scholarly journals Self-Organizing Tree Algorithm (SOTA) Clustering for Defining Level of Service (LOS) Criteria of Urban Streets

2018 ◽  
Vol 47 (4) ◽  
pp. 309-317
Author(s):  
Amit Kumar Das ◽  
Prasanta Kumar Bhuyan
Keyword(s):  
Travel Speed ◽  
Flow Speed ◽  
Free Flow ◽  
Level Of Service ◽  
Highway Capacity ◽  
Tree Algorithm ◽  
Highway Capacity Manual ◽  
Urban Streets ◽  
Flow Speeds ◽  
Self Organizing

This study is intended to define the Free Flow Speed (FFS) ranges of urban street classes and speed ranges of Level of Service (LOS) categories. In order to accomplish the study FFS data and average travel speed data were collected on five urban road corridors in the city of Mumbai, India. Mid-sized vehicle (car) mounted with Global Positioning System (GPS) device was used for the collection of large number of speed data. Self-Organizing Tree Algorithm (SOTA) clustering method and five cluster validation measures were used to classify the urban streets and LOS categories. The above study divulges that the speed ranges for different LOS categories are lower than that suggested by Highway Capacity Manual (HCM) 2000. Also it has been observed that average travel speed of LOS categories expressed in percentage of free flow speeds closely resembles the percentages mentioned in HCM 2010.

scholarly journals Travel Time Estimation on Urban Street Segment

2018 ◽  
Vol 30 (1) ◽  
pp. 115-120 ◽  
Author(s):  
Jelena Kajalić ◽  
Nikola Čelar ◽  
Stamenka Stanković
Keyword(s):  
Travel Time ◽  
Time Estimation ◽  
Travel Speed ◽  
Degree Of Saturation ◽  
Level Of Service ◽  
Travel Time Estimation ◽  
Highway Capacity ◽  
Local Conditions ◽  
Highway Capacity Manual ◽  
Urban Streets

Level of service (LOS) is used as the main indicator of transport quality on urban roads and it is estimated based on the travel speed. The main objective of this study is to determine which of the existing models for travel speed calculation is most suitable for local conditions. The study uses actual data gathered in travel time survey on urban streets, recorded by applying second by second GPS data. The survey is limited to traffic flow in saturated conditions. The RMSE method (Root Mean Square Error) is used for research results comparison with relevant models: Akcelik, HCM (Highway Capacity Manual), Singapore model and modified BPR (the Bureau of Public Roads) function (Dowling - Skabardonis). The lowest deviation in local conditions for urban streets with standardized intersection distance (400-500 m) is demonstrated by Akcelik model. However, for streets with lower signal density (<1 signal/km) the correlation between speed and degree of saturation is best presented by HCM and Singapore model. According to test results, Akcelik model was adopted for travel speed estimation which can be the basis for determining the level of service in urban streets with standardized intersection distance and coordinated signal timing under local conditions.

Application of Moving Car Observer Method for Measuring Free Flow Speed on Two-lane Highways

2014 ◽  
Vol 69 (6) ◽  
Author(s):  
Othman Che Puan ◽  
Muttaka Na’iya Ibrahim ◽  
Usman Tasiu Abdurrahman
Keyword(s):  
Field Measurement ◽  
Flow Speed ◽  
Operating Conditions ◽  
Free Flow ◽  
Geometric Features ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Free Flow Speed ◽  
The Subject ◽  
Low Traffic

There exists a need to evaluate the performance indicator that reflects the current level of service (LOS) of the subject facility to justify any decision making on expenditures to be made for improving the performance level of a road facility. Free-flow speed (FFS) is one of the key parameters associated with LOS assessment for two-lane highways. Application of a more realistic approach for assessing road’s performance indicators would result in better estimates which could in turn suggest the most appropriate decision to be made (for situations where upgrading is needed); especially, in terms of finance, materials and human resources. FFS is the driver’s desired speed at low traffic volume condition and in the absence of traffic control devices. Its estimation is significant in the analysis of two-lane highways through which average travel speed (ATS); an LOS indicator for the subject road class is determined. The Highway Capacity Manual (HCM) 2010 offers an indirect method for field estimation of FSS based on the highway operating conditions in terms of base-free-flow-speed (BFFS). It is however, recommended by the same manual that direct field FSS measurement approach is most preferred. The Malaysian Highway Capacity Manual (MHCM) established a model for estimating FFS based on BFFS, the geometric features of the highway and proportion of motorcycles in the traffic stream. Estimating FFS based on BFFS is regarded as an indirect approach which is only resorted to, if direct field measurement proved difficult or not feasible. This paper presents the application of moving car observer (MCO) method for direct field measurement of FFS. Data for the study were collected on six segments of two-lane highways with varying geometric features. FFS estimates from MCO method were compared with those based on MHCM model. Findings from the study revealed that FFS values from MCO method seem to be consistently lower than those based on MHCM model. To ascertain the extent of the difference between the FFS values from the two approaches, student t-statistics was used. The t-statistics revealed a P–value of less than 0.05 (P < 0.05) which implies that there is a statistically significant difference between the two sets of data. Since MCO method was conducted under low traffic flow (most desired condition for field observation), it can be suggested that MCO estimates of FFS represent the actual scenario. A relationship was therefore developed between the estimates from the two methods. Thus, if the MHCM model is to be applied, the measured value needs to be adjusted based on the relationship developed between the two approaches.

Uncertainty in Operational Analysis of Two-Lane Highways

2002 ◽  
Vol 1802 (1) ◽  
pp. 105-114 ◽  
Author(s):  
R. Tapio Luttinen
Keyword(s):  
Input Data ◽  
Travel Speed ◽  
Level Of Service ◽  
Model Parameters ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Operational Analysis ◽  
Percent Time ◽  
Different Types ◽  
Percent Time Spent Following

The Highway Capacity Manual (HCM) 2000 provides methods to estimate performance measures and the level of service for different types of traffic facilities. Because neither the input data nor the model parameters are totally accurate, there is an element of uncertainty in the results. An analytical method was used to estimate the uncertainty in the service measures of two-lane highways. The input data and the model parameters were considered as random variables. The propagation of error through the arithmetic operations in the HCM 2000 methodology was estimated. Finally, the uncertainty in the average travel speed and percent time spent following was analyzed, and four approaches were considered to deal with uncertainty in the level of service.

scholarly journals AFFINITY PROPAGATION CLUSTERING IN DEFINING LEVEL OF SERVICE CRITERIA OF URBAN STREETS

Transport ◽  
2014 ◽  
Vol 29 (4) ◽  
pp. 401-411 ◽  
Author(s):  
Prasanta Kumar Bhuyan ◽  
Smruti Sourava Mohapatra
Keyword(s):  
Traffic Flow ◽  
Heterogeneous Traffic ◽  
Level Of Service ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Urban Streets ◽  
Urban Street ◽  
Indian Context ◽  
Validation Parameters ◽  
Street Segments

Defining Level Of Service (LOS) criteria is very important as this is the first step of LOS analysis but this is not well defined in Indian context. The analysis followed in India is basically adaptation of Highway Capacity Manual (HCM 2000) methodology which is more suitable for developed countries having homogenous traffic pattern. An attempt has been made in this study to define LOS criteria of urban streets for developing countries having heterogeneous traffic flow condition. Defining LOS is basically a classification problem and to solve it Affinity Propagation (AP), a very recently developed cluster algorithm is used. Inventory details and the required speed data are collected from five major street corridors of Greater Mumbai Region in India through the application of Trimble GeoXT Global Positioning System (GPS) receiver. Six validation parameters are used on Free Flow Speed (FFS) data to find the optimal number of clusters, which is required for the classification of street segments into number of classes. After that speed data collected during both peak and off-peak hours are averaged over street segments and clustered into six groups to get the speed ranges of different LOS categories. Using validation parameters, considering the physical and surrounding environmental characteristics it is found that street segments can be classified into four classes in Indian context as mentioned in Highway Capacity Manual 2000. However, the FFS range for urban street class IV (urban design category) is significantly lower because of varying road geometric characteristics. The speed ranges of LOS categories under urban street classes are proportionately lower to that values mentioned in HCM 2000 because of highly heterogeneous traffic flow on urban Indian roads. The travel speed data collection procedure using GPS is simple and accurate. In addition, AP clustering is highly efficient in terms of time saving and provides a very accurate solution to classification problems. Hence, both GPS and AP techniques can be applied in other countries to define the speed ranges of LOS categories considering the local conditions.

Field Measurement of Signalized Intersection Delay for 1997 Update of the Highway Capacity Manual

1998 ◽  
Vol 1646 (1) ◽  
pp. 79-86 ◽  
Author(s):  
James L. Powell
Keyword(s):  
Field Measurement ◽  
Flow Speed ◽  
Signalized Intersection ◽  
Volume Control ◽  
Level Of Service ◽  
Highway Capacity ◽  
Total Delay ◽  
Highway Capacity Manual ◽  
Measuring Field ◽  
Vehicle Deceleration

The 1997 update of the Highway Capacity Manual changes the basis of delay for level-of-service determination at signalized intersections from stopped delay to conceptually more appealing total delay. Total delay is made up of components including volume, control, and geometric delay. Level of service is now defined in terms of control delay, which provides a more stable and tractable relation to total delay, but the issue of field measurement remains in any case. A combined theoretical and empirical approach to measuring field delay on the basis of typical vehicle deceleration and acceleration profiles is taken in this paper. The profiles are related to the relatively easily surveyed quantity of vehicles in queue, which is equivalent to estimating time in queue of all vehicles stopped by the traffic signal. The results indicate that after vehicles in queue are sampled, correction factors can account, in practical terms, for the unsurveyed deceleration and acceleration delay. The corrections are simple additive factors that are a function of free-flow speed and average number of vehicles stopped in queue. Another adjustment is included for the consistent tendency of human observers to overestimate vehicles in queue. All of these factors are included in the new 1997 HCM procedure for measuring signalized intersection delay in the field. Further identified work includes the need to fully develop the total delay concept to account for geometric delay consistently over a variety of interrupted- and uninterrupted-flow facilities. Such resolution should be included in HCM 2000 preparation currently in progress.

Proposed Framework for Evaluating Spillback in the Highway Capacity Manual

2017 ◽  
Vol 2615 (1) ◽  
pp. 148-158
Author(s):  
Yinan Zheng ◽  
Michael Armstrong ◽  
Gustavo de Andrade ◽  
Lily Elefteriadou
Keyword(s):  
Signalized Intersection ◽  
Level Of Service ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Urban Streets ◽  
Facility Type ◽  
Street Intersection ◽  
Lane Utilization ◽  
New Procedures ◽  
Data Collection Effort

Procedures detailed in the Highway Capacity Manual 2010 (HCM 2010) estimate capacity and several operational measures dictating level of service for freeway facilities and surface streets. However, these methods do not consider cases in which spillback occurs from one facility type to another. The queuing effects in oversaturated conditions as they propagate upstream onto a freeway main line or a surface street intersection are not accounted for. The objective of this paper is to propose a series of modifications to enhance the HCM 2010 methods to address spillback conditions. These modifications consider lane utilization and lane blockage under spillback conditions and consist of restructuring existing equations and reference tables as well as developing new procedures. A four-regime method is proposed for evaluating spillback effects from urban streets to diverge and weaving segments. In addition, a method is proposed to account for the spillback effects from freeway on-ramps by reducing the effective green time as a proportion of the percent of time that the queue is expected to block the upstream signalized intersection. The framework developed uses assumptions that should be further explored through an extensive, nationwide data collection effort.

Predicting Lane-by-Lane Flows and Speeds for Freeway Segments

2020 ◽  
Vol 2674 (9) ◽  
pp. 1052-1068
Author(s):  
Fabio Sasahara ◽  
Luan Guilherme Staichak Carvalho ◽  
Tanay Datta Chowdhury ◽  
Zachary Jerome ◽  
Lily Elefteriadou ◽  
...  
Keyword(s):  
Field Data ◽  
Performance Estimation ◽  
Free Flow ◽  
Highway Capacity ◽  
Distribution Models ◽  
Highway Capacity Manual ◽  
Speed Flow ◽  
Flow Speeds ◽  
The Relationship

The Highway Capacity Manual is a major reference for evaluating the capacity and quality of service of road facilities. However, it holds the assumption that lanes perform equally, which can result in inaccuracies in performance estimation. The main purpose of this research is to develop a series of models for estimating flows and speeds by lane for various types of freeway segments, including basic, merge, and diverge types. These models consider the demand-to-capacity ratio, the presence of trucks, grade, and the presence of upstream and downstream ramps. To predict lane performance effectively, it is critical that capacity and free-flow speeds are also determined for individual lanes. Therefore, this study also investigates the relationship between segment average values and lane values for free-flow speeds and capacities, and proposes a method to estimate these parameters for each lane as a function of the segment average. Observed field data has shown that free-flow speeds and capacities have lowest values on the shoulder lanes and highest values on the median lanes. Speed and flow data were collected from 48 segments throughout the U.S.A., including basic, merge, and diverge segments, to develop flow and speed distribution models. A case example is provided to illustrate the application of the developed model and the predicted speed–flow relationship is compared with field data, with satisfactory results.

Driver Assessment of Service Quality on Urban Streets

2005 ◽  
Vol 1920 (1) ◽  
pp. 25-31 ◽  
Author(s):  
Aimee Flannery ◽  
Kathryn Wochinger ◽  
Angela Martin
Keyword(s):  
Service Quality ◽  
Travel Speed ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Urban Streets ◽  
Urban Street ◽  
Lane Width ◽  
Travel Efficiency ◽  
Design Characteristics

This paper presents the results of a study that compared drivers’ assessments of the performance of urban streets with objective measures of performance, including level of service (LOS). The purpose of the study was to test the ability of LOS to predict drivers’ perceptions of service quality. Seventy-seven automobile drivers rated the service quality of half-mile segments of urban streets as depicted on videotaped scenes from the driver's perspective. Drivers rated 12 to 15 video segments on a six-point scale from very satisfactory to very unsatisfactory. After rating all segments, the drivers selected and ranked from a list of 36 factors the three factors that they considered the most important to quality. The results show that the mean driver rating had statistically significant correlations with operational and design characteristics and aesthetics, including the following variables: travel time, average travel speed, number of stops, delay, number of signals, lane width, the presence of trees, and the quality of the landscaping. LOS, calculated by the Highway Capacity Manual methodology, predicted 35% of the variance in mean driver rating. This finding suggests that LOS does not completely represent drivers’ assessments of performance because drivers perceive the quality of urban street segments in several dimensions, including travel efficiency, sense of safety, and aesthetics.

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