8,448 research outputs found

    Simulating the Impact of Traffic Calming Strategies

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    This study assessed the impact of traffic calming measures to the speed, travel times and capacity of residential roadways. The study focused on two types of speed tables, speed humps and a raised crosswalk. A moving test vehicle equipped with GPS receivers that allowed calculation of speeds and determination of speed profiles at 1s intervals were used. Multi-regime model was used to provide the best fit using steady state equations; hence the corresponding speed-flow relationships were established for different calming scenarios. It was found that capacities of residential roadway segments due to presence of calming features ranged from 640 to 730 vph. However, the capacity varied with the spacing of the calming features in which spacing speed tables at 1050 ft apart caused a 23% reduction in capacity while 350-ft spacing reduced capacity by 32%. Analysis showed a linear decrease of capacity of approximately 20 vphpl, 37 vphpl and 34 vphpl when 17 ft wide speed tables were spaced at 350 ft, 700 ft, and 1050 ft apart respectively. For speed hump calming features, spacing humps at 350 ft reduced capacity by about 33% while a 700 ft spacing reduced capacity by 30%. The study concludes that speed tables are slightly better than speed humps in terms of preserving the roadway capacity. Also, traffic calming measures significantly reduce the speeds of vehicles, and it is best to keep spacing of 630 ft or less to achieve desirable crossing speeds of less or equal to 15 mph especially in a street with schools nearby. A microscopic simulation model was developed to replicate the driving behavior of traffic on urban road diets roads to analyze the influence of bus stops on traffic flow and safety. The impacts of safety were assessed using surrogate measures of safety (SSAM). The study found that presence of a bus stops for 10, 20 and 30 s dwell times have almost 9.5%, 12%, and 20% effect on traffic speed reductions when 300 veh/hr flow is considered. A comparison of reduction in speed of traffic on an 11 ft wide road lane of a road diet due to curbside stops and bus bays for a mean of 30s with a standard deviation of 5s dwell time case was conducted. Results showed that a bus stop bay with the stated bus dwell time causes an approximate 8% speed reduction to traffic at a flow level of about 1400 vph. Analysis of the trajectories from bust stop locations showed that at 0, 25, 50, 75, 100, 125, 150, and 175 feet from the intersection the number of conflicts is affected by the presence and location of a curbside stop on a segment with a road diet

    Tradeoffs among Free-flow Speed, Capacity, Cost, and Environmental Footprint in Highway Design

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    This paper investigates differentiated design standards as a source of capacity additions that are more affordable and have smaller aesthetic and environmental impacts than expressways. We consider several tradeoffs, including narrow versus wide lanes and shoulders on an expressway of a given total width, and high-speed expressway versus lower-speed arterial. We quantify the situations in which off-peak traffic is sufficiently great to make it worthwhile to spend more on construction, or to give up some capacity, in order to provide very high off-peak speeds even if peak speeds are limited by congestion. We also consider the implications of differing accident rates. The results support expanding the range of highway designs that are considered when adding capacity to ameliorate urban road congestion.Highway design; Capacity; Free-flow speed; Parkway

    Modeling Link-level Road Traffic Resilience to Extreme Weather Events Using Crowdsourced Data

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    Climate changes lead to more frequent and intense weather events, posing escalating risks to road traffic. Crowdsourced data offer new opportunities to monitor and investigate changes in road traffic flow during extreme weather. This study utilizes diverse crowdsourced data from mobile devices and the community-driven navigation app, Waze, to examine the impact of three weather events (i.e., floods, winter storms, and fog) on road traffic. Three metrics, speed change, event duration, and area under the curve (AUC), are employed to assess link-level traffic change and recovery. In addition, a user's perceived severity is computed to evaluate link-level weather impact based on crowdsourced reports. This study evaluates a range of new data sources, and provides insights into the resilience of road traffic to extreme weather, which are crucial for disaster preparedness, response, and recovery in road transportation systems

    Congestion costing critique

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    The Urban Mobility Report (UMR) is a widely-cited study that quantifies and monetises (measures in monetary units) traffic congestion costs in U.S. metropolitan regions. This report critically examines the UMR’s assumptions and methods. The UMR reflects an older planning paradigm which assumes that “transportation” means automobile travel, and so evaluates transport system performance based primarily on automobile travel speeds; it ignores other modes, other planning objectives and other impacts. The UMR methodology overestimates congestion costs and roadway expansion benefits by using higher baseline speeds and travel time unit cost values than most experts recommend, by ignoring induced travel impacts, and using an inaccurate speed-emission curve. Its estimates represent upper-bound values and are two- to four times higher than result from more realistic assumptions. The UMR claims that congestion costs are “massive,” although they increase total travel time and fuel consumption by 2% at most. It exaggerates future congestion problems by ignoring evidence of peaking vehicle travel and changing travel demands. The UMR ignores basic research principles: it fails to identify best current practices, explain assumptions, document sources, incorporate peer review, or respond to criticisms

    Identification of infrastructure related risk factors, Deliverable 5.1 of the H2020 project SafetyCube

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    The present Deliverable (D5.1) describes the identification and evaluation of infrastructure related risk factors. It outlines the results of Task 5.1 of WP5 of SafetyCube, which aimed to identify and evaluate infrastructure related risk factors and related road safety problems by (i) presenting a taxonomy of infrastructure related risks, (ii) identifying “hot topics” of concern for relevant stakeholders and (iii) evaluating the relative importance for road safety outcomes (crash risk, crash frequency and severity etc.) within the scientific literature for each identified risk factor. To help achieve this, Task 5.1 has initially exploited current knowledge (e.g. existing studies) and, where possible, existing accident data (macroscopic and in-depth) in order to identify and rank risk factors related to the road infrastructure. This information will help further on in WP5 to identify countermeasures for addressing these risk factors and finally to undertake an assessment of the effects of these countermeasures. In order to develop a comprehensive taxonomy of road infrastructure-related risks, an overview of infrastructure safety across Europe was undertaken to identify the main types of road infrastructure-related risks, using key resources and publications such as the European Road Safety Observatory (ERSO), The Handbook of Road Safety Measures (Elvik et al., 2009), the iRAP toolkit and the SWOV factsheets, to name a few. The taxonomy developed contained 59 specific risk factors within 16 general risk factors, all within 10 infrastructure elements. In addition to this, stakeholder consultations in the form of a series of workshops were undertaken to prioritise risk factors (‘hot topics’) based on the feedback from the stakeholders on which risk factors they considered to be the most important or most relevant in terms of road infrastructure safety. The stakeholders who attended the workshops had a wide range of backgrounds (e.g. government, industry, research, relevant consumer organisations etc.) and a wide range of interests and knowledge. The identified ‘hot topics’ were ranked in terms of importance (i.e. which would have the greatest effect on road safety). SafetyCube analysis will put the greatest emphasis on these topics (e.g. pedestrian/cyclist safety, crossings, visibility, removing obstacles). To evaluate the scientific literature, a methodology was developed in Work Package 3 of the SafetyCube project. WP5 has applied this methodology to road infrastructure risk factors. This uniformed approach facilitated systematic searching of the scientific literature and consistent evaluation of the evidence for each risk factor. The method included a literature search strategy, a ‘coding template’ to record key data and metadata from individual studies, and guidelines for summarising the findings (Martensen et al, 2016b). The main databases used in the WP5 literature search were Scopus and TRID, with some risk factors utilising additional database searches (e.g. Google Scholar, Science Direct). Studies using crash data were considered highest priority. Where a high number of studies were found, further selection criteria were applied to ensure the best quality studies were included in the analysis (e.g. key meta-analyses, recent studies, country origin, importance). Once the most relevant studies were identified for a risk factor, each study was coded within a template developed in WP3. Information coded for each study included road system element, basic study information, road user group information, study design, measures of exposure, measures of outcomes and types of effects. The information in the coded templates will be included in the relational database developed to serve as the main source (‘back end’) of the Decision Support System (DSS) being developed for SafetyCube. Each risk factor was assigned a secondary coding partner who would carry out the control procedure and would discuss with the primary coding partner any coding issues they had found. Once all studies were coded for a risk factor, a synopsis was created, synthesising the coded studies and outlining the main findings in the form of meta-analyses (where possible) or another type of comprehensive synthesis (e.g. vote-count analysis). Each synopsis consists of three sections: a 2 page summary (including abstract, overview of effects and analysis methods); a scientific overview (short literature synthesis, overview of studies, analysis methods and analysis of the effects) and finally supporting documents (e.g. details of literature search and comparison of available studies in detail, if relevant). To enrich the background information in the synopses, in-depth accident investigation data from a number of sources across Europe (i.e. GIDAS, CARE/CADaS) was sourced. Not all risk factors could be enhanced with this data, but where it was possible, the aim was to provide further information on the type of crash scenarios typically found in collisions where specific infrastructure-related risk factors are present. If present, this data was included in the synopsis for the specific risk factor. After undertaking the literature search and coding of the studies, it was found that for some risk factors, not enough detailed studies could be found to allow a synopsis to be written. Therefore, the revised number of specific risk factors that did have a synopsis written was 37, within 7 infrastructure elements. Nevertheless, the coded studies on the remaining risk factors will be included in the database to be accessible by the interested DSS users. At the start of each synopsis, the risk factor is assigned a colour code, which indicates how important this risk factor is in terms of the amount of evidence demonstrating its impact on road safety in terms of increasing crash risk or severity. The code can either be Red (very clear increased risk), Yellow (probably risky), Grey (unclear results) or Green (probably not risky). In total, eight risk factors were given a Red code (e.g. traffic volume, traffic composition, road surface deficiencies, shoulder deficiencies, workzone length, low curve radius), twenty were given a Yellow code (e.g. secondary crashes, risks associated with road type, narrow lane or median, roadside deficiencies, type of junction, design and visibility at junctions) seven were given a Grey code (e.g. congestion, frost and snow, densely spaced junctions etc.). The specific risk factors given the red code were found to be distributed across a range of infrastructure elements, demonstrating that the greatest risk is spread across several aspects of infrastructure design and traffic control. However, four ‘hot topics’ were rated as being risky, which were ‘small work-zone length’, ‘low curve radius’, ‘absence of shoulder’ and ‘narrow shoulder’. Some limitations were identified. Firstly, because of the method used to attribute colour code, it is in theory possible for a risk factor with a Yellow colour code to have a greater overall magnitude of impact on road safety than a risk factor coded Red. This would occur if studies reported a large impact of a risk factor but without sufficient consistency to allocate a red colour code. Road safety benefits should be expected from implementing measures to mitigate Yellow as well as Red coded infrastructure risks. Secondly, findings may have been limited by both the implemented literature search strategy and the quality of the studies identified, but this was to ensure the studies included were of sufficiently high quality to inform understanding of the risk factor. Finally, due to difficulties of finding relevant studies, it was not possible to evaluate the effects on road safety of all topics listed in the taxonomy. The next task of WP5 is to begin identifying measures that will counter the identified risk factors. Priority will be placed on investigating measures aimed to mitigate the risk factors identified as Red. The priority of risk factors in the Yellow category will depend on why they were assigned to this category and whether or not they are a hot topic

    INTELLIGENTE TRANSPORT SYSTEMEN ITS EN VERKEERSVEILIGHEID

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    This report discusses Intelligent Transport Systems (ITS). This generic term is used for a broad range of information-, control- and electronic technology that can be integrated in the road infrastructure and the vehicles themselves, saving lives, time and money bymonitoring and managing traffic flows, reducing conges-tion, avoiding accidents, etc. Because this report was written in the scope of the Policy Research Centre Mobility & Public Works, track Traffic Safety, it focuses on ITS systems from the traffic safety point of view. Within the whole range of ITS systems, two categories can be distinguished: autonomous and cooperative systems. Autonomous systems are all forms of ITS which operate by itself, and do not depend on the cooperation with other vehicles or supporting infrastructure. Example applications are blind spot detection using radar, electronic stability control, dynamic traffic management using variable road signs, emergency call, etc. Cooperative systems are ITS systems based on communication and cooperation, both between vehicles as between vehicles and infrastructure. Example applications are alerting vehicles approaching a traffic jam, exchanging data regarding hazardous road conditions, extended electronic brake light, etc. In some cases, autonomous systems can evolve to autonomous cooperative systems. ISA (Intelligent Speed Adaptation) is an example of this: the dynamic aspect as well as communication with infrastructure (eg Traffic lights, Variable Message Sign (VMS)...) can provide additional road safety. This is the clear link between the two parts of this report. The many ITS applications are an indicator of the high expectations from the government, the academic world and the industry regarding the possibilities made possible by both categories of ITS systems. Therefore, the comprehensive discussion of both of them is the core of this report. The first part of the report covering the autonomous systems treats two aspects: 1. Overview of European projects related to mobility and in particular to road safety 2. Overview for guidelines for the evaluation of ITS projects. Out of the wide range of diverse (autonomous) ITS applications a selection is made; this selection is focused on E Safety Forum and PreVENT. Especially the PreVent research project is interesting because ITS-applications have led to a number of concrete demonstration vehicles that showed - in protected and unprotected surroundings- that these ITS-applications are already technically useful or could be developed into useful products. The component “guidelines for the evaluation of ITS projects” outlines that the government has to have specific evaluation tools if the government has the ambition of using ITS-applications for road safety. Two projects -guidelines for the evaluation of ITS projects- are examined; a third evaluation method is only mentioned because this description shows that a specific targeting of the government can be desirable : 1. TRACE describes the guidelines for the evaluation of ITS projects which are useful for the evaluation of specific ITS-applications. 2. FITS contains Finnish guidelines for the evaluation of ITS project; FIS is an adaptation of methods used for evaluation of transport projects. 3. The third evaluation method for the evaluation of ITS projects is developed in an ongoing European research project, eImpact. eImpact is important because, a specific consultation of stake holders shows that the social importance of some techniques is underestimated. These preliminary results show that an appropriate guiding role for the government could be important. In the second part of this document the cooperative systems are discussed in depth. These systems enable a large number of applications with an important social relevance, both on the level of the environment, mobility and traffic safety. Cooperative systems make it possible to warn drivers in time to avoid collisions (e.g. when approaching the tail of a traffic jam, or when a ghost driver is detected). Hazardous road conditions can be automatically communicated to other drivers (e.g. after the detection of black ice or an oil trail by the ESP). Navigation systems can receive detailed real-time up-dates about the current traffic situation and can take this into account when calculating their routes. When a traffic distortion occurs, traffic centers can immediately take action and can actively influence the way that the traffic will be diverted. Drivers can be notified well in advance about approaching emergency vehicles, and can be directed to yield way in a uniform manner. This is just a small selection from the large number of applications that are made possible because of cooperative ITS systems, but it is very obvious that these systems can make a significant positive contribution to traffic safety. In literature it is estimated that the decrease of accidents with injuries of fatalities will be between 20% and 50% . It is not suprising that ITS systems receive a lot of attention for the moment. On an international level, a number of standards are being established regarding this topic. The International Telecommunications Uniont (ITU), Institute for Electrical and Electronics Engineers (IEEE), International Organization for Standardization (ISO), Association of Radio Industries and Business (ARIB) and European committee for standardization (CEN) are currently defining standards that describe different aspects of ITS systems. One of the names that is mostly mentioned in literature is the ISO TC204/WG16 Communications Architecture for Land Mobile environment (CALM) standard. It describes a framework that enables transparent (both for the application and the user) continuous communication through different communication media. Besides the innumerable standardization activities, there is a great number of active research projects. On European level, the most important are the i2010 Intelligent Car Initiative, the eSafety Forum, and the COMeSafety, the CVIS, the SAFESPOT, the COOPERS and the SEVECOM project. The i2010 Intelligent Car Initiative is an European initiative with the goal to halve the number of traffic casualties by 2010. The eSafety Forum is an initiative of the European Commission, industry and other stakeholders and targets the acceleration of development and deployment of safety-related ITS systems. The COMeSafety project supports the eSafety Forum on the field of vehicle-to-vehicle and vehicle-to-infrastructure communication. In the CVIS project, attention is given to both technical and non-technical issues, with the main goal to develop the first free and open reference implementation of the CALM architecture. The SAFEST project investigates which data is important for safety applications, and with which algorithmsthis data can be extracted from vehicles and infrastructure. The COOPERS project mainly targets communication between vehicles and dedicated roadside infrastructure. Finally, the SEVECOM project researches security and privacy issues. Besides the European projects, research is also conducted in the United States of America (CICAS and VII projects) and in Japan (AHSRA, VICS, Smartway, internetITS). Besides standardization bodies and governmental organizations, also the industry has a considerable interest in ITS systems. In the scope of their ITS activities, a number of companies are united in national and international organizations. On an international level, the best known names are the Car 2 Car Communication Consortium, and Ertico. The C2C CC unites the large European car manufacturers, and focuses on the development of an open standard for vehicle-to-vehicle and vehicle-to-infrastructure communications based on the already well established IEEE 802.11 WLAN standard. Ertico is an European multi-sector, public/private partnership with the intended purpose of the development and introduction of ITS systems. On a national level, FlandersDrive and The Telematics Cluster / ITS Belgium are the best known organizations. Despite the worldwide activities regarding (cooperative) ITS systems, there still is no consensus about the wireless technology to be used in such systems. This can be put down to the fact that a large number of suitable technologies exist or are under development. Each technology has its specific advantages and disadvantages, but no single technology is the ideal solution for every ITS application. However, the different candidates can be classified in three distinct categories. The first group contains solutions for Dedicated Short Range Communication (DSRC), such as the WAVE technology. The second group is made up of several cellular communication networks providing coverage over wide areas. Examples are GPRS (data communication using the GSM network), UMTS (faster then GPRS), WiMAX (even faster then UMTS) and MBWA (similar to WiMAX). The third group consists of digital data broadcast technologies such as RDS (via the current FM radio transmissions, slow), DAB and DMB (via current digital radio transmissions, quicker) and DVB-H (via future digital television transmissions for mobiledevices, quickest). The previous makes it clear that ITS systems are a hot topic right now, and they receive a lot of attention from the academic world, the standardization bodies and the industry. Therefore, it seems like that it is just a matter of time before ITS systems will find their way into the daily live. Due to the large number of suitable technologies for the implementation of cooperative ITS systems, it is very hard to define which role the government has to play in these developments, and which are the next steps to take. These issues were addressed in reports produced by the i2010 Intelligent Car Initiative and the CVIS project. Their state of the art overview revealed that until now, no country has successfully deployed a fully operational ITS system yet. Seven EU countries are the furthest and are already in the deployment phase: Sweden, Germany, the Netherlands, the United Kingdom, Finland, Spain and France. These countries are trailed by eight countries which are in the promotion phase: Denmark, Greece, Italy, Austria, Belgium,Norway, the Czech Republic and Poland. Finally, the last ten countries find themselves in the start-up phase: Estonia, Lithuania, Latvia, Slovenia, Slovakia, Hungary, Portugal, Switzerland, Ireland and Luxembourg. These European reports produced by the i2010 Intelligent Car Initiative and the CVIS project have defined a few policy recommendations which are very relevant for the Belgian and Flemish government. The most important recommendations for the Flemish government are: • Support awareness: research revealed that civilians consider ITS applications useful, but they are not really willing to pay for this technology. Therefore, it is important to convince the general public of the usefulness and the importance of ITS systems. • Fill the gaps: Belgium is situated in the promotion phase. This means that it should focus at identifying the missing stakeholders, and coordinating national and regional ITS activities. Here it is important that the research activities are coordinated in a national and international context to allow transfer of knowledge from one study to the next, as well as the results to be comparable. • Develop a vision: in the scope of ITS systems policies have to be defined regarding a large number of issues. For instance there is the question if ITS users should be educated, meaning that the use of ITS systems should be the subject of the drivers license exam. How will the regulations be for the technical inspection of vehicles equipped with ITS technology? Will ITS systems be deployed on a voluntary base, or will they e.g. be obliged in every new car? Will the services be offered by private companies, by the public authorities, or by a combination of them? Which technology will be used to implement ITS systems? These are just a few of the many questions where the government will have to develop a point of view for. • Policy coordination: ITS systems are a policy subject on an international, national and regional level. It is very important that these policy organizations can collaborate in a coordinated manner. • Iterative approach to policy development: developing policies for this complex matter is not a simple task. This asks for an iterative approach, where policy decisions are continuously refined and adjusted

    Evaluating the safety impact of connected and autonomous vehicles on motorways

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    Recent technological advancements bring the Connected and Autonomous Vehicles (CAVs) era closer to reality. CAVs have the potential to vastly improve road safety by taking the human driver out of the driving task. However, the evaluation of their safety impacts has been a major challenge due to the lack of real-world CAV exposure data. Studies that attempt to simulate CAVs by using either a single or integrating multiple simulation platforms have limitations, and in most cases, consider a small element of a network (e.g. a junction) and do not perform safety evaluations due to inherent complexity. This paper addresses this problem by developing a decision-making CAV control algorithm in the simulation software VISSIM, using its External Driver Model Application Programming Interface. More specifically, the developed CAV control algorithm allows a CAV, for the first time, to have longitudinal control, search adjacent vehicles, identify nearby CAVs and make lateral decisions based on a ruleset associated with motorway traffic operations. A motorway corridor within M1 in England is designed in VISSIM and employed to implement the CAV control algorithm. Five simulation models are created, one for each weekday. The baseline models (i.e. CAV market penetration: 0%) are calibrated and validated using real-world minute-level inductive loop detector data and also data collected from a radar-equipped vehicle. The safety evaluation of the proposed algorithm is conducted using the Surrogate Safety Assessment Model (SSAM). The results show that CAVs bring about compelling benefit to road safety as traffic conflicts significantly reduce even at relatively low market penetration rates. Specifically, estimated traffic conflicts were reduced by 12–47%, 50–80%, 82–92% and 90–94% for 25%, 50%, 75% and 100% CAV penetration rates respectively. Finally, the results indicate that the presence of CAVs ensured efficient traffic flow

    Impact analysis of accidents on the traffic flow based on massive floating car data

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    The wide usage of GPS-equipped devices enables the mass recording of vehicle movement trajectories describing the movement behavior of the traffic participants. An important aspect of the road traffic is the impact of anomalies, like accidents, on traffic flow. Accidents are especially important as they contribute to the the aspects of safety and also influence travel time estimations. In this paper, the impact of accidents is determined based on a massive GPS trajectory and accident dataset. Due to the missing precise date of the accidents in the data set used, first, the date of the accident is estimated based on the speed profile at the accident time. Further, the temporal impact of the accident is estimated using the speed profile of the whole day. The approach is applied in an experiment on a one month subset of the datasets. The results show that more than 72% of the accident dates are identified and the impact on the temporal dimension is approximated. Moreover, it can be seen that accidents during the rush hours and on high frequency road types (e.g. motorways, trunks or primaries) have an increasing effect on the impact duration on the traffic flow
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