Real-Time Inductive-Signature-Based Level of Service for Signalized Intersections

The Highway Capacity Manual (HCM) presents a procedure for estimating signalized intersection control delay, which is used to determine level of service (LOS) and to evaluate intersection performance. The HCM is used extensively by traffic engineers. However, it is intended as an offline decision support tool for planning and design. To meet user requirements of advanced traffic management and information systems, new LOS criteria are required for real-time intersection analysis. The objective of this research was to demonstrate a technique for development of such LOS criteria. The study used a new measure of effectiveness, called reidentification delay (RD), derived from analysis of vehicle inductive signatures and reidentification of vehicles traveling through a major signalized intersection in the city of Irvine, California. Two main issues regarding real-time LOS criteria were tackled. The first was how to determine the threshold values partitioning the LOS categories. To provide reliable real-time traffic information, the threshold values should be decided on so that RDs within the same LOS category would represent similar traffic conditions as much as possible. RDs in different LOS categories should also represent dissimilar traffic conditions. The second issue concerned the aggregation interval to use for RD in deriving LOS categories. An investigation of both fixed and cycle-based aggregation intervals was conducted. Several clustering techniques were then employed to derive LOS categories, including k-means, fuzzy, and self-organizing map approaches. The resulting real-time LOS criteria were then determined. The procedures used in this study are readily transferable to other signalized intersections for the derivation of real-time LOS.

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Modeling Pedestrian Level of Service at Signalized Intersection Under Mixed Traffic Conditions

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/2634-13 ◽

2017 ◽

Vol 2634 (1) ◽

pp. 86-94 ◽

Cited By ~ 12

Author(s):

S. Marisamynathan ◽

P. Vedagiri

Keyword(s):

Linear Regression ◽

Signalized Intersections ◽

Level Of Service ◽

Delay Model ◽

Mixed Traffic ◽

Threshold Values ◽

User Perceptions ◽

Traffic Conditions ◽

Fcm Clustering ◽

Pedestrian Level Of Service

Developing countries such as India need to have the proper pedestrian level of service (PLOS) criteria for various facilities to help in planning, designing, and maintaining pedestrian facilities. Thus, the objective of this study was to develop a suitable method for estimating the PLOS model under mixed traffic conditions and also to define threshold values for PLOS classification at signalized intersections. First, the data were collected with video and a user perceptions survey at eight selected signalized intersections in Mumbai, India. Second, pedestrian crossing behaviors were modeled according to arrival pattern, crossing speed, noncompliance behavior, and pedestrian–vehicular interaction. Third, a pedestrian delay model was proposed by considering crossing behavior variations and subsequent validation with field data. Fourth, significant variables were identified on the basis of the Pearson’s correlation test with user’s perceptions score. Fifth, the conventional linear regression (CLR) technique was explored to determine the PLOS. To overcome the limitations of the CLR technique, fuzzy linear regression (FLR) was done to develop a PLOS model that fits mixed traffic conditions in India. Two models were validated, and their statistical performance results indicate that the FLR model predicts the PLOS score more precisely. Finally, k-means and fuzzy C-means (FCM) clustering techniques were applied to classify the PLOS score, and the results were compared by time complexity value and field values. The performance evaluation results indicate that the k-means method saves time but fails to produce more reliable threshold values, and the FCM method produces more accurate and efficient threshold values for the PLOS score at signalized intersections under mixed traffic conditions.

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Delay Variability at Signalized Intersections

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/1710-25 ◽

2000 ◽

Vol 1710 (1) ◽

pp. 215-221 ◽

Cited By ~ 33

Author(s):

Liping Fu ◽

Bruce Hellinga

Keyword(s):

Analytical Model ◽

Signalized Intersections ◽

Signalized Intersection ◽

Level Of Service ◽

Cycle Times ◽

Traffic Conditions ◽

Cycle Simulation ◽

Proposed Model ◽

Delay Variability ◽

Practical Implications

Delays that individual vehicles may experience at a signalized intersection are usually subject to large variation because of the randomness of traffic arrivals and interruption caused by traffic signal controls. Although such variation may have important implications for the planning, design, and analysis of signal controls, currently no analytical model is available to quantify it. The development of an analytical model for predicting the variance of overall delay is described. The model is constructed on the basis of the delay evolution patterns under two extreme traffic conditions: highly undersaturated and highly oversaturated conditions. A discrete cycle-by-cycle simulation model is used to generate data for calibrating and validating the proposed model. The practical implications of the model are demonstrated through its use in determining optimal cycle times with respect to delay variability and in assessing level of service according to the percentiles of overall delay.

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Mobile Road Traffic Management System Using Weighted Sensor

International Journal of Interactive Mobile Technologies (iJIM) ◽

10.3991/ijim.v11i5.6745 ◽

2017 ◽

Vol 11 (5) ◽

pp. 147 ◽

Cited By ~ 2

Author(s):

Solomon Adegbenro Akinboro ◽

Johnson A Adeyiga ◽

Adebayo Omotosho ◽

Akinwale O Akinwumi

Keyword(s):

Real Time ◽

Traffic Control ◽

Urban Areas ◽

Traffic Management ◽

Management System ◽

Road Traffic ◽

Traffic Information ◽

Traffic Light ◽

Real Time Traffic ◽

Traffic Management System

Vehicular traffic is continuously increasing around the world, especially in urban areas, and the resulting congestion has become a major concern to automobile users. The popular static electric traffic light controlling system can no longer sufficiently manage the traffic volume in large cities where real time traffic control is paramount to deciding best route. The proposed mobile traffic management system provides users with traffic information on congested roads using weighted sensors. A prototype of the system was implemented using Java SE Development Kit 8 and Google map. The model was simulated and the performance was assessed using response time, delay and throughput. Results showed that, mobile devices are capable of assisting road users’ in faster decision making by providing real-time traffic information and recommending alternative routes.

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Sistem Pengamatan Kondisi Lalu Lintas Berbasis Data GPS pada Smartphone (Studi Kasus : Kota Denpasar)

Jurnal Teknologi Informasi dan Ilmu Komputer ◽

10.25126/jtiik.2020741909 ◽

2020 ◽

Vol 7 (4) ◽

pp. 667

Author(s):

Gede Herdian Setiawan ◽

I Ketut Dedy Suryawan

Keyword(s):

Real Time ◽

Traffic Congestion ◽

Data Retrieval ◽

Traffic Information ◽

Vehicle Speed ◽

Observation Model ◽

Economic Activities ◽

Traffic Condition ◽

Traffic Conditions ◽

Real Time Traffic

Pertumbuhan jumlah kendaraan yang semakin meningkat setiap tahunnya mengakibatkan volume kendaraan yang melintasi ruas jalan semakin padat yang kerap mengakibatkan kemacetan lalu lintas. Kemacetan lalu lintas dapat menjadi beban biaya yang signifikan terhadap kegiatan ekonomi masyarakat. Informasi lalu lintas yang dinamis seperti informasi kondisi lalu lintas secara langsung (real time) akan membantu mempengaruhi aktivitas masyarakat pengguna lalu lintas untuk melakukan perencanaan dan penjadwalan aktivitas yang lebih baik. Penelitian ini mengusulkan model pengamatan kondisi lalu lintas berbasis data GPS pada smartphone, untuk informasi kondisi lalu lintas secara langsung. GPS Receiver pada smartphone menghasilkan data lokasi secara instan dan bersifat mobile sehingga dapat digunakan untuk pengambilan data kecepatan kendaraan secara langsung. Kecepatan kendaraan diperoleh berdasarkan jarak perpindahan koordinat kendaraan dalam satuan detik selanjutnya di konversi menjadi satuan kecepatan (km/jam) kemudian data kecepatan kendaraan di proses menjadi informasi kondisi lalu lintas. Secara menyeluruh model pengamatan berfokus pada tiga tahapan, yaitu akuisisi data kecepatan kendaraan berbasis GPS pada smartphone, pengiriman data kecepatan dan visualisasi kondisi lalu lintas berbasis GIS. Pengujian dilakukan pada ruas jalan kota Denpasar telah mampu mendapatkan data kecepatan kendaraan dan mampu menunjukkan kondisi lalu lintas secara langsung dengan empat kategori keadaan lalu lintas yaitu garis berwarna hitam menunjukkan lalu lintas macet dengan kecepatan kendaraan kurang dari 17 km/jam, merah menunjukkan padat dengan kecepatan kendaraan 17 km/jam sampai 27 km/jam, kuning menunjukkan sedang dengan kecepatan kendaraan 26 km/jam sampai 40 km/jam dan hijau menunjukkan lancar dengan kecepatan kendaraan diatas 40 km/jam. AbstractThe growth in the number of vehicles that is increasing every year has resulted in the volume of vehicles crossing the road increasingly congested which often results in traffic congestion. Traffic congestion can be a significant cost burden on economic activities. Dynamic traffic information such as information on real time traffic conditions will help influence the activities of the traffic user community to better plan and schedule activities. This study proposes a traffic condition observation model based on GPS data on smartphones, for information on real time traffic conditions. The GPS Receiver on the smartphone produces location and coordinate data instantly and is mobile so that it can be used for direct vehicle speed data retrieval. Vehicle speed is obtained based on the displacement distance of the vehicle's coordinates in units of seconds and then converted into units of speed (km / h), the vehicle speed data is then processed into information on traffic conditions. Overall, the observation model focuses on three stages, namely GPS-based vehicle speed data acquisition on smartphones, speed data delivery and visualization of GIS-based traffic conditions. Tests carried out on the Denpasar city road segment have been able to obtain vehicle speed data and are able to show traffic conditions directly with four categories of traffic conditions, namely black lines indicating traffic jammed with vehicle speeds of less than 17 km / h, red indicates heavy with speed vehicles 17 to 27 km / h, yellow indicates medium speed with vehicles 26 km/h to 40 km / h and green shows fluent with vehicle speeds above 40 km / h.

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Driver Acceptance of Unreliable Route Guidance Information

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/154193129403801615 ◽

1994 ◽

Vol 38 (16) ◽

pp. 1062-1066 ◽

Cited By ~ 7

Author(s):

Richard J. Hanowski ◽

Susan C. Kantowitz ◽

Barry H. Kantowitz

Keyword(s):

Real Time ◽

Heavy Traffic ◽

Traffic Information ◽

Route Guidance ◽

Experimental Conditions ◽

Traveler Information ◽

Traveler Information Systems ◽

Traffic Conditions ◽

Driver Acceptance ◽

Real Time Information

Human factors research can be used to design safe and efficient Advanced Traveler Information Systems (ATIS) that are easy to use (Kantowitz, Becker, & Barlow, 1993). This research used the Battelle Route Guidance Simulator (RGS) to examine two important issues related to driver behavior and acceptance of ATIS technology: (1) the effect of route familiarity on ATIS use and acceptance and (2) the level of information accuracy needed for an ATIS to be accepted and considered useful. The RGS included two 486 computers that provided drivers with real-time information and traffic reports. Drivers used a touch screen to select routes on one computer monitor and watched the results of their selection (i.e., real-time video of the traffic) on a second computer monitor. Drivers could use the system to obtain information about the traffic conditions on any link before traversing a route. In this experiment, subjects were exposed to four experimental conditions involving manipulation of the driver's familiarity with the route and the reliability of the traffic information obtained from the RGS (i.e., 100%, 71%, and 43% accuracy). The driver's goal was to reach the destination as quickly as possible by avoiding heavy traffic. The results indicated that drivers were able to benefit from system information when it was reliable, but not when it was unreliable. Trust ratings for the 43% accuracy group were significantly higher at the beginning of the four trials than at the end. Also, drivers were more apt to rely on the ATIS and accept information given in an unfamiliar traffic network versus a familiar one.

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Macroscopic Traffic State Estimation: Understanding Traffic Sensing Data-Based Estimation Errors

Journal of Advanced Transportation ◽

10.1155/2017/5730648 ◽

2017 ◽

Vol 2017 ◽

pp. 1-11 ◽

Cited By ~ 1

Author(s):

Paul B. C. van Erp ◽

Victor L. Knoop ◽

Serge P. Hoogendoorn

Keyword(s):

State Estimation ◽

Traffic Management ◽

Estimation Error ◽

Ground Truth ◽

Traffic Information ◽

Estimation Errors ◽

Sensing Data ◽

Traffic Conditions ◽

Traffic State ◽

Traffic State Estimation

Traffic state estimation is a crucial element in traffic management systems and in providing traffic information to road users. In this article, we evaluate traffic sensing data-based estimation error characteristics in macroscopic traffic state estimation. We consider two types of sensing data, that is, loop-detector data and probe speed data. These data are used to estimate the mean speed in a discrete space-time mesh. We assume that there are no errors in the sensing data. This allows us to study the errors resulting from the differences in characteristics between the sensing data and desired estimate together with the incomplete description of the relation between the two. The aim of the study is to evaluate the dependency of this estimation error on the traffic conditions and sensing data characteristics. For this purpose, we use microscopic traffic simulation, where we compare the estimates with the ground truth using Edie’s definitions. The study exposes a relation between the error distribution characteristics and traffic conditions. Furthermore, we find that it is important to account for the correlation between individual probe data-based estimation errors. Knowledge related to these estimation errors contributes to making better use of the available sensing data in traffic state estimation.

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An Improvement of Three Leg Signalized Intersections in Duhok City Kurdistan-Iraq

Academic Journal of Nawroz University ◽

10.25007/ajnu.v7n4a275 ◽

2018 ◽

Vol 7 (4) ◽

pp. 87

Author(s):

Baran R. Omer ◽

Sherzad W. Khalid

Keyword(s):

Cycle Time ◽

Signalized Intersections ◽

Signalized Intersection ◽

Level Of Service ◽

Remarkable Improvement ◽

Iraqi Kurdistan ◽

Length Changes ◽

Time Changes ◽

Geometric Changes ◽

The City

Nowadays, number of cars increases in Iraqi Kurdistan. Duhok is one of the Iraqi Kurdistan cities where an enormous increase in the number of cars and population is noticed during the last decade. Roads were been mended according to the 1970s plans where the city was small and number of cars was few. Although the city geographically is located in a hilly area and between two mountains, mending roads is a problem of area. Roads in the mentioned city are quite busy due to the high number of cars, traffic jams can be noticed in every corner of the city especially in signalized intersections. The level of service (LOS) in most of the signalized intersections is F or E. in order to lower the high (LOS), a three leg signalized intersection has been chosen to do an improvement on. During the study the number of the cars (Volume) have been enumerated in all lane groups and the results showed that the (LOS) was E in the intersection. As a result, some solutions have been provided according to the site area and the traffic flow. Solutions were geometric changes, cycle time changes or combination in both geometric and cycle time changes. According to the collected data, it was found that level of service was E for WB and SB and for EB was D. Based on data analysis it was found that LOS has not been improved when only one of the mentioned solutions is applied. In order to have the best improvement, the combination between geometric and cycle time length changes are applied. Analysis showed that there was a remarkable improvement in LOS and changed from E to D.

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PEDESTRIAN SAFETY EVALUATION OF SIGNALIZED INTERSECTIONS USING SURROGATE SAFETY MEASURES

Transport ◽

10.3846/transport.2020.12157 ◽

2020 ◽

Vol 35 (1) ◽

pp. 48-56

Author(s):

Sankaran Marisamynathan ◽

Perumal Vedagiri

Keyword(s):

Safety Evaluation ◽

Pedestrian Safety ◽

Signalized Intersections ◽

Signalized Intersection ◽

Mixed Traffic ◽

Model Framework ◽

Safety Measures ◽

Severity Level ◽

Traffic Conditions ◽

Surrogate Safety Measures

The large proportions of pedestrian fatalities led researchers to make the improvements of pedestrian safety at intersections. Thus, this paper proposes a methodology to evaluate crosswalk safety at signalized intersections using Surrogate Safety Measures (SSM) under mixed traffic conditions. The required pedestrian, traffic, and geometric data were extracted based on the videographic survey conducted at signalized intersections in Mumbai (India). Post Encroachment Time (PET) for each pedestrian were segregated into three categories for estimating pedestrian–vehicle interactions and Cumulative Frequency Distribution (CDF) was plotted to calculate the threshold values for each interaction severity level. The Cumulative Logistic Regression (CLR) model was developed to predict the pedestrian mean PET values in the cross-walk at signalized intersections. The proposed model was validated with a new signalized intersection and the results were shown that the proposed PET ranges and model appropriate for Indian mixed traffic conditions. To assess the suitability of model framework, model transferability was carried out with data collected at signalized intersection in Kolkata (India). Finally, this study can be helpful to rank the severity level of pedestrian safety in the crosswalk and improve the existing facilities at signalized intersections.

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Link Flow Evaluation Using Loop Detector Data: Traveler Response to Variable-Message Signs

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198196155000108 ◽

1996 ◽

Vol 1550 (1) ◽

pp. 58-64 ◽

Cited By ~ 5

Author(s):

Youngbin Yim ◽

Jean-Luc Ygnace

Keyword(s):

Real Time ◽

Traffic Management ◽

Preliminary Investigation ◽

Traffic Information ◽

Mean Flow ◽

Variable Message Signs ◽

Real Time Traffic ◽

Operational Test ◽

Paris Region ◽

Message Signs

Système d'Information Routière Intelligible aux Usagers (SIRIUS) is the largest urban field operational test of the advanced traveler information and automated traffic management system in Europe. With variable-message signs, SIRIUS has been in operation in the Paris region for 3 years. A preliminary investigation of the effectiveness of the SIRIUS system in traffic management is presented. The extent to which drivers respond to real-time traffic information and the consequential changes in link flow under SIRIUS is also presented. Time-series traffic data were analyzed to measure changes in mean flow rates at a selected link. It was found that variable-message signs influence drivers to choose less congested routes when drivers are provided with real-time traffic information, and that a driver's decision to divert is closely associated with the information pertaining to the level of congestion. In the Paris region, drivers received information on the length of the queue at the time of this study. As congestion becomes heavier, drivers are more likely to respond to variable-message signs. According to the data analysis, a queue length of 3 km seems to be a threshold at which a significant number of drivers choose to use an alternative route.

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Artificial Intelligence-Based Architecture for Real-Time Traffic Flow Management

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/1651-08 ◽

1998 ◽

Vol 1651 (1) ◽

pp. 53-58 ◽

Cited By ~ 6

Author(s):

Adel W. Sadek ◽

Brian L. Smith ◽

Michael J. Demetsky

Keyword(s):

Artificial Intelligence ◽

Real Time ◽

Traffic Flow ◽

Traffic Management ◽

Traffic Information ◽

Case Based Reasoning ◽

Flow Management ◽

Real Time Traffic ◽

Highway Network ◽

Traffic Flow Management

Real-time traffic flow management has recently emerged as one of the promising approaches to alleviating congestion. This approach uses real-time and predicted traffic information to develop routing strategies that attempt to optimize the performance of the highway network. A survey of existing approaches to real-time traffic management indicated that they suffer from several limitations. In an attempt to overcome these, the authors developed an architecture for a routing decision support system (DSS) based on two emerging artificial intelligence paradigms: case-based reasoning and stochastic search algorithms. This architecture promises to allow the routing DSS to ( a) process information in real time, ( b) learn from experience, ( c) handle the uncertainty associated with predicting traffic conditions and driver behavior, ( d) balance the trade-off between accuracy and efficiency, and ( e) deal with missing and incomplete data problems.

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