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Due to recent advancements in connected and autonomous vehicles (CAVs), freeway traffic control (FTC) has become a trendy area of research. Combining CAVs and control measures has opened more efficient traffic flow possibilities. However, while there is extensive research on how traffic control and CAVs can enhance traffic flow performance, their safety benefits should be evaluated more comprehensively. It is challenging to distinguish their contributions to traffic flow safety. Studies on the safety of CAVs in traffic flow indicate that traffic flow safety improves with higher market penetration rates (MPR) of CAVs. However, this finding only sometimes aligns with the traffic flow performance effects of CAVs on freeways. This paper introduces a framework for assessing the safety effects of FTC strategies in mixed traffic scenarios involving human-driven vehicles and CAVs. The proposed framework is tested through a microsimulation-based case study in Istanbul, Turkey. The results show that, despite varying MPRs, the safety effects of CAVs and FTC methods do not consistently reduce the number of conflicts in the traffic flow context. [ABSTRACT FROM AUTHOR]

Highway work zones are associated with significant adverse impacts on safety. Mitigating these impacts can be achieved by implementing several countermeasures. This paper uses controlled experiments in a driving simulator to investigate the effects of physical and digital temporary traffic control countermeasures on work zone safety. These include variable message signs, dynamic speed displays, rumble strips, and lane widths. 116 participants were recruited for the experiment. A linear mixed-effects model was developed to capture the effects of these countermeasures on average travel speed and standard deviation of speeds in the advanced warning area and within the work zone itself. The results reveal that rumble strips installed within the work zone cause the strongest reduction in speeds. Narrower lanes cause smaller speed reductions. In general, the effects of temporary traffic control countermeasures on speeds were local and were not retained beyond their proximity. [ABSTRACT FROM AUTHOR]

The essential of developing an advanced driving assistance system is to learn human-like decisions to enhance driving safety. When controlling a vehicle, joining roundabouts smoothly and timely is a challenging task even for human drivers. In this paper, we propose a novel imitation learning based decision making framework to provide recommendations to join roundabouts. Our proposed approach takes observations from a monocular camera mounted on vehicle as input and use deep policy networks to provide decisions when is the best timing to enter a roundabout. The domain expert guided learning framework can not only improve the decision-making but also speed up the convergence of the deep policy networks. We evaluate the proposed framework by comparing with state-of-the-art supervised learning methods, including conventional supervised learning methods, such as SVM and kNN, and deep learning based methods. The experimental results demonstrate that the imitation learning-based decision making framework, which ourperforms supervised learning methods, can be applied in driving assistance system to facilitate better decision-making when approaching roundabouts. [ABSTRACT FROM AUTHOR]

Intelligent transportation brings huge benefits to humans' life and Industrial production in terms of vehicle control and traffic management. Now, the development of edge-cloud computing has once again promoted intelligent transportation into a new era. However, the development of intelligent transportation inevitably produces a large amount of data, which brings new challenges to data privacy protection and security. In this paper, we propose to develop an improved trajectory prediction framework based on the self-adaptive trajectory prediction model (SATP), which could significantly enhance traffic safety in transportation systems. The proposed framework is capable of guaranteeing the accurate trajectory prediction of moving target under different application scenarios. In particular, to reduce the size of original trajectory point data collected by sensors, the angle change and minimum description length (MDL) principle are first combined to remove the redundant points in raw trajectories. The obtained points can then be reduced for model using the two-step clustering method. To further enhance the prediction performance, we add the "self-transfer" to the original model to solve the problems that the state of original SATP model may be discontinuous. Furthermore, we propose to develop a trajectory complementation method based on Bezier curve to improve the prediction accuracy. Finally, by comparing the two-step clustering method with the commonly-used SinglePass and density-based clustering method (DBCM) algorithms, the proposed two-step clustering policy greatly reduce the time cost of clustering. At the same time, by comparing the improved SATP model with the original model, the results show that the improved SATP method can greatly improve the speed of prediction model. [ABSTRACT FROM AUTHOR]

A system to automatically recognize vehicle license plates is a growing need to improve safety and traffic control, specifically in major urban centers. However, the license plate recognition task is generally computationally intensive, where the entire input image frame is scanned, the found plates are segmented, and character recognition is then performed for each segmented character. This paper presents a methodology for engineering a system to detect and recognize Brazilian license plates using convolutional neural networks (CNN) that is suitable for embedded systems. The resulting system detects license plates in the captured image using Tiny YOLOv3 architecture and identifies its characters using a second convolutional network trained on synthetic images and fine-tuned with real license plate images. The proposed architecture has demonstrated to be robust to angle, lightning, and noise variations while requiring a single forward pass for each network, therefore allowing faster processing compared to other deep learning approaches. Our methodology was validated using real license plate images under different environmental conditions reached a detection rate of 99.37% and an overall recognition rate of 98.43% while showing an average time of 2.70 s to process 1024 × 768 images with a single license plate in a Raspberry Pi3 (ARM Cortex-A53 CPU). To improve the recognition accuracy, an ensemble of CNN models was tested instead of a single CNN model, which resulted in an increase in the average processing time to 4.88 s for each image while increasing the recognition rate to 99.53%. Finally, we discuss the impact of using an ensemble of CNNs considering the accuracy-performance trade-off when engineering embedded systems for license plate recognition. [ABSTRACT FROM AUTHOR]

Electronic Toll Collection (ETC) systems are based on tags, on-board units associated to personal bank accounts, used for paying tolls electronically. Despite the benefits associated to their use, acknowledged by public authorities among other stakeholders, these systems are relentlessly penetrating as a means for paying the use of roads worldwide. However, governments and infrastructure operators still have a great potential to increase the effectiveness and expediency of these mechanisms. Previous literature in this field has focused on analyzing users' perceptions and willingness to pay to use toll roads. However, there is still room for addressing additional aspects such as drivers' adoption of ETC systems in these road networks allowing the payment of tolls electronically. The aim of this paper is to identify the explanatory factors influencing the adoption of ETC technologies by toll road drivers. To that end, we exploit a nationwide survey conducted to road users in interurban toll roads in Spain, and develop a multilevel logit framework to explore users' adoption and position towards the use of electronic tolling. The research concludes that drivers' tag ownership is mainly related to trip-related attributes, while personal socioeconomic characteristics play a minor role. Then, it is not possible to establish specific socioeconomic user market segments to direct policy efforts aimed at increasing the penetration of ETC. Furthermore, according to the results, delivering tag devices for free would be an effective policy measure to encourage individuals adopting electronic tolling and making additional use of toll roads, due to the benefits provided by ETC systems. [ABSTRACT FROM AUTHOR]

To form ergonomic driving conditions in the "driver–vehicle–road environment" system, it is proposed to use a mathematical model of automatic control theory, in which special features of traffic control are determined by the transition process described by transfer functions of the vehicle and the driver. The proposed model makes it possible to simulate vehicle speed control processes in accordance with road conditions whose impact on the driver is estimated by the complex characteristic: maximum entropy of the traffic environment. [ABSTRACT FROM AUTHOR]

This study’s aim was to enhance the maneuverability safety in the coordination of active rear steering and differential braking control for untripped rollover prevention, which performs a panic lane change maneuver to bypass the obstacle encountered in the path. In avoiding rollover accidents, there are several guidance preventions, such as to secure the vehicle from the intention of the driver and to position the vehicle in the actual lane. A crosswind effect is also found to be a crucial factor since this may cause other accidents. Therefore, there is a need to monitor the driver’s actual path and maintaining the stability of the vehicle along the desired path in order to avoid rollover accidents. We extended the analysis of Yakub and Mori (2015) [1], by suggesting an explicit model of predictive control, which includes an active rear steering and braking control for each wheel. Our main focus was on the general trade-off between rollover prevention and path tracking. The effectiveness of the explicit control model invented for this study was measured and validated by the simulation results for a heavy vehicle proposed in this research. [ABSTRACT FROM AUTHOR]

Explicit traffic control measures are absent in uncontrolled intersections which make them susceptible to frequent conflicts and resulting collisions between vehicles. In developing countries like India, drivers at such intersections do not yield to higher priority movements which cause more crashes between vehicles. The objective of this study is to analyze and model the gap acceptance behavior of minor street drivers at uncontrolled T-intersections considering their aggressive nature. Three intersections in the northeast region of India have been selected as the case study area. Preliminary analysis of the data revealed that drivers behave aggressively, not because they have to wait for a long time at the stop line, but because of their lack of respect for traffic rules. Binary logit models are developed for minor road right turning vehicles which show that gap acceptance behavior is influenced by gap duration, clearing time and aggressive nature of drivers. The equations obtained were used to estimate the critical gaps for aggressive and non-aggressive drivers. Critical gaps are also calculated using an existing method called clearing behavior approach. It is also shown that the estimation of critical gap is more realistic if clearing time and aggressive behavior of drivers are considered. [ABSTRACT FROM AUTHOR]

Some studies have estimated fatality and injury rates for bus occupants, but data was aggregated at the country level and made no distinction between bus types. Also, injured pedestrians and cyclists, as a result of bus travel, were overlooked. We compared injury rates for car and city bus occupants on specific urban major roads, as well as the cyclist and pedestrian injuries associated with car and bus travel. We selected ten bus routes along major urban arterials (in Montreal, Canada). Passenger-kilometers traveled were estimated from vehicle counts at intersections (2002-2010) and from bus passenger counts (2008). Police accident reports (2001-2010) provided injury data for all modes. Injury rates associated with car and bus travel were calculated for vehicle occupants, pedestrians, and cyclists. Injury rate ratios were also computed. The safety benefits of bus travel, defined as the number of vehicle occupant, cyclist, and pedestrian injuries saved, were estimated for each route. Overall, for all ten routes, the ratio between car and bus occupant injury rates is 3.7 (95% CI [3.4, 4.0]). The rates of pedestrian and cyclist injuries per hundred million passenger-kilometers are also significantly greater for car travel than that for bus travel: 4.1 (95% CI [3.5, 4.9]) times greater for pedestrian injuries; 5.3 (95% CI [3.8, 7.6]) times greater for cyclist injuries. Similar results were observed for fatally and severely injured vehicle occupants, cyclists, and pedestrians. At the route level, the safety benefits of bus travel increase with the difference in injury rate associated with car and bus travel but also with the amount of passenger-kilometers by bus. Results show that city bus is a safer mode than car, for vehicle occupants but also for cyclists and pedestrians traveling along these bus routes. The safety benefits of bus travel greatly vary across urban routes; this spatial variation is most likely linked to environmental factors. Understanding the safety benefits of public transit for specific transport routes is likely to provide valuable information for mobilizing city and transportation planners. [ABSTRACT FROM AUTHOR]

Purpose In order to explore the effect of curb parking on dynamic traffic and formulate some reasonable and effective traffic management measures, the effects on capacity and traffic safety are studied. Methods Four road segments with curb parking were selected as the investigation location. Several traffic characteristics and parameters were then investigated and counted, including traffic flow volume, speed, headway and traffic conflict. Based on a reduction of lane effective width and the Gap Acceptance Theory, two effect models describing curb parking and road capacity were constructed. Considering the factors involved in motor vehicle conflicts (such as non-motor vehicle lane distribution and stopping sight distance), the effects of curb parking on both motor vehicle and non-motor vehicle traffic safety was analyzed, as well as pedestrian crossing safety. This case study analyzes both the capacity and traffic safety of all four investigation segments. Results Results show that the lane effective width of road segment with curb parking significantly influences the road capacity and impacts the traffic flow volumes of the parking lane and its adjacent lane. Conclusions Curb parking significantly effects traffic operation safety; however, it can be improved by implementing traffic safety management measures. [ABSTRACT FROM AUTHOR]

In India, traffic flow on roads is highly mixed in nature with wide variations in the static and dynamic characteristics of vehicles. At unsignalized intersections, vehicles generally do not follow lane discipline and ignore the rules of priority. Drivers generally become more aggressive and tend to cross the uncontrolled intersections without considering the conflicting traffic. All these conditions cause a very complex traffic situation at unsignalized intersections which have a great impact on the capacity and performance of traffic intersections. A new method called additive conflict flow (ACF) method is suitable to determine the capacity of unsignalized intersections in non-lane-based mixed traffic conditions as prevailing in India. Occupation time is the key parameter for ACF method, which is defined as the time spent by a vehicle in the conflict area at the intersection. Data for this study were collected at two three-legged unsignalized intersections (one is uncontrolled and other one is semicontrolled) in Mangalore city, India using video-graphic technique during peak periods on three consecutive week days. The occupation time of vehicles at these intersections were studied and compared. The data on conflicting traffic volume and occupation time by each subject vehicle at the conflict area were extracted from the videos using image processing software. The subject vehicles were divided into three categories: two wheelers, cars, and auto-rickshaws. Mathematical relationships were developed to relate the occupation time of different categories of vehicles with the conflicting flow of vehicles for various movements at both the intersections. It was found that occupation time increases with the increasing conflicting traffic and observed to be higher at the uncontrolled intersection compared to the semicontrolled intersection. The segregated turning movements and the presence of mini roundabout at the semicontrolled intersection reduces the conflicts of vehicular movements, which ultimately reduces the occupation time. The proposed methodology will be useful to determine the occupation time for various movements at unsignalized intersections. The models developed in the study can be used by practitioners and traffic engineers to estimate the capacity of unsignalized intersections in non-lane-based discipline and mixed traffic conditions. [ABSTRACT FROM AUTHOR]

Accident prediction is one of the most critical aspects of road safety, whereby an accident can be predicted before it actually occurs and precautionary measures taken to avoid it. For this purpose, accident prediction models are popular in road safety analysis. Artificial intelligence (AI) is used in many real world applications, especially where outcomes and data are not same all the time and are influenced by occurrence of random changes. This paper presents a study on the existing approaches for the detection of unsafe driving patterns of a vehicle used to predict accidents. The literature covered in this paper is from the past 10 years, from 2004 to 2014. AI techniques are surveyed for the detection of unsafe driving style and crash prediction. A number of statistical methods which are used to predict the accidents by using different vehicle and driving features are also covered in this paper. The approaches studied in this paper are compared in terms of datasets and prediction performance. We also provide a list of datasets and simulators available for the scientific community to conduct research in the subject domain. The paper also identifies some of the critical open questions that need to be addressed for road safety using AI techniques. [ABSTRACT FROM AUTHOR]

Unidirectional two-lane freeway is a typical and the simplest form of freeway. The traffic flow characteristics including safety condition on two-lane freeway is of great significance in planning, design, and management of a freeway. Many previous traffic flow models are able to figure out flow characteristics such as speed, density, delay, and so forth. These models, however, have great difficulty in reflecting safety condition of vehicles. Besides, for the cellular automation, one of the most widely used microscopic traffic simulation models, its discreteness in both time and space can possibly cause inaccuracy or big errors in simulation results. In this paper, a micro-simulation model of two-lane freeway vehicles is proposed to evaluate characteristics of traffic flow, including safety condition. The model is also discrete in time but continuous in space, and it divides drivers into several groups on the basis of their preferences for overtaking, which makes the simulation more aligned with real situations. Partial test is conducted in this study and results of delay, speed, volume, and density indicate the preliminary validity of our model, based on which the proposed safety coefficient evaluates safety condition under different flow levels. It is found that the results of this evaluation coincide with daily experience of drivers, providing ground for effectiveness of the safety coefficient. [ABSTRACT FROM AUTHOR]

Road traffic is known to have its own complex dynamics. One implication of complexity is that road traffic collisions have become an unwelcome but unavoidable part of human life. One of the major causes of collisions is the human factor. While car manufacturers have been focusing on developing feasible solutions for autonomous and semi-autonomous vehicles to replace or assist human drivers, the proposed solutions have been designed only for individual vehicles. The road traffic, however, is an interaction-oriented system including complex flows. Such a system requires a complex systems approach to solving this problem as it involves considering not only pedestrians, road environment, but also road traffic which can include multiple vehicles. Recent research has demonstrated that large-scale autonomous vehicular traffic can be better modeled using a collective approach as proposed in the form of vehicular cyber-physical systems (VCPS) such as given by Li et al. (IEEE Trans Parallel Distrib Syst 23(9):1775-1789, ) or Work et al. (Automotive cyber physical systems in the context of human mobility. In: National workshop on high-confidence automotive cyber-physical systems, Troy, MI, ). To the best of our knowledge, there is currently no comprehensive review of collision avoidance in the VCPS. In this paper, we present a comprehensive literature review of VCPS from the collision-avoidance perspective. The review includes a careful selection of articles from highly cited sources presented in the form of taxonomy. We also highlight open research problems in this domain. [ABSTRACT FROM AUTHOR]

Today's high-end vehicles are technologically more sophisticated and smarter than the 'old machines with engine and wheels'. These vehicles are anticipated to provide consumers with safe, reliable, and infotainment-rich driving experience through intelligent transportation system, realized through a technology referred to as vehicular ad hoc network (VANET). VANET offers a plethora of applications to the consumers ranging from safety to infotainment. Among other messages defined by the dedicated short range communication standard, cooperative awareness messages (CAMs) are of paramount importance for the VANET applications. In VANET, vehicles share their frequent mobility information in the form of CAMs with neighbors for cooperative awareness, traffic view construction, maneuver, and cruise control. In this work we target the CAM-based traffic information dissemination. VANET applications construct short-range local and long-range extend traffic views with the information contained in scheduled CAMs (also known as beacons). To construct aforementioned traffic views, naïve approach is multi-hop communication; however, historically multi-hop communication does not scale efficiently in dynamic VANET due to computational and communication overhead. Therefore another alternative approach is essential to address the problems of the multi-hop communication in highly ephemeral VANET and to achieve maximum degree of the information dissemination in VANET. To fill the gap, in this paper we propose a geocast-based abstract piggybacking mechanism for traffic information dissemination in VANET through single-hop CAMs. In the proposed scheme, vehicles compress their local traffic view constructed through single-hop CAMs. The compressed local traffic view is referred to as traffic data unit (TDU). Every vehicle broadcasts its own TDU along with a number of TDUs received from other vehicles in the next scheduled CAM, in order to construct a long-range extended traffic view, also known as compressed data word (CDW). In other words, CDW is encapsulated into normal CAM in order to share it with the neighbors in the vicinity. The receivers of CDW use the received TDUs to construct the desired length of the long-range extended traffic view. The proposed scheme leverages only single-hop beacons data to construct both local and extended traffic views. Our simulation results show that the extended traffic view up to 1 km can be constructed with only single-hop beacons at the expense of 10 % of extra information with the regular CAM. The results also show that the effect of the extra overhead is not phenomenal from overhead standpoint. The proposed virtual multi-hop communication paradigm with single-hop CAM will reduce the overall communication thereby saving the bandwidth for other important safety related communications. [ABSTRACT FROM AUTHOR]

In recent years, the topic of car-following has experimented an increased importance in traffic engineering and safety research. This has become a very interesting topic because of the development of driverless cars (Google driverless cars, ). Driving models which describe the interaction between adjacent vehicles in the same lane have a big interest in simulation modeling, such as the Quick-Thinking-Driver model. A non-linear version of it can be given using the logistic map, and then chaos appears. We show that an infinite-dimensional version of the linear model presents a chaotic behaviour using the same approach as for studying chaos of death models of cell growth. [ABSTRACT FROM AUTHOR]

Maritime traffic is a distributed, self-organising system. When resources are abundant, this has proven to be successful. However, near ports navigation space becomes limited, decreasing manoeuvring space, which has a negative effect on efficiency and safety. This article discusses how arrival management, realising efficiency and safety, can be modelled in the maritime domain using a functional approach. This management system needs to fit the requirements set by the maritime domain: large mass, small safety margins, and complex ship control. The main focus will be on resilience to ensure safety at all times and on control to realise efficiency. [ABSTRACT FROM AUTHOR]

Traffic management is not formally organised in the maritime domain. Ships are autonomous and find their own way. Traffic is organised through rules, regulations, and 'good seamanship'; it is a distributed system. In areas of high traffic-density support is proved by vessel traffic service (VTS) to promote traffic safety and fluency. VTS does not take control. This organisational structure has proven itself in situations with sufficient resources. When resources become insufficient (e.g. not enough sailing space), the traffic needs an organising mechanism. In this article, the authors argue that the most promising way to do this is by organising centralised planning coordination, whilst leaving maritime traffic a distributed system with no additional central control. [ABSTRACT FROM AUTHOR]

This paper demonstrates the results of field tests for assessing a cooperative intersection signal violation warning system (CISVWS), which consists of (a) hardware, including an in-vehicle warning device, roadside antenna, and traffic signal controller, and (b) software to operate and test the cooperative system through vehicle to infrastructure (V2I) communication systems. Field tests were performed under real traffic situations in order to test the system in terms of the initiation time of the signal violation warning from the signal controller, the activation and duration of on board equipment (OBE), and the warning delay based on the relationships between distance variables, including the safe stopping distance, and the location of road side equipment (RSE). Findings from the field test at the real-world signalized intersection sites indicated that the system would be capable of reducing red light violations and intersection collisions through use of the in-vehicle warning device at signalized intersections. [ABSTRACT FROM AUTHOR]

This paper aims to discuss a number of questions that are highly important for the ex ante evaluation of the safety impacts of transport policy options, from the perspective of ethical theory: (1) Is it morally OK to express prevention on acceptance of fatalities or risks in monetary terms? (2) How useful is the concept of the value of a statistical life (VOSL) for ex ante evaluations of transport policy options? (3) What are the pros and cons of pricing protection of lives or prevention of risks in ex ante evaluations? (4) Which methods are available for expressing (protection of) human lives in monetary terms, and what are the main related methodological discussions? (5) Are all safety-related costs generally included in ex ante evaluations of the safety impacts of transport policy options, and if not: what is the relevance of excluded costs categories from an ethical perspective? (6) How important is the distribution of safety effects from an ethical perspective? The answer to the first question highly depends on the ethical theory that is used. With respect to question 2 we think that the VOSL is a useful concept, but that its application is not straightforward, for several reasons. Thirdly we think that probably pricing safety improves the quality of decision making, but to the best of our knowledge there is no research to underpin this expectation. The answer to question 4 is that several methods exist to estimate the value of a statistical life (VOSL), willingness-to-pay (WTP) methods being the most common category of methods. However, several methodological issues arise that make estimates of VOSL less straightforward. With respect to question 5 we conclude that behaviour-related avoidance costs are often overlooked and that these costs are relevant from an ethical perspective because the freedom to move and the freedom to participate in activities are challenged. Finally the answer to question 6 is that from an ethical perspective, in terms of the evaluation of policy measures, it might matter which groups of the population are the victims of the transport system, or are at risk. Egalitarian theories as well as sufficientarianism are useful theories to discuss distribution effects. Different theories conclude differently. [ABSTRACT FROM AUTHOR]

Modern weather prediction models use relatively high grid resolutions as well as sophisticated parametrization schemes for microphysical and other subgrid-scale atmospheric processes. Nonetheless, with these models it remains a difficult task to perform successful numerical fog forecasts since many factors controlling a particular fog event are not yet sufficiently simulated. Here we describe our efforts to create a mechanism that produces successful predictions of fog in the territory located on the north coast of the Arabian Peninsula. Our approach consists in the coupling of the one-dimensional PAFOG fog model with the three-dimensional WRF 3.0 (Weather Research and Forecast) modelling system. The proposed method allows us to construct an efficient operative road traffic warning system for the occurrence of fog in the investigated region. In total 84 historical situations were studied during the period 2008-2009. Moreover, results of operative day-by-day fog forecasting during January and February 2010 are presented. For the investigated arid and hot climate region the land-sea breeze circulation seems to be the major factor affecting the diurnal variations of the meteorological conditions, frequently resulting in the formation of fog. [ABSTRACT FROM AUTHOR]

Zero-inflated count models are increasingly employed in many fields in case of “zero-inflation”. In modeling road traffic crashes, it has also shown to be useful in obtaining a better model-fitting when zero crash counts are over-presented. However, the general specification of zero-inflated model can not account for the multilevel data structure in crash data, which may be an important source of over-dispersion. This paper examines zero-inflated Poisson regression with site-specific random effects (REZIP) with comparison to random effect Poisson model and standard zero-inflated poison model. A practical and flexible procedure, using Bayesian inference with Markov Chain Monte Carlo algorithm and cross-validation predictive density techniques, is applied for model calibration and suitability assessment. Using crash data in Singapore (1998–2005), the illustrative results demonstrate that the REZIP model may significantly improve the model-fitting and predictive performance of crash prediction models. This improvement can contribute to traffic safety management and engineering practices such as countermeasure design and safety evaluation of traffic treatments. [ABSTRACT FROM AUTHOR]

The Netherlands is a densely populated country. As a result environmental issues related to road traffic are taken very serious. This paper discusses the mechanistic design of porous asphalt surface mixtures, PA. The environmental advantages of PA are that it dramatically reduces traffic noise. A disadvantage of PA is that the presence of pores reduces the strength of the mixture which is reflected in the materials vulnerability to ravelling. And, to make matters worse, the open structure makes the material vulnerable to aging which further enhances the ravelling vulnerability. Ravelling has a negative effect on noise emission, implying that the main advantage of PA is gradually lost as the development of ravelling damage progresses throughout the service life of PA. Furthermore ravelling of PA is the main reason for PA maintenance. In this paper a mechanistic mixture design approach for PA surfacings and open graded thin surfacings is discussed. The procedure is based on meso scale material mechanics in which the in-mixture response to wheel loadings is simulated and used for further durability determination. The development of the theory summarised and the paper comes to a conclusion by validation of the procedure on the basis of full-scale ravelling tests. It is concluded that the mechanistic design of silent porous surfacing layers is feasible today and that this may well contribute to the introduction of durable and silent road surfacings on a wider scale. [ABSTRACT FROM AUTHOR]

This study examined how objective measures of the local road environment related to safety were associated with change in physical activity (including active transport) among youth. Few longitudinal studies have examined the impact of the road environment on physical activity among children/adolescents in their neighborhoods. Participants were children aged 8–9 years ( n = 170) and adolescents aged 13–15 years ( n = 276) in 2004. Data were collected in 2004 and 2006 during follow-up of participants recruited initially in 2001 from 19 primary schools in Melbourne, Australia. Walking/cycling to local destinations was parent-reported for children and self-reported by adolescents. Moderate-to-vigorous physical activity (MVPA) during nonschool hours was recorded using accelerometers. Road environment features in each participant’s neighborhood (area within 800 m radius of their home) were measured objectively using a Geographical Information System. Linear regression analyses examined associations between road features and changes in active transport (AT) and MVPA over 2 years. Children’s AT increased but MVPA levels decreased in both age groups; on average, younger girls recorded the greatest declines. The number of traffic/pedestrian lights was associated with ΔAT among younger girls (B=0.45, p=0.004). The total length of walking tracks (in meters) was associated with ∆AT among younger girls ( B = 0.0016, p = 0.015) and adolescent girls ( B = 0.0016, p = 0.002). For adolescent boys, intersection density was associated with ∆AT ( B = 0.03, p = 0.030). Slow points were associated with ∆MVPA among younger boys before school ( B = 1.55, p = 0.021), while speed humps were associated with ∆MVPA among adolescent boys after school ( B = 0.23, p = 0.015). There were many associations for adolescent girls: for example, the total length of local roads ( B = 0.49, p = 0.005), intersection density ( B = 0.05, p = 0.036), and number of speed humps ( B = 0.33, p = 0.020) were associated with ∆MVPA during nonschool hours. Safety-related aspects of the built environment are conducive to physical activity among youth and may help stem age-related declines in physical activity. Passive road safety interventions may promote AT and physical activity among less active girls, in particular. [ABSTRACT FROM AUTHOR]

The design and implementation of new technologies dedicated to driver support and information management systems is the crucial transformation that has taken place in the field of automotive environment. While the development of these new systems has found a variety of sound and effective solutions, a number of fundamental questions and issues remain to be tackled and solved with respect to the consequences that such new technologies have on driver activity. In particular, a major concern is on “behavioural adaptation” and on the possible impact that this may play on the driving performance and ultimately on overall road safety. Within the European Project Adaptive Integrated Driver-vehicle InterfacE (AIDE), a specific research activity is dedicated (1) to the identification of crucial behavioural adaptation aspects associated with the use of new driver support systems and (2) of the specification of most relevant parameters that can be implemented in models for supporting design and safety assessment processes. This paper describes the results of a set of experiments carried out on a number of specific driving support systems and their results in terms of observed behavioural adaptation. These results will be imbedded in modelling architecture that enables to predict driver-vehicle-environment interactions in different dynamic conditions. Such model is also described in some details for what concerns the model characteristics and main parameters. [ABSTRACT FROM AUTHOR]

Traffic research shares a fundamental dilemma with other areas of empirical research in which humans are potentially put at risk. Research is justified because it can improve safety in the long run. Nevertheless, people can be harmed in the research situation. Hence, we need to balance short-term risks against long-term safety improvements, much as in other areas of research with human subjects. In this paper we focus on ethical issues that arise when human beings are directly affected in the performance of research by examining how the ethical requirements in biomedical research can inform traffic research. After introducing the basic ethical requirements on biomedical research, each of the major requirements is discussed in relation to traffic research. We identify the main areas where biomedical research and traffic research differ, and where the ethical requirements from the former cannot easily be transferred to the latter. Finally, we argue that there is a need for systematic studies of the ethics of traffic research and point to some of the issues that need to be addressed. [ABSTRACT FROM AUTHOR]

A recent investigation revealed that there is a substantiated need for the development of a micro-simulation system designed for traffic safety assessment. This paper describes the development of a road traffic simulation system, which uses a ‘nanoscopic model’ of driver behaviour and an integrated analysis-evaluation system designed for traffic safety assessment. The primary focus is on estimating the effects of an advanced driver assistance system thereby reducing traffic accidents. The effectiveness and validity of the present system are demonstrated through comparison with measured traffic data. This paper also proposes algorithms embedded in a ‘driver-agent’, for recognising driver’s intentions regarding choosing steering-control modes, lateral control tasks, and the driving mood. This is because the driver assistance systems need to recognise the driver’s intention when choosing steering-control. The results of a simulation study, using the data drawn from actual driving, show that the systems would achieve a high recognition capability. As an example of how driving mood recognition applies to driver assistance systems, an advanced steering system and the adaptability to the driver’s mood, have also been presented. [ABSTRACT FROM AUTHOR]

As one component of traffic incident management systems, freeway service patrols (FSP) facilitate quick removal of incidents through faster response and reduced clearance time. This paper is to investigate how to allocate tow trucks among patrol beats to maximize the effectiveness of the FSP services. A min–max bi-level programming model is proposed to determine an optimal fleet allocation that minimizes the maximal system travel time that incidents may incur. A heuristic iterative solution algorithm is proposed to solve the model. Both the model and the algorithm are demonstrated and validated through a numerical example. [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]

Technology and human behavior can influence the effectiveness of safety policies. In the field of traffic safety, rational-choice theorists postulate that auto mobile safety devices induce increased driver risk taking. Such behavioral responses could partly or totally nullify the lifesaving potential of governmental safety rules for new cars, such as the crashworthiness standards adopted by the United States in the late 1960s and early 1970s. This study explores the behavioral-response hypothesis in the context of a car-vintage model of U.S. car occupant death rates. Results from the model imply that U.S. standards have reduced the occupant death rate by roughly 30 percent, a finding consistent with minimal driver response to safety devices. The study provides support for the technological approach to safety policy and suggests that policymakers might consider adopting additional crashworthiness regulations, such as some form of passive-restraint program. [ABSTRACT FROM AUTHOR]