scholarly journals New Travel Time Reliability Methodology for Urban Arterial Corridors

Author(s):  
Ernest O. A. Tufuor ◽  
Laurence R. Rilett

The need for reliable performance measures of urban arterial corridors is increasing because of the rise in traffic congestion and the high value of users’ travel time. Consequently, travel time reliability (TTR), which attempts to capture the day-to-day variability in travel times, has recently received considerable research interest. The basis of all TTR metrics is the underlying travel time distribution (TTD) along the given link or corridor. Estimating and forecasting arterial corridor TTDs for TTR analysis is the focus of this paper. This paper proposes a TTR methodology that addresses some of the limitations of the current U.S. state-of-the-art methodology which was published in the 6th edition of the Highway Capacity Manual (HCM6). Specifically, HCM6 can only estimate average TTD and not the population TTD. However, the population TTD is needed for accurate trip decision-making by individual drivers and logistics companies. In addition, HCM6 cannot be used to analyze the effect of new technologies, such as connected and automated vehicles, nor can it be used easily for long corridors or networks. The proposed TTR methodology, which is traffic-microsimulation based, was applied on a 1.16 mi arterial testbed in Lincoln, Nebraska, U.S. It was shown that the proposed TTR methodology, when calibrated, could replicate the empirical population TTD at a 5% significance level. The population TTD could also be transformed into an average TTD that also replicated the corresponding empirical average TTD at a 5% significance level.

Author(s):  
Nabaruna Karmakar ◽  
Seyedbehzad Aghdashi ◽  
Nagui M. Rouphail ◽  
Billy M. Williams

Traffic congestion costs drivers an average of $1,200 a year in wasted fuel and time, with most travelers becoming less tolerant of unexpected delays. Substantial efforts have been made to account for the impact of non-recurring sources of congestion on travel time reliability. The 6th edition of the Highway Capacity Manual (HCM) provides a structured guidance on a step-by-step analysis to estimate reliability performance measures on freeway facilities. However, practical implementation of these methods poses its own challenges. Performing these analyses requires assimilation of data scattered in different platforms, and this assimilation is complicated further by the fact that data and data platforms differ from state to state. This paper focuses on practical calibration and validation methods of the core and reliability analyses described in the HCM. The main objective is to provide HCM users with guidance on collecting data for freeway reliability analysis as well as validating the reliability performance measures predictions of the HCM methodology. A real-world case study on three routes on Interstate 40 in the Raleigh-Durham area in North Carolina is used to describe the steps required for conducting this analysis. The travel time index (TTI) distribution, reported by the HCM models, was found to match those from probe-based travel time data closely up to the 80th percentile values. However, because of a mismatch between the actual and HCM estimated incident allocation patterns both spatially and temporally, and the fact that traffic demands in the HCM methods are by default insensitive to the occurrence of major incidents, the HCM approach tended to generate larger travel time values in the upper regions of the travel time distribution.


Author(s):  
Ernest O. A. Tufuor ◽  
Laurence R. Rilett

The Highway Capacity Manual 6th edition (HCM6) includes a new methodology to estimate and predict the distribution of average travel times (TTD) for urban streets. The TTD can then be used to estimate travel time reliability (TTR) metrics. Previous research on a 0.5-mi testbed showed statistically significant differences between the HCM6 estimated TTD and the corresponding empirical TTD. The difference in average travel time was 4 s that, while statistically significant, is not important from a practical perspective. More importantly, the TTD variance was underestimated by 70%. In other words, the HCM6 results reflected a more reliable testbed than field measurement. This paper expands the analysis on a longer testbed. It identifies the sources and magnitude of travel time variability that contribute to the HCM6 error. Understanding the potential sources of error, and their quantitative values, are the first steps in improving the HCM6 model to better reflect actual conditions. Empirical Bluetooth travel times were collected on a 1.16-mi testbed in Lincoln, Nebraska. The HCM6 methodology was used to model the testbed, and the estimated TTD by source of travel time variability was compared statistically to the corresponding empirical TTD. It was found that the HCM6 underestimated the TTD variability on the longer testbed by 67%. The demand component, missing variable(s), or both, which were not explicitly considered in the HCM6, were found to be the main source of the error in the HCM6 TTD. A focus on the demand estimators as the first step in improving the HCM6 TTR model was recommended.


Author(s):  
Wei Sun ◽  
Scott S. Washburn

Applications in the field often require analysis of freeway travel time reliability (TTR) at the network level. While micro-simulation is suitable for performing network-level analysis, the computational burden can become unreasonable when TTR analysis is factored in. As for macro-simulation, most network analysis studies often use simplified link performance functions to represent the travel time and flow relationship. Such functions are not generally sensitive to the range of geometric and traffic conditions that can influence freeway facility operations. This research extends the Highway Capacity Manual (HCM) freeway TTR analysis methodology to the network level. The proposed freeway network TTR analysis methodology generates scenarios that represent the impacts of origin–destination (OD) demand variations, weather events, incident events, and work zone events on freeway network travel time. For each scenario, the methodology performs user equilibrium (UE) traffic assignment and the HCM freeway facility core methodology is applied to represent the travel time and flow relationship. The method of successive average approach is applied to solve the UE traffic assignment. Finally, scenario travel times (and/or other performance measures) are aggregated into various distributions of interest, such as the network-, facility-, and OD-level distributions, and TTR performance measures are calculated at the three different levels. A software tool is developed using C# language on the .NET Framework. The software tool provides a convenient and efficient approach for transportation planners and researchers to conduct the freeway network TTR analysis, which helps to bridge the gap between research and practice.


2013 ◽  
Author(s):  
Paul Ryus ◽  
James Bonneson ◽  
Richard Dowling ◽  
John Zegeer ◽  
Mark Vandehey ◽  
...  

Author(s):  
Ernest O. A. Tufuor ◽  
Laurence R. Rilett

The 6th edition of the Highway Capacity Manual (HCM-6) includes the concept of travel time reliability (TTR), which attempts to determine the distribution of average trip travel times over an extended period. TTR is an inherent part of travelers’ route choice decisions and is used by traffic managers to better quantify operations rather than simply using average travel times. The focus of this paper is on the HCM-6 urban street TTR methodology contained in Chapter 17. The approach uses historical data (e.g., weather and volume fluctuations) and simple empirical data (e.g., 1-day volume count) to provide the user with average travel time and reliability predictions for a traffic facility over an extended period (e.g., a year). To the best of the authors’ knowledge, there is no existing literature on validating the HCM-6 methodology with empirical data. The goals of this paper were to validate the HCM-6 urban street reliability methodology by comparing the empirical Bluetooth (BT) travel time distributions with the estimated HCM-6 distribution, and to propose potential HCM-6 augmentation strategies. Archived BT data from a 0.5-mi urban arterial in Lincoln, Nebraska was used for comparison. It was found that there were statistically significant differences, but minimal practical differences, between the mean of the predicted HCM-6 travel time distribution and the mean of the empirical distribution. However, the HCM-6 distribution had a lower variance than the empirical distribution. Not surprisingly, the HCM-6 model underestimated the TTR metrics (buffer index and the planning time index) by approximately 62% and 9%, respectively.


Author(s):  
Ernest Tufuor ◽  
Laurence Rilett ◽  
Sean Murphy

The 6th edition of the Highway Capacity Manual (HCM6) introduced a methodology for estimating and forecasting arterial travel time (TT) distributions (TTD) and their associated travel time reliability (TTR) metrics. Recently, it was shown that the HCM6 severely underestimated both the TTD and the TTR metrics for a test network in Lincoln, NE, U.S. Subsequently, it was shown that the underestimation issue could be eliminated through a proposed calibration methodology. Because this validation and calibration work was done on a single, relatively short section of arterial roadway there is an open research question on whether this finding applies to longer and more congested arterial roadways. The goal of this paper is to validate and calibrate the HCM6 TTR methodology on five arterial roadway testbeds that are longer and more congested than the original testbed. Empirical data from the National Performance Management Research Data Set (NPMRDS) which is managed by INRIX was used to represent the ground truth. Similar to the original study, it was found that the HCM6 TTR methodology severely underestimated the TTDs, and their respective TTR metrics, on all five testbeds. This is problematic, because the HCM6 methodology indicates that the corridors had more reliable TT than the empirical data would suggest. It was also shown that the calibration methodology eliminated this underestimation. It is recommended that users of the HCM6 TTR methodology validate and, if necessary, calibrate the model using local empirical travel data.


2014 ◽  
Author(s):  
Wayne Kittelson ◽  
Mark Vandehey ◽  
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...  

Author(s):  
Rubén José Calderas Volcanes ◽  
Emilio Germán Moreno González

Settlements of uncontrolled population on side of road in Venezuela originate the excessive use of traffic speed reducers to mitigate accidents. Misuse of these speed control devices generate problem of functionality in the two-lane main rural roads which requires to be studied to demonstrate its effect on the capacity and level of service. Although other factors may occur (i.e, environmental problems and health), the disproportionate use of speed-bumps worsens circulation quality by increase of travel time as most sensitive parameter. Where this effect not can be reversed it should be made efforts to mitigate speed using another traffic-calming device. The studied stretches are selected according to particular characteristics such as: urban settlement, isolated speed-bump and its installation in series, including case without speed-bumps which guarantees the proper contrast. Video cameras to detect the travel time of vehicles are used in each road section, it allow the measures of other parameters.The travel time distribution with or without speed-bumps and probability distribution that characterizes vehicle movement in each stretch allows the simulation and modeling with the ARENA software. Travel time allows obtain the speed which, together with the volume of traffic, determines the level of service according to the Highway Capacity Manual criterion. The economic cost of substitute measures versus travel time is evaluated and may be useful in decision-making or implementation of better policies by transport governmental institutions.DOI: http://dx.doi.org/10.4995/CIT2016.2016.2255 


Author(s):  
Chao Chen ◽  
Alexander Skabardonis ◽  
Pravin Varaiya

Statistics from a corridor along Interstate 5 in Los Angeles show that average travel time and travel-time variability are meaningful measures of freeway performance. Variability of travel time is an important measure of service quality for travelers. Travel time can be used to quantify the effect of incidents, and incident information can help reduce travel-time uncertainty. Predictability of travel time is a measure of the benefits of intelligent transportation systems. These measures differ from those defined in the Highway Capacity Manual and other aggregate measures of delay.


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