Average Travel Speed Research Articles

Analysis of discharge consistency and performance of a sugarcane billet planter with side-conveyer concept

Sugarcane is an important economic crop of Okinawa Prefecture. The sugarcane billet planter has been widely used in Okinawa due to high labor costs and planting time limits. Most of them were powered by hydraulic systems to avoid ground wheel drive problems when working under high moisture heavy clay conditions. This study aimed to evaluate the performance and discharge consistency of the sugarcane billet planter, YABIKU B600, operated in Minami Daito Island, Okinawa Prefecture. The Ni28 cultivar seed cane was harvested and chopped to an average length of 21.8 cm by Austoft TM2008 harvester. The field experiment was done with 3 replications. A video camera with GPS logger was positioned over the hopper of the planter during the tests to examine the performance and planting consistency of the planter. The numbers of discharged billets at each frame were recorded to calculate the discharge index or planting rate. Moreover, the speed, GPS position and time of each activity were collected to obtain the field capacity and field efficiency of the planter. The results showed that the average traveling speed of the planter was 0.97 m/s. The field capacity was 0.24 ha/hr with a field efficiency of 45.66%. The average discharge index was 7.2 billet/m. Considering a discharge index range of 8-10 billet/m, the precision index averaged 24.63%.

Analysis on safety impact of red light cameras using the Empirical Bayesian approach

Traffic signal violations at urban intersections have become a major safety concern in urban areas since, compared to other types of crashes, they may cause a higher percentage of injuries and fatal crashes. Therefore, the deployment of red light cameras has been concentrated on urban intersections, both to prevent traffic signal violations and to reduce vehicle crashes. Other methodologies for establishing the safety impact of red light cameras are also being researched, but accurate results are difficult to ascertain. In this study, the safety impact of red light cameras on urban intersections in Daejeon Metropolitan City, South Korea was assessed using the Empirical Bayesian (EB) approach. According to the EB analysis in this study, red light camera has increased fatal crashes in all crash types by around 2%. However, it has also increased injury crashes in all crash types by about 53%. In specific types of crashes at urban intersections, such as angle, sideswipe & rear-end, and head-on, red light cameras have reduced fatal crashes by around 23%. However, injury crashes for typical crash types at urban intersections have actually increased by around 37%. Furthermore, the EB analysis results of total crashes are similar to those of injury crashes. This may be the result of a higher than average travel speed on arterial link sections in Daejeon compared to that of other metropolitan cities like Seoul. Therefore, the higher average speed on arterial roads may be the cause of the increase of injuries resulting from sideswipe & rear-end crashes.

Evaluation of Level-of-Service Measures for Two-Lane Highways with a Simulation Model

Most highway capacity guidelines use two main traffic measures to establish the level of service for two-lane highways: average travel speed (ATS) and percentage of time spent following (PTSF). In the Highway Capacity Manual (HCM), directional ATS is related to volume by using a linear expression with a single coefficient for volume in both directions (travel and opposing), whereas in other capacity guides such as those in Germany, Finland, and Brazil, a nonlinear form of expression is used; some of these expressions use different coefficients for travel and opposing volumes. In the HCM, directional PTSF is related to volume by using an exponential expression. Other models use a slightly different exponential form of model with different coefficients. The purpose of this research is to use a newly developed and calibrated two-lane microsimulation model to investigate the relationship between traffic volume and directional ATS and PTSF. New expressions are suggested and subsequently compared with those of the HCM and of a number of existing European and South American models. The simulation results show that, unlike the HCM expression, ATS versus volume has a nonlinear convex shape especially at low volume in the travel direction. This finding is in accordance with German, Finnish, and Brazilian models. A new nonlinear exponential expression is suggested to replace the current linear expression for ATS versus volume in the HCM. The HCM PTSF model structure, however, was found to be in accordance with simulation results. Hence, model coefficients were updated for PTSF only.

Operational Impact of Horizontal and Vertical Alignment of Two-Lane Highways

The Highway Capacity Manual (HCM) defines the level-of-service criteria for two-lane highways based on three performance measures: average travel speed (ATS), percent time spend following (PTSF) and percent of free-flow speed (PFFS). The performance measures are affected by the lack of passing opportunities, which is quantified through adjustment factors depending on the percentage of no passing zones. Passing zones are provided where available sight distance is greater than the minimum passing sight distance; and their length and frequency depend mainly on the physical constrains and cost limitations. HCM current evaluation of traffic performance excludes horizontal alignment variations, which could produce more or less sinuous alignments and thus affect potentially to both average travel speed and percentage time spent following. Moreover, HCM considers terrain type rather than the actual vertical profile, which could overestimate or underestimate the expected traffic performance depending on how accurately the roadway was adapted to the terrain. The objective of the research is to analyze the relationship between highway horizontal alignment, characterized by curvature change rate (CCR), highway vertical alignment, characterized by the gradient change rate, and traffic performance, based on ATS and PTSF. For the research, 25 Spanish two-lane rural highways were selected. Horizontal geometry was obtained from Google Earth using an azimuth-based restitution program. CCR was calculated and used to identify homogenous segments. Vertical alignment was recreated from GPS data. The sample included 112 homogeneous segments and 451 passing zones. After the geometry-based characterization, 20 homogeneous segments were introduced and simulated in the TWOPAS simulation model. TWOPAS was previously calibrated and validated with passing maneuvers data from Spanish highways. Traffic conditions (directional traffic volume, directional split and percentage of heavy vehicles) were varied. The analysis of the simulation results provided models of PTSF and ATS depending on CCR and gradient change rate, among other parameters. The results of this research will help highway designers and practitioners to predict operational performance based on CCR, type of gradient and expected hourly traffic volume, and could be used as management and design criteria.

Safety Impact of Average Speed Control in the UK

There is considerable safety potential in ensuring that motorists respect the speed limits. High speeds increase the number and severity of accidents. Technological development over the last 20 years has enabled the development of systems that allow automatic speed control. The first generation of automatic speed control was point-based, but in recent years a potentially more effective alternative automatic speed control method has been introduced. This method is based upon records of drivers’ average travel speed over selected sections of the road and is normally called average speed control or section control. This article discusses the different methods for automatic speed control and presents an evaluation of the safety effects of average speed control, documented through changes in speed levels and accidents before and after the implementation of average speed control at selected sites in the UK. The study demonstrates that the introduction of average speed control results in statistically significant and substantial reductions both in speed and in number of accidents. The evaluation indicates that average speed control has a higher safety effect than point-based automatic speed control.

Climbing Lane Level of Service Estimation in Spain

A road in Spain was monitored with cameras with the objective of calibrating the TWOPAS model, which was successfully achieved with the information gathered. The model was also applied for estimating its Level of service, with and without a climbing lane, and for comparing the results with those obtained with the Highway Capacity Manual (HCM) procedure.The basic indicators were Percent Time Spent Following (PTSF) and Average Travel Speed (ATS).As a result, it is concluded that the two procedures show improvements on the climbing lane applicable on the field. However, changes are recommended to improve the estimation

Traffic Flow Quality from the User's Perspective

Achieving the maximum utilization of the existing infrastructure is an essential goal of traffic management for both freeways and the urban road network. Reliable and explicit information about the current traffic condition are required for using the road network efficiently. So far, the lack of a uniform classification scheme results in a time consuming process of coordination between different stakeholders developing and implementing control strategies and providing traffic information. In this study, a uniform concept is developed defining the traffic conditions on freeways and urban roads. This classification scheme is applicable for all stakeholders (e.g. road authorities, broadcasting services, private service providers) and can be used in both infrastructure-based and vehicle-based applications. In order to determine an appropriate traffic flow parameter for a comprehensible representation of the traffic condition, extensive data from freeways and urban roads in Germany were collected and analyzed. The empirical basis is provided by segment-based and local data obtained with different detection methods. As expected, the average speed per segment leads to a more precise description of the traffic condition than local speed values from stationary detectors. Test runs with probe vehicles were made using a GPS tracking device to record the floating car's driving speed. During the test runs, a subjective evaluation of the traffic flow quality was provided by different passengers (probands) in the vehicle. In total, over 15000 sets of travel speed data with associated grading of the experienced traffic flow quality were analyzed to develop a six-step classification scheme. Based on different approaches, threshold values of the average travel speed were determined depending on the type of road and the speed limit. This uniform classification scheme can offer valuable decision guidance for traffic management strategies. For providing more comprehensible traffic information for the road users, the developed scheme was transferred to a three-step system, easily illustrated by the colors green, yellow and red.

Investigation of Automated Vehicle Effects on Driver's Behavior and Traffic Performance

Advanced Driver Assistance Systems (ADAS) offer the possibility of helping drivers to fulfill their driving tasks. Automated vehicles (AV) are capable of communicating with surrounding vehicles (V2V) and infrastructure (V2I) in order to collect and provide essential information about the driving environment. Studies have proved that automated driving have the potential to decrease traffic congestion by reducing the time headway (THW), enhancing the traffic capacity and improving the safety margins in car following. Despite different encouraging factors, automated driving raise some concerns such as possible loss of situation awareness, overreliance on automation and system failure. This paper aims to investigate the effects of AV on driver’s behavior and traffic performance. A literature review was conducted to examine the AV effects on driver’s behavior. Findings from the literature survey reveal that conventional vehicles (CV), i.e. human driven, which are driving close to a platoon of AV with short THW, tend to reduce their THW and spend more time under their critical THW. Additionally, driving highly AV reduce situation awareness and can intensify driver drowsiness, exclusively in light traffic. In order to investigate the influences of AV on traffic performance, a simulation case study consisting of a 100% AV scenario and a 100% CV scenario was performed using microscopic traffic simulation. Outputs of this simulation study reveal that the positive effects of AV on roads are especially highlighted when the network is crowded (e.g. peak hours). This can definitely count as a constructive point for the future of road networks with higher demands. In details, average density of autobahn segment remarkably improved by 8.09% during p.m. peak hours in the AV scenario, while the average travel speed enhanced relatively by 8.48%. As a consequent, the average travel time improved by 9.00% in the AV scenario. The outcome of this study jointly with the previous driving simulator studies illustrates a successful practice of microscopic traffic simulation to investigate the effects of AV. However, further development of the microscopic traffic simulation models are required and further investigations of mixed traffic situation with AV and CV need to be conducted.

Divisive Analysis (DIANA) of hierarchical clustering and GPS data for level of service criteria of urban streets

Level of Service (LOS) for heterogeneous traffic flow on urban streets is not well defined in Indian context. Hence in this study an attempt is taken to classify urban road networks into number of street classes and average travel speeds on street segments into LOS categories. Divisive Analysis (DIANA) Clustering is used for such classification of large amount of speed data collected using GPS receiver. DIANA algorithm and silhouette validation parameter are used to classify Free Flow Speeds (FFS) into optimal number of classes and the same algorithm is applied on speed data to determine ranges of different LOS categories. Speed ranges for LOS categories (A–F) expressed in percentage of FFS are found to be 90, 70, 50, 40, 25 and 20–25 respectively in the present study. On the other hand, in HCM (2000) it has been mentioned these values are 85 and above, 67–85, 50–67, 40–50, 30–40 and 30 and less percent respectively.

Exploring Trip Fuel Consumption by Machine Learning from GPS and CAN Bus Data

This study aims to explore the trip fuel consumption from a large-scale dataset. To better understand how the multiple variables (e.g., average travel speed, trip distance) influence the trip fuel consumption, we propose the support vector machine (SVM) to learn the relationship between the trip fuel consumption and the corresponding factors. A large-scale global positioning system (GPS) and Controller Area Network (CAN) bus data provided by 153 probe vehicles during one month are used. Elasticity analysis indicates that trip distance and coefficient of variance of link speed have relatively great importance on the SVM model. To demonstrate the performance of the proposed method, three other regression methods, i.e., the multiple linear regression model, artificial neural network (ANN), and the link fuel summation SVM model (LSSVM) are also adopted for performance comparisons. The results show that SVM model is much closer to the target than the other three models.

Analysis of the Effectiveness of Providing National Highway Detour Information via Variable Message Signs on Expressway Operations

PURPOSES : Expressways experience chronic and recurring congestion, especially during weekends and holidays, because of the increased demands for leisure-related travel. The alternatives to solve chronic and recurring congestion may be three-fold: (1) physical expansion of expressway capacities, (2) road pricing, and (3) temporal and spatial distribution of traffic demands. Among these, the third alternative may be the most cost-effective method for the Korea Expressway Corporation (KEC) that can be achieved by using the existing ITS infrastructure. METHODS : KEC initiated a pilot study in which the traffic on congested expressways was managed by providing traffic condition information (i.e., travel times) of neighboring national highways for taking detours via variable message signs (VMS). This study aimed to estimate the detour rate, and the two pilot studies on Seohaean and Yeongdong expressways yielded many benefits. RESULTS : It was revealed that the total length of congestion segments decreased by 7.8 km, and the average travel speed increased by 5.3 km/h. CONCLUSIONS : Based on these findings, it was concluded that the propagation of detour information via VMSs during congestion hours can help reduce congestion on expressways and increase the benefits of the entire network.

Application of genetic programming clustering in defining LOS criteria of urban street in Indian context

India is a highly populated country having second largest road network in the world. Owing to boastfully population, the congestion is growing rapidly on the urban road networks. The level of service (LOS) is not substantially defined for heterogeneous traffic flow with different operational characteristics. Defining LOS is essentially a classification problem. The application of cluster analysis is the worthiest proficiency to solve such problem for which genetic programming (GP) clustering, an evolutionary algorithm is used in this study. Five cluster validation parameters are utilized to examine the optimal number of clusters. The cluster validation parameters are used to obtain the number of categories of urban street classes. After acquiring optimal number of clusters, GP clustering is implemented to the free flow speed (FFS) data to get ranges of different urban street classes. Again, GP clustering is enforced on average travel speeds of street segments to specify the ranges of different LOS categories. Speed data used in this study are collected using Trimble GeoXT GPS receivers fitted on mid-sized vehicles for five major urban corridors comprising of 100 street segments of Greater Mumbai region. Result shows that FFS of urban street classes and average travel speed of LOS categories are lower than that mentioned in Highway Capacity Manual (HCM 2000) on account of physical and surrounding environmental characteristics. Also, average travel speed of LOS categories expressed in terms percentage of FFS of urban street classes found to be different from that mentioned in HCM 2010.

Green vehicle traffic routing system using ant-based algorithm

Vehicle traffic congestion leads to air pollution, driver frustration, and costs billions of dollars annually in fuel consumption. Finding a proper solution to vehicle congestion is a considerable challenge due to the dynamic and unpredictable nature of the network topology of vehicular environments, especially in urban areas. Vehicle Traffic Routing Systems (VTRSs) are one of the most significant solutions for this problem. Although most of the existing VTRSs obtained promising results for reducing travel time or improving traffic flow, they cannot guarantee reduction of the traffic-related nuisances such as air pollution, noise, and fuel consumption. Hence, in this paper, we present a green VTRS that reduces fuel consumption and consequently CO2 emissions via ant-based algorithm combined with fuel consumption model. This VTRS is an Ant-based Vehicle Congestion Avoidance System (AVCAS) that uses Signalized Intersection Design and Research Aid (SIDRA) fuel consumption and emission model in its vehicle routing procedure. This approach is called AVCAS+SIDRA which utilizes various criterion such as average travel time, speed, distance, vehicle density along with road map segmentation to reduce fuel consumption as much as possible by finding the least congested shortest paths in order to reduce the vehicle traffic congestion and their pollutant emissions. The proposed approach is evaluated and validated through simulation environment and tools (i.e. NS-2, SUMO, TraNS). Experimental results conducted on three different scenarios (i.e. various vehicle densities, system usage rates and accident condition) considering average travel time, travel speed, travel distance and fuel consumption as evaluation metrics. The obtained results show that the AVCAS+SIDRA outperforms the existing approaches in terms of average travel time, average travel speed and fuel consumption rate, by an average of 25.5%, 19.5% and 17%, respectively. Consequently, our proposed green VTRS alleviates energy consumption as it is not only becoming scarce and expensive but also causing a dramatic climate change and emission.

Speed pattern recognition technique for short‐term traffic forecasting based on traffic dynamics

This study introduces a new short-term traffic forecasting technique, based on the dynamic features of traffic data derived from vehicles moving in urban networks. The authors goal is to forecast the values of appropriate traffic status indicators such as average travel time or speed, for one or more time steps in the future until the next half hour. The proposed forecasting technique is based on road profiles generated from the application of data clustering techniques on real traffic data. Data clustering is applied after the original feature space is transformed to a new one of a significantly lower dimension. This transformation is based on the dynamic characteristics of current traffic, expressed in the form of the speed derivatives. To evaluate the proposed technique they used two-week historical data from the city of Berlin, Germany. Extensive evaluation results indicate improvement of the forecasting accuracy after comparison with a set of existing traffic forecasting techniques.

자유류 상태에서 고속도로 구간과속단속구간 및 대조구간 간의 교통류 특성 비교

무인과속단속시스템은 속도위반 차량을 효과적으로 단속하기 위해 도입되었으나, 기존의 지점 과속단속시스템의 경우 차량 내비게이션, 스마트폰 등을 통해 제공되는 위치정보 서비스로 인해 단속 효과가 현격히 낮아지게 되었다. 구간 과속단속시스템은 지점 과속단속카메라 설치 지점에서 나타나는 카메라 전후에서 급감속 및 재가속을 반복하는 회피 거동으로 인한 여러 가지 부정적인 문제점을 보완하기 위해 도입되어 설치를 확대해 나가고 있다. 이에 본 연구에서는, 국내 고속도로 상에 설치된 구간 과속단속시스템에서 나타나는 교통류 특성에 대해 대조 구간을 설정하여 비교 분석하였다. 이를 위해 구간의 특성 등을 고려하여, 중부내륙선, 대전-통영선, 영동선 내의 구간 과속단속 시행구간에 대해 VDS 검지기 데이터를 수집하였으며, 데이터필터링을 통해 비교분석에 용이한 조건을 설정하고 자유속도 상태에서의 교통류 특성을 분석하였다. 분석결과, 구간 과속단속구간 내에서는 대조 구간에 비해 속도 평균 및 속도 분산이 낮아지는 경향을 보였으며, 통계적 검정 방법을 이용하여 이를 확인하였다. The Korean government introduced an automated speed enforcement system (ASES), which uses traffic enforcement cameras, to counteract safety issues that are caused by speeding. As the information of the traffic enforcement camera locations is provided to the drivers via navigation systems and mobile applications in a timely manner, drivers can avoid enforcement by momentarily diminishing their speeds only near the camera locations. To prevent drivers' evasional behavior and improve the effectiveness of ASES, section control, which enforces speeding vehicles by measuring their average travel speeds over a stretch of road and checking against the speed limit, has been recently implemented. In this study, Section Speed Enforcement Zone and Comparison Zone are compared in terms of traffic stream characteristics under free flow conditions. To this end, loop detector data were obtained from the three study sites and analyzed. The study results demonstrated that drivers maintain their speeds below the speed limit over the enforcement section with a lower variance of speeds.

Predictability of road traffic and congestion in urban areas.

Mitigating traffic congestion on urban roads, with paramount importance in urban development and reduction of energy consumption and air pollution, depends on our ability to foresee road usage and traffic conditions pertaining to the collective behavior of drivers, raising a significant question: to what degree is road traffic predictable in urban areas? Here we rely on the precise records of daily vehicle mobility based on GPS positioning device installed in taxis to uncover the potential daily predictability of urban traffic patterns. Using the mapping from the degree of congestion on roads into a time series of symbols and measuring its entropy, we find a relatively high daily predictability of traffic conditions despite the absence of any priori knowledge of drivers' origins and destinations and quite different travel patterns between weekdays and weekends. Moreover, we find a counterintuitive dependence of the predictability on travel speed: the road segment associated with intermediate average travel speed is most difficult to be predicted. We also explore the possibility of recovering the traffic condition of an inaccessible segment from its adjacent segments with respect to limited observability. The highly predictable traffic patterns in spite of the heterogeneity of drivers' behaviors and the variability of their origins and destinations enables development of accurate predictive models for eventually devising practical strategies to mitigate urban road congestion.

Point-to-point speed enforcement systems: Speed limits design criteria and analysis of drivers’ compliance

Point-to-point (P2P) speed enforcement is a relatively new approach to traffic law enforcement. Its technology allows vehicles whose average speed exceeds the speed limit over the controlled section to be fined. It therefore encourages compliance over distances longer than those where spot enforcement policies have been in place.In this paper, a procedure for consistently setting speed limits with such enforcement systems is proposed. Such a method has been applied to design the speed limits on two motorways in the district of Naples, Italy, where P2P enforcement systems became operational in 2009 and 2010. The speed limits, which were set using the Italian geometric design standard to assess vehicle stability and stopping sight distance, have been compared with those provided by using well-known international standards.The impact of the newly designed speed limits and of the P2P enforcement system on drivers’ speeding behaviour has been quantified for each highway section and vehicle type. In fact, accurate measurements of the average travel speeds of each vehicle crossing the enforced sections, before and after the activation of the system, were available. The migration from the old speed limits with spot speed enforcement to the new approach resulted in a notable increase in drivers’ compliance to the speed limits with a remarkable decrease in both the average of individual speeds and in their standard deviation.In addition, the analysis of 3years of data shows that a gradual adaptation of drivers’ behaviour to the system took place. In particular, a decreasing compliance to the speed limits points to a non-optimal system management. Finally, the results of a revealed preference survey allowed us to make a behavioural interpretation regarding the significantly different impacts measured on the two motorways.

Effects of number of animals monitored on representations of cattle group movement characteristics and spatial occupancy.

The number of animals required to represent the collective characteristics of a group remains a concern in animal movement monitoring with GPS. Monitoring a subset of animals from a group instead of all animals can reduce costs and labor; however, incomplete data may cause information losses and inaccuracy in subsequent data analyses. In cattle studies, little work has been conducted to determine the number of cattle within a group needed to be instrumented considering subsequent analyses. Two different groups of cattle (a mixed group of 24 beef cows and heifers, and another group of 8 beef cows) were monitored with GPS collars at 4 min intervals on intensively managed pastures and corn residue fields in 2011. The effects of subset group size on cattle movement characterization and spatial occupancy analysis were evaluated by comparing the results between subset groups and the entire group for a variety of summarization parameters. As expected, more animals yield better results for all parameters. Results show the average group travel speed and daily travel distances are overestimated as subset group size decreases, while the average group radius is underestimated. Accuracy of group centroid locations and group radii are improved linearly as subset group size increases. A kernel density estimation was performed to quantify the spatial occupancy by cattle via GPS location data. Results show animals among the group had high similarity of spatial occupancy. Decisions regarding choosing an appropriate subset group size for monitoring depend on the specific use of data for subsequent analysis: a small subset group may be adequate for identifying areas visited by cattle; larger subset group size (e.g. subset group containing more than 75% of animals) is recommended to achieve better accuracy of group movement characteristics and spatial occupancy for the use of correlating cattle locations with other environmental factors.

EVALUATION OF SPEED–FLOW CHARACTERISTICS ON TWO-LANE HIGHWAYS WITH MIXED TRAFFIC

The HCM (Highway Capacity Manual 2010) classifies two-lane rural highway that passes through developed areas as ‘Class III’ and suggests using Percent Free-Flow Speed (PFFS) as performance measure to define Level Of Service (LOS). Apparently, this performance measure addresses the main limitation associated with using Average Travel Speed (ATS) as a measure of performance. However, larger speed differential under heterogeneous traffic causes error in estimating Free-Flow Speed (FFS) and thus affects PFFS. This implication was examined in the present study using field data collected on a national highway approaching a city. Speed–flow equations were developed and intercept values were compared to the FFS obtained according to HCM guidelines. Comparison confirms a very close agreement between average FFS value and those obtained for different types of vehicle separately except for car. This consequently causes an error in estimating PFFS since the traffic composition consists of significant proportion of car. The possible capacity of the highway section was observed to be around 2300 pc/h for mixed traffic situation.

Methodology to Compute Travel Time of a Roundabout Corridor

Urban and suburban arterials with roundabouts in series are becoming more prevalent in North America. While the Highway Capacity Manual (HCM) provides a methodology for computing segment travel time of urban streets with various forms of intersection control, the manual does not provide a similar procedure for corridors with interdependent roundabouts. Such a methodology is necessary to evaluate performance of roundabout corridors and will allow the practitioner to compare both roundabout and signalized treatments for the same series of intersections. This paper presents a series of models intended to predict arterial travel time for a corridor with roundabouts, including a model for free-flow speed (FFS), a model to predict the length of the roundabout influence area (RIA, the area where geometric delay has incurred), a model for geometric delay, and models for impeded delay and average travel speed. These models were calibrated with data from seven roundabout corridors. The resulting models suggest that while FFS is a function of segment length, posted speed limit, and central island diameter, RIA length and geometric delay are functions of the FFS itself, as well as other geometric elements. The impeded delay and average travel speed are functions of traffic congestion and FFS. After validating the models with travel time data from two additional roundabout corridors not used in model development, the authors present a framework for incorporating the procedure for travel time prediction into the HCM analysis of urban streets.