69,215 research outputs found

    How Effective are Toll Roads in Improving Operational Performance?

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    The main focus of this research is to develop a systematic analytical framework and evaluate the effect of a toll road on region’s traffic using travel time and travel time reliability measures. The travel time data for the Triangle Expressway in Raleigh, North Carolina, United States was employed for the assessment process. The spatial and temporal variations in the travel time distributions on the toll road, parallel alternate route, and near-vicinity cross-streets were analyzed using various travel time reliability measures. The results indicate that the Triangle Expressway showed a positive trend in reliability over the years of its operation. The parallel route reliability decreased significantly during the analysis period, whereas the travel time reliability of cross-streets showed a consistent trend. The stabilization of travel time distributions and the reliability measures over different years of toll road operation are good indicators, suggesting that further reduction in performance measures may not be seen on the near vicinity corridors. The findings from link-level and corridor-level analysis may help with transportation system management, assessing the influence of travel demand patterns, and evaluating the effect of planned implementation of similar projects

    How to monitor sustainable mobility in cities? Literature review in the frame of creating a set of sustainable mobility indicators

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    The role of sustainable mobility and its impact on society and the environment is evident and recognized worldwide. Nevertheless, although there is a growing number of measures and projects that deal with sustainable mobility issues, it is not so easy to compare their results and, so far, there is no globally applicable set of tools and indicators that ensure holistic evaluation and facilitate replicability of the best practices. In this paper, based on the extensive literature review, we give a systematic overview of relevant and scientifically sound indicators that cover different aspects of sustainable mobility that are applicable in different social and economic contexts around the world. Overall, 22 sustainable mobility indicators have been selected and an overview of the applied measures described across the literature review has been presented

    Performance Measures to Assess Resiliency and Efficiency of Transit Systems

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    Transit agencies are interested in assessing the short-, mid-, and long-term performance of infrastructure with the objective of enhancing resiliency and efficiency. This report addresses three distinct aspects of New Jersey’s Transit System: 1) resiliency of bridge infrastructure, 2) resiliency of public transit systems, and 3) efficiency of transit systems with an emphasis on paratransit service. This project proposed a conceptual framework to assess the performance and resiliency for bridge structures in a transit network before and after disasters utilizing structural health monitoring (SHM), finite element (FE) modeling and remote sensing using Interferometric Synthetic Aperture Radar (InSAR). The public transit systems in NY/NJ were analyzed based on their vulnerability, resiliency, and efficiency in recovery following a major natural disaster

    Feasibility of expanding traffic monitoring systems with floating car data technology

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    Trajectory information reported by certain vehicles (Floating Car Data or FCD) can be applied to monitor the road network. Policy makers face difficulties when deciding to invest in the expansion of their infrastructure based on inductive loops and cameras, or to invest in a FCD system. This paper targets this decision. The provided FCD functionality is investigated, minimum requirements are determined and reliability issues are researched. The communication cost is derived and combined with other elements to assess the total costs for different scenarios. The outcome is to target a penetration rate of 1%, a sample interval of 10 seconds and a transmission interval of 30 seconds. Such a deployment can accurately determine the locations of incidents and traffic jams. It can also estimate travel times accurately for highways, for urban roads this is limited to a binary categorization into normal or congested traffic. No reliability issues are expected. The most cost efficient scenario when deploying a new FCD system is to launch a smartphone application. For Belgium, this costs 13 million EUR for 10 years. However, it is estimated that purchasing data from companies already acquiring FCD data through their own product could reduce costs with a factor 10

    The economic costs of road traffic congestion

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    The main cause of road traffic congestion is that the volume of traffic is tooclose to the maximum capacity of a road or network. Congestion in the UK isworse than many, perhaps most, other European countries. More important, itis getting worse, year by year. Current official forecasts imply that congestionwill be substantially worse by the end of this decade, even on the veryfavourable assumption that all current Government projects and policies areimplemented in full, successfully, and to time. This is because road traffic isgrowing faster than road capacity. This is not a temporary problem: it willcontinue to be the case, in the absence of measures to reduce traffic, because itis infeasible to match a road programme to unrestricted trends in traffic growth.The effect, using the current Government method of measuring congestion,and a long established method of valuing it, would be that the widely quotedfigure of an annual cost of £20 billion, would increase to £30 billion by 2010.Under current social and economic frameworks, there are no feasible policiesthat could reduce congestion to zero in practice, or that would be worthwhiledoing in theory. But savings worth £4b-£6b a year could in principle be madeby congestion charging alone, over the whole network, of which (veryapproximately) half might be reflected in the prices of goods, and half insavings in individuals? own time spent travelling. A good proportion of thiscould alternatively be secured by an appropriate package of alternativemeasures: priority lanes and signalling; switching to other modes includingfreight to rail and passenger movements to public transport, walking andcycling; ?soft? policies to encourage reduced travel by car; land-use patternswhich reduce unnecessary travel; and associated measures to prevent benefitsfrom being eroded by induced travel. The combined effects of road chargingand a supportive set of complementary measures represent the best that couldbe reasonably achieved in the short to medium run. This could reducecongestion costs (as distinct from slowing down their increase) by 40%-50%.These broad-brush figures, though based on long-established methods, must betreated with great caution. The ?cost of congestion?, as used for thesecalculations, is based on relationships which in reality are not exact, stable oreven meaningful. The wrong indicator has been used, comparing average realspeeds with average ideal speeds. But in the real world, speeds are differentevery day, and so is the level of congestion. For just-in-time operation, and formuch personal and business travel, variability and reliability are much moreimportant. The really costly effect of congestion is not the slightly increasedaverage time, but the greater than average effect in particular locations andmarkets, and the greatly increased unreliability.During the near future, until road pricing is implemented, increases in roadcongestion can lead to some shift in the balance of attractiveness of rail freight,sufficient for a proportion of the freight market to transfer from road. Thiswould in turn make a small but significant contribution to reducing congestion,especially in some specific important corridors. Even though rail freight isusually a small proportion of all freight, the annual economic saving incongestion cost, to road users generally, from transferring a 5-times a week,200 mile round trip, mostly on congested motorways, from road to rail wouldbe in the order of £40,000 to £80,000, to which should be added thecommercial cost savings made by the freight operator who chooses to do so. Itshould be emphasised that sustaining this would require measures to preventinduced car traffic filling up the relieved road space.An example of the impact of factoring in unreliability is given by approximatecalculations made for journeys such as Glasgow to Newcastle, Cardiff toDover, or London to Manchester. In free-flow theory these could be 3-hourjourneys, but moderate congestion requires adding an hour to the average timeand another hour safety margin to ensure that a tight delivery slot is not missedtoo often. In congestion so severe as to double the average time, the extrasafety margin for unreliability could be as much as 4 hours, which is simply notfeasible in many cases.The ?total cost of congestion? is a large number, but it is practicallymeaningless and by ?devaluing the currency? it distracts attention from moreimportant, achievable, objectives. It would be better not to use it as a target forpolicy. The two key important things to do are:· Strategic action to reduce traffic volume to a level where conditions do notvary too much from day to day. In some circumstances this will slightlyincrease average speed, though not always: in some road conditions areduction of average speed can greatly improve the smoothness of trafficflow. But in both cases, it will greatly increase reliability, this being moreimportant than the change in average speed;· Practical measures to provide good alternatives for freight and passengermovements which reduce the intensity of use of scarce road space incongested conditions. Even where this only applies to a minority ofmovements, significant effects are possible.The Government plans to ?re-launch? the Ten Year Plan for Transport thisSummer or Autumn. It is not reasonable to expect that the re-launch willinclude congestion charging for cars within the decade, so it will need to planfor it as soon as possible after, and a short-term coping strategy of prioritymeasures to protect the most important classes of movement (both passengerand freight) from congestion in the period before charging is implemented

    Assessing the Impact of Game Day Schedule and Opponents on Travel Patterns and Route Choice using Big Data Analytics

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    The transportation system is crucial for transferring people and goods from point A to point B. However, its reliability can be decreased by unanticipated congestion resulting from planned special events. For example, sporting events collect large crowds of people at specific venues on game days and disrupt normal traffic patterns. The goal of this study was to understand issues related to road traffic management during major sporting events by using widely available INRIX data to compare travel patterns and behaviors on game days against those on normal days. A comprehensive analysis was conducted on the impact of all Nebraska Cornhuskers football games over five years on traffic congestion on five major routes in Nebraska. We attempted to identify hotspots, the unusually high-risk zones in a spatiotemporal space containing traffic congestion that occur on almost all game days. For hotspot detection, we utilized a method called Multi-EigenSpot, which is able to detect multiple hotspots in a spatiotemporal space. With this algorithm, we were able to detect traffic hotspot clusters on the five chosen routes in Nebraska. After detecting the hotspots, we identified the factors affecting the sizes of hotspots and other parameters. The start time of the game and the Cornhuskers’ opponent for a given game are two important factors affecting the number of people coming to Lincoln, Nebraska, on game days. Finally, the Dynamic Bayesian Networks (DBN) approach was applied to forecast the start times and locations of hotspot clusters in 2018 with a weighted mean absolute percentage error (WMAPE) of 13.8%

    Modeling the Effect of a Road Construction Project on Transportation System Performance

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    Road construction projects create physical changes on roads that result in capacity reduction and travel time escalation during the construction project period. The reduction in the posted speed limit, the number of lanes, lane width and shoulder width at the construction zone makes it difficult for the road to accommodate high traffic volume. Therefore, the goal of this research is to model the effect of a road construction project on travel time at road link-level and help improve the mobility of people and goods through dissemination or implementation of proactive solutions. Data for a resurfacing construction project on I-485 in the city of Charlotte, North Carolina (NC) was used evaluation, analysis, and modeling. A statistical t-test was conducted to examine the relationship between the change in travel time before and during the construction project period. Further, travel time models were developed for the freeway links and the connecting arterial street links, both before and during the construction project period. The road network characteristics of each link, such as the volume/ capacity (V/C), the number of lanes, the speed limit, the shoulder width, the lane width, whether the link is divided or undivided, characteristics of neighboring links, the time-of-the-day, the day-of-the-week, and the distance of the link from the road construction project were considered as predictor variables for modeling. The results obtained indicate that a decrease in travel time was observed during the construction project period on the freeway links when compared to the before construction project period. Contrarily, an increase in travel time was observed during the construction project period on the connecting arterial street links when compared to the before construction project period. Also, the average travel time, the planning time, and the travel time index can better explain the effect of a road construction project on transportation system performance when compared to the planning time index and the buffer time index. The influence of predictor variables seem to vary before and during the construction project period on the freeway links and connecting arterial street links. Practitioners should take the research findings into consideration, in addition to the construction zone characteristics, when planning a road construction project and developing temporary traffic control and detour plans

    17-11 Evaluation of Transit Priority Treatments in Tennessee

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    Many big cities are progressively implementing transit friendly corridors especially in urban areas where traffic may be increasing at an alarming rate. Over the years, Transit Signal Priority (TSP) has proven to be very effective in creating transit friendly corridors with its ability to improve transit vehicle travel time, serviceability and reliability. TSP as part of Transit Oriented Development (TOD) is associated with great benefits to community liveability including less environmental impacts, reduced traffic congestions, fewer vehicular accidents and shorter travel times among others.This research have therefore analysed the impact of TSP on bus travel times, late bus recovery at bus stop level, delay (on mainline and side street) and Level of Service (LOS) at intersection level on selected corridors and intersections in Nashville Tennessee; to solve the problem of transit vehicle delay as a result of high traffic congestion in Nashville metropolitan areas. This study also developed a flow-delay model to predict delay per vehicle for a lane group under interrupted flow conditions and compared some measure of effectiveness (MOE) before and after TSP. Unconditional green extension and red truncation active priority strategies were developed via Vehicle Actuated Programming (VAP) language which was tied to VISSIM signal controller to execute priority for transit vehicles approaching the traffic signal at 75m away from the stop line. The findings from this study indicated that TSP will recover bus lateness at bus stops 25.21% to 43.1% on the average, improve bus travel time by 5.1% to 10%, increase side street delay by 15.9%, and favour other vehicles using the priority approach by 5.8% and 11.6% in travel time and delay reduction respectively. Findings also indicated that TSP may not affect LOS under low to medium traffic condition but LOS may increase under high traffic condition
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