytical model for the determination of the number and locations of time points as well as the amount of slack times in transit schedule design is developed. The model considers a bus route with a special passenger demand pattern in which all boarding passengers coordinate their arrivals at each stop in such a way that they never miss their intended bus, and therefore designing the schedule separately, a single run at a time, becomes possible. The model employs the dynamic programming method to deal with the trade-offs among various cost components associated with the schedule quantitatively, and yet is flexible enough to incorporate the existing rules of thumb as well as transit operators' policies. Numerical examples that illustrate the applications of the model are given. The model, although not quite applicable to bus routes with general passenger demand patterns, is useful in the analysis of the contributing factors to the design of an economical, reliable, and operational transit schedule, and is likely to be adaptable for more realistic cases. [ABSTRACT FROM AUTHOR]

A basic issue in the planning of urban public transport is the determination of headways or inter-dispatch times. During each season, i.e. distinct time-period whose demand characteristics are constant, the following tradeoff must be considered. Dispatching too many vehicles on a route causes high operating costs, while too few vehicles may result in unsatisfactory levels of service. An appropriate policy on headways will help to balance resources between lines (routes) in peak-demand hours and will influence the total number of buses acquired by a transit company. Previous practice in industry usually bases the planning of headways upon satisfying service criteria on a ‘most-congested segment’. This approach reduces the problem from that of studying a route to that of a single segment (stop), but thereby fails to account for other important information about the line's characteristics. In this article, we develop two new service criteria which consider the line as a whole: (1) ‘crowding-overdistance’ takes into account discomfort resulting from a vehicle carrying too many passengers, and the corresponding distance travelled; and (2) ‘probability-of-failure’, the frequency with which a waiting passenger fails to board due to lack of space. COD will be analyzed using simulation. POF will be related to a time-dependent Markov chain that is ‘inhomogeneous’ in terms of distance along the route. Optimal headways are those which dispatch the smallest number of buses while meeting the particular service criterion. Models based on each of the two criteria are illustrated and applied to a number of routes of the Israeli transit company, DAN. [ABSTRACT FROM AUTHOR]

Comments on transportation as one of the most important geographic phenomenon. Emergence of the term intelligent transportation systems; Exploration of the issue evolving rules for geographic information systems; Impact of the emergence of geographic information and intelligent transportation systems on the way people deal with transportation.

Background: Understanding traffic is an important challenge in different scientific fields. While there are many approaches to constructing traffic models, most of them rely on origin-destination data and have difficulties when phenomena should be investigated that have an effect on the origin-destination matrix.Methods: A macroscopic traffic model is introduced that is novel in the sense that no origin-destination data are required as an input. This information is generated from mobility behavior data using a hybrid approach between agent-based modeling to find the origin and destination points of each vehicle and network techniques to find efficiently the routes most likely used to connect those points. The simulated road utilization and resulting congestion is compared to traffic data to quantitatively evaluate the results. Traffic jam avoidance behavior is included in the model in several variants, which are then all evaluated quantitatively.Results: The described model is applied to the City of Graz, a typical European city with about 320,000 inhabitants. Calculated results correspond well with reality.Conclusions: The introduced traffic model, which uses mobility data instead of origin-destination data as input, was successfully applied and offers unique advantages compared to traditional models: Mobility behavior data are valid for different systems, while origin-destination data are very specific to the region in question and more difficult to obtain. In addition, different scenarios (increased population, more use of public transport, etc.) can be evaluated and compared quickly. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports within the issue on topics including transportation, spatial economics and traffic models.

The article offers information on the U.S.-China Workshop on Research and Education Collaboration in Transportation Infrastructure held in Washington, D.C. on January 23, 2011. The workshop, themed "Asphalt Pavement Technology in China," was organized jointly by the International Association of Chinese Infrastructure Professionals and the Research Institute of Highway of China. Topics discussed focused on the area of pavement and traffic engineering.

An introduction is presented in which the editor discusses various reports within the issue on topics including transportation, spatial economics and microstimulation.