Travel Time Reliability Index Research Articles

Quantifying the Effect of Rainfall and Visibility Conditions on Road Traffic Travel Time Reliability

Abstract This research explores a data-driven methodological framework to quantify the effect of rainfall and visibility on travel time reliability (TTR) by considering selected road segments in North Carolina. The framework includes capturing, processing, and integrating weather-related information and travel time data for the selected road segments. Various TTR indices were computed for the selected road segments under different rainfall and visibility ranges by day of the week (DOW) and time of the day (TOD). The TTR indices were computed for one week before and after (same DOW and TOD) under the normal weather condition and compared with those obtained under different intensities of rainfall and visibility. The variability in travel time patterns due to other events is expected to be marginal when considering the same DOW and TOD for comparison purposes. The results indicate that poor visibility with different rainfall intensities has the maximum adverse effect on the TTR. The outcomes from the data-driven methodological framework help the transportation planners in developing weather-responsive traffic management strategies and assessing their effectiveness using TTR indices. Significance Statement Travel time reliability (TTR) generally refers to the level of consistency or dependability in transportation service. It is considered as a measure of road operational performance. Ensuring higher levels of reliability is critical for efficient transportation system management along with mobility and accessibility needs. However, factors such as weather condition have a negative effect on the TTR. A data-driven methodological framework is proposed by integrating weather information and travel time data to quantify the effect of common weather conditions like rainfall and visibility on the TTR. The results indicated that heavy rain and poor visibility have an adverse effect on the TTR. These results are useful for agencies to better manage the traffic under different weather conditions.

Analyzing Travel Time Reliability from Sparse Probe Vehicle Data: A Case Study on the Effects of Spatial and Temporal Aggregation

Travel time reliability (TTR) indices have gained considerable attention for evaluating the quality of traffic infrastructure. Whereas TTR measures have been widely explored using data from stationary sensors with high penetration rates, there is a lack of research on calculating TTR from mobile sensors such as probe vehicle data (PVD) which is characterized by low penetration rates. PVD is a relevant data source for analyzing non-highway routes, as they are often not sufficiently covered by stationary sensors. The paper presents a methodology for analyzing TTR on (sub-)urban and rural routes with sparse PVD as the only data source that could be used by road authorities or traffic planners. Especially in the case of sparse data, spatial and temporal aggregations could have great impact, which are investigated on two levels: first, the width of time of day (TOD) intervals and second, the length of road segments. The spatial and temporal aggregation effects on travel time index (TTI) as prominent TTR measure are analyzed within an exemplary case study including three different routes. TTI patterns are calculated from data of one year grouped by different days-of-week (DOW) groups and the TOD. The case study shows that using well-chosen temporal and spatial aggregations, even with sparse PVD, an in-depth analysis of traffic patterns is possible.

A Dynamic Adaptive Algorithm for Merging Into Platoons in Connected Automated Environments

The automated merging control is one of the connected and automated vehicle applications that is expected to improve the operation and safety of freeway merging areas. This study introduces a dynamic adaptive algorithm for automated merging control based on a cost function of travel time for both on-ramp and mainline vehicles. The developed algorithm is designed to guide on-ramp vehicles to merge efficiently, without frequent slowdown or wait for merging gaps at the end of the ramp and with minimal disruption to the mainline traffic. The algorithm was evaluated under different mainline traffic demands, ranging from light to heavy conditions, using a simulation model for a one-mile freeway segment with two lanes and a single-lane on-ramp. Platooning is implemented in the simulation based on Cooperative Adaptive Cruise Control. The performance of the algorithm is compared to a base case where mainline vehicles cooperatively decelerate to help on-ramp vehicles merge. The results show that the proposed algorithm reduced ramp delays in the range of 38% to 91% for different traffic conditions, without disrupting mainline operation. Additionally, travel time reliability index improved in the range of 18% to 48% under different traffic conditions. According to the simulation results, the proposed automated merging algorithm is henceforth considered reliable, with its promising performance.

Travel Time Reliability Analysis on Selected Bus Route of Mysore Using GPS Data

This research study aims at evaluating the travel time reliability indices like Buffer Time Index, Planning Time Index and Travel Time Index over space and time on selected city bus route of Mysore city, India. Also, this study focuses on developing the correlation models between the bus journey speed and flow for different type of urban roadway conditions. These models are observed to be performing better and hence can be used for predicting traffic volumes for similar roadway conditions when traffic data are not available from field. Further, the variation of volume-to-capacity (V/C) with travel time reliability indices is also studied in detail. The k-means clustering analysis is performed for classifying the reliability measures with respect to V/C and Coefficient of Variation. It is expected that the developed reliability measures may be useful for defining level of service for bus routes in class-II cities (cities with lesser population than metropolitan cities).

Congestion Quantification Using the National Performance Management Research Data Set

Monitoring of transportation system performance is a key element of any transportation operation and planning strategy. Estimation of dependable performance measures relies on analysis of large amounts of traffic data, which are often expensive and difficult to gather. National databases can assist in this regard, but challenges still remain with respect to data management, accuracy, storage, and use for performance monitoring. In an effort to address such challenges, this paper showcases a process that utilizes the National Performance Management Research Data Set (NPMRDS) for generating performance measures for congestion monitoring applications in the Birmingham region. The capabilities of the relational database management system (RDBMS) are employed to manage the large amounts of NPMRDS data. Powerful visual maps are developed using GIS software and used to illustrate congestion location, extent and severity. Travel time reliability indices are calculated and utilized to quantify congestion, and congestion intensity measures are developed and employed to rank and prioritize congested segments in the study area. The process for managing and using big traffic data described in the Birmingham case study is a great example that can be replicated by small and mid-size Metropolitan Planning Organizations to generate performance-based measures and monitor congestion in their jurisdictions.

Travel Time Prediction Models and Reliability Indices for Palestine Urban Road in Baghdad City

Abstract
 Travel Time estimation and reliability measurement is an important issues for improving operation efficiency and safety of traffic roads networks. The aim of this research is the estimation of total travel time and distribution analysis for three selected links in Palestine Arterial Street in Baghdad city. Buffer time index results in worse reliability conditions. Link (2) from Bab Al Mutham intersection to Al-Sakara intersection produced a buffer index of about 36% and 26 % for Link (1) Al-Mawall intersection to Bab Al- Mutham intersection and finally for link (3) which presented a 24% buffer index. These illustrated that the reliability get worst for link (2), (1) and (3) respectively during the peak period. Extra delay is observed on link(1), (2) and (3) in terms of 95% percentile travel time of about (301.9, 219.4, and 193.8)sec. for Link (1, 2 and 3) respectively. Higher value for 95% travel time is obtained for link (1). Travel time index (TTI) of 4.2 %, 4.9% and 4% is obtained for Link (1, 2 and 3) respectively. Maximum value for delay per km that obtained for link (1) which is about 266 sec/km and 268 sec./km for link (3) and 244 sec/km for link(2). Different predicted model for the three studied links of Palestine street have been developed based on the obtained field data. A best fit is presented as compared the predicted models with the observed field travel time data for all the models of studied links which illustrated that the predicted model can present the actual field data.
 Keywords: Delay, Buffer Index, Travel Time, predicted model, Reliability, Urban Arterial.

Modeling basic freeway section level-of-service based on travel time and reliability

The assessment of operational performance is a challenge for the state, regional and local transportation agencies due to the complex and dynamic nature of traffic movement. A qualitative classification of operational performance is often done in the form of a six letter-grade, A to –F level-of-service (LOS) scale, defined in the Highway Capacity Manual (HCM). It is based on density for basic freeway sections, weaving sections, and merging/diverging areas. Presently, speed and travel time are two performance measures used by the practitioners when making decisions. Further, travel time reliability is becoming an important concept for modern and urban transportation system managers, planners and engineers. Efforts have been initiated through Strategic Highway Research Program (SHRP 2) to quantify LOS based on travel time reliability. To contribute to the body of knowledge, this paper adopts a microscopic simulation based method, and researches the validity of travel time and travel time reliability indices to quantify LOS thresholds for basic freeway sections. Findings indicate that the average travel time per mile threshold values for respective LOS letter-grades increase as the speed limit decreases, until the saturation point where the speed limit on the freeway does not have any influence on the operational performance. As the posted speed limit decreases, the percent difference between two adjacent travel time per mile threshold values also decreases. Further, the average travel time reliability LOS threshold values for the respective LOS letter-grades decrease as the speed limit decreases.

Dynamic Travel Time Reliability of Urban Road Network Based on Road Users

AbstractMost research on travel time reliability (TTR) is from the perspective of the road managers. Therefore, dynamic TTR from the view of road users is proposed. The concept considers the influence of random road network variations on road users. Two dimensions of travel time distribution and its temporal-spatial characteristic are analyzed. Based on daily variation reliability and assumptions of normal distribution of travel time and given threshold value, the influencing factors are studied according to its probability density distribution function. A TTR index is then proposed. Link and route TTRs are computed with the index, and the dynamic TTR of urban road networks is calculated and investigated. Three methods are adopted separately to compute the route TTR on a test road network. The traditional method is flawed, whereas the presented reliability index method and Monte Carlo method can obtain comparable results. Therefore, the validity of the reliability index method is verified.

Investigating Travel Time Reliability Measures in Toll Design Problem

Congestion pricing has been regarded as an effective method of reducing networkwide travel cost. Previous work on the toll-design problem focused on the deterministic network, assuming that the network operates deterministically without uncertainty. This essentially precludes investigating the recently proposed travel time reliability indices as a system performance measure to evaluate and prioritize the selection of future investment strategies. In this study, the authors investigate various recently proposed travel time reliability measures in determining the optimal toll strategies to improve travel time reliability in the network. A simulation-based genetic algorithm (SGA) procedure is developed to solve the stochastic bi-level programming problem. The experimental results using a simple test network show that optimal toll determined by the misery index can improve both travel time reliability for network users and total travel time for the network planner.

Comparative study on travel time reliability indexes for highway users and operators

SUMMARYTravel time reliability is an emerging evaluation measure for highway network service levels. This paper focuses on travel time reliability indexes for a highway network and proposes new travel time indexes for users. The paper also discusses and compares several previously and newly proposed indexes for use by both highway users and operators. Because this comparative study requires travel time variation, two models are developed for estimating travel time variation. One is the multi‐hierarchical stochastic model for estimating travel time variation under uncertainty in demand and service. The other is the temporal and spatial transition model using actual traffic detector data. Then, new indexes for assessing travel time reliability are proposed. Because operators of highway network are interested in the degree of congestion and delay, the previously proposed indexes are regarded as operator‐side indexes. The highway users are, however, interested in the accuracy of their travel time and in the earlier arrival at their destination. Thus, this paper proposes the user‐side indexes. Travel time reliability indexes, including previously proposed indexes, are calculated on the basis of the cumulative distribution function outcome from these models and are compared and discussed. In two sections, 11 indexes with different characteristics are compared. One of the results is that these indexes behave differently for the same route. This suggests that understanding an index's formulation and characteristics is important for selecting the appropriate index according to both the purpose of use and the characteristics of the study route. Another important result is that indexes useful for the user side do not always agree with the operator‐side indexes. Finally, the results of the comparative study suggest that the combination of average travel time and an appropriate travel time reliability index is very important for both users and operators for assessing the route reliability properly. Copyright © 2012 John Wiley & Sons, Ltd.

Travel Time Reliability for Rescue and Recovery after Disaster

Travel time reliability is very important for normal period and abnormal period especially disaster recovery. However, traditional indexes can not reflect travel time reliability in disaster areas. Thus a new travel time reliability index for disaster is proposed in this paper. The index proposed in this paper is different from usual indexes because of some special factors in disaster. Firstly, traffic capacity can be ignored because the traffic network would be controlled by transportation department. Secondly, the buffer time is difficult to estimate because traffic conditions are unknown after disaster, thus the traffic accessibility is used to build the new index for disaster recovery. Thirdly, distance of damaged roads is an important factor. The parameters of disaster scale or damage level are also discussed. However, the simulated results from this model are imperfect because some disaster areas are unpredictable and only the historical data can be use. Therefore, more factors and simulations should be considered to improve this model in the future.

Investigating Travel Time Reliability Measures in Toll Design Problem

Congestion pricing has been regarded as an effective method of reducing networkwide travel cost. Previous work on the toll-design problem focused on the deterministic network, assuming that the network operates deterministically without uncertainty. This essentially precludes investigating the recently proposed travel time reliability indices as a system performance measure to evaluate and prioritize the selection of future investment strategies. In this study, the authors investigate various recently proposed travel time reliability measures in determining the optimal toll strategies to improve travel time reliability in the network. A simulation-based genetic algorithm (SGA) procedure is developed to solve the stochastic bi-level programming problem. The experimental results using a simple test network show that optimal toll determined by the misery index can improve both travel time reliability for network users and total travel time for the network planner.

Travel time reliability for recovery activity immediately after disaster

There are many models on travel time reliability that have been applied to many traffic conditions including traffic jams and road constructions (Wakabayashi, 2008). In fact, travel time reliability is also important for disaster recovery (Aaskura et al., 1998). This paper proposes a concept and a requirement for a new travel time reliability index in disaster recovery period.The traditional connectivity reliability analysis can not reflect the travel time reliability in disaster areas although the travel time is important in disaster recovery period. Thus a new index which reflects the travel time reliability should be developed in order to insure the emergency operation (Wakabayashi, 2008). We develop a new model for travel time reliability to relieve the excess demand of traffic when a disaster occurs.The travel time reliability for disaster recovery in our model is different from the usual travel time reliability because of the special factors in disaster. Firstly, the traffic capacity is not considered in our model because the road network would be controlled by transportation department and the traffic capacity can be ignored under the human control. Secondly, the buffer time in our model is difficult to estimate because the traffic condition is unknown when a disaster occurs (Lomax et al., 2003), so the traffic accessibility is considered in our model (Lwan et al., 2003). Thirdly, the path's distance is an important factor in our model. The influence of path's distance will be remarkable in the central disaster areas and almost disappear in the boundary part of disaster areas. It also means that the influence of distance will increase no longer when the length of the distance is beyond a certain critical point.The relation between travel time reliability for disaster recovery and traffic accessibility is also studied from various network hierarchies, involving path, OD pair and the whole network (Tu et al., 2007). The parameters which stood for the disaster scale or the damage level are also discussed.Because the disaster of some areas is unpredictable, we only use the historical data to certificate the model, and then the simulated results of our model for some disasters are imperfect. So this model is only a theoretical model and cannot be used for the actual situation. More factors and simulations should be considered to solve the defects of our model.

IMPACT OF ROAD PRICING ON THE NETWORK RELIABILITY

In this paper, the impact of road pricing on the transport network reliability is investigated with the use of a newly developed reliability-based user equilibrium (RUE) model. The RUE model can be adopted to overcome the difficulty in predicting the flow pattern in a congested and unreliable road network. In this RUE model, both the travel time and travel time reliability are taken into account for drivers' route choices by introducing a concept of path preference index (PI) to quantify the attractiveness of each alternative path for travel between a particular origin-destination pair. The PI is a weight sum of the path travel time index (TI) and the path travel time reliability index (RI), which represent the travel time and travel time reliability on a particular path respectively. The RUE model can be applied to investigate the effects of road pricing on travel time and reliability in urban road networks, in which drivers would consider both the travel time and its reliability for their route choices. In this paper, the RUE model is extended to maximize the network reliability by road pricing. The results demonstrated the trade-off between the total network travel time and the network travel time reliability. The effects of the toll on the total network travel time and the network travel time reliability are investigated.

Using Travel Time Reliability Measures to Improve Regional Transportation Planning and Operations

Estimation of travel time is of increasing importance to travelers and transportation professionals alike as congestion worsens in major urban areas. In fact, the reliability of travel time estimates on a given corridor may be more important for travelers, shippers, and transport managers than the travel time itself. This paper examines the uses of measured travel time reliability indices for improving real-time transportation management and traveler information with the use of archived intelligent transportation system data. A literature review of travel time reliability and its value as a congestion measure is followed by a description of a content analysis of 20 regional transportation plans from across the nation. Results from the content analysis indicate that travel time reliability is not currently used as a congestion measure and that the most common measures of congestion are the volume-to-capacity ratio, vehicle hours of delay, and mean speed. As a case study using data from Portland, Oregon, several reliability measures are then tested including travel time, 95th percentile travel time, travel time index, buffer index, planning time index, and congestion frequency. The buffer index is used to prioritize freeway corridors according to travel time reliability. Metropolitan planning organizations should use travel time reliability in the following ways: (a) incorporate it as a systemwide goal, (b) evaluate roadway segments according to travel time reliability measures, and (c) prioritize roadway segments using those measures.