scholarly journals Traffic Congestion Quantification for Urban Heterogeneous Traffic Using Public Transit Buses as Probes

2018 ◽  
Vol 47 (4) ◽  
pp. 257-267
Author(s):  
Selvaraj Vasantha Kumar ◽  
Ramaswamy Sivanandan
Keyword(s):  
Travel Time ◽  
Performance Measures ◽  
Traffic Congestion ◽  
Public Transit ◽  
Heterogeneous Traffic ◽  
Time Data ◽  
Transit Buses ◽  
Wide Range ◽  
Acceleration And Deceleration ◽  
Bus Stops

Understanding congestion in space-time domain using performance measures is essential prior to suggesting improvement schemes to reduce congestion. With technological advances like Global Positioning System (GPS), many metropolitan planning organizations give more emphasis on travel time based performance measures to quantify congestion, than on traditional way of using volume-to-capacity (V/C) ratios. In India, often it may not be possible to use personal vehicles as probes for travel time data collection. However, the public transit buses fitted with GPS devices could be used as cheap and effective probes to estimate the congestion status of other types of vehicles in the stream. The present study is an attempt in this direction. Two bus transit routes in Chennai, India were considered as case studies in order to cover the wide range of geometric and traffic conditions on urban arterials. GPS-fitted buses on these routes were used as probes in congestion quantification. As the dwell time at bus stops is a unique characteristic of transit buses when compared to other vehicles in the stream, a methodology has been proposed to find the dwell times including acceleration and deceleration times based on the approaching and departing speeds at bus stops. Regression models were then developed to predict the Congestion Index (CI) for various types of vehicles using bus CI, weighted carriageway width and the presence or absence of signalized intersection as independent variables. The results are promising and could be considered for real-time display of congestion levels for Advanced Traveler Information System (ATIS) applications.

scholarly journals Researching Relationships between Truck Travel Time Performance Measures and On-Network and Off-Network Characteristics

2021 ◽  
Author(s):  
Sarvani Duvvuri ◽  
Srinivas S. Pulugurtha
Keyword(s):  
Travel Time ◽  
Performance Measures ◽  
Traffic Congestion ◽  
Pearson Correlation ◽  
Time Data ◽  
Network Characteristics ◽  
Time Index ◽  
Time Performance ◽  
Travel Time Data ◽  
Day Of The Week

Trucks serve significant amount of freight tonnage and are more susceptible to complex interactions with other vehicles in a traffic stream. While traffic congestion continues to be a significant ‘highway’ problem, delays in truck travel result in loss of revenue to the trucking companies. There is a significant research on the traffic congestion mitigation, but a very few studies focused on data exclusive to trucks. This research is aimed at a regional-level analysis of truck travel time data to identify roads for improving mobility and reducing congestion for truck traffic. The objectives of the research are to compute and evaluate the truck travel time performance measures (by time of the day and day of the week) and use selected truck travel time performance measures to examine their correlation with on-network and off-network characteristics. Truck travel time data for the year 2019 were obtained and processed at the link level for Mecklenburg County, Wake County, and Buncombe County, NC. Various truck travel time performance measures were computed by time of the day and day of the week. Pearson correlation coefficient analysis was performed to select the average travel time (ATT), planning time index (PTI), travel time index (TTI), and buffer time index (BTI) for further analysis. On-network characteristics such as the speed limit, reference speed, annual average daily traffic (AADT), and the number of through lanes were extracted for each link. Similarly, off-network characteristics such as land use and demographic data in the near vicinity of each selected link were captured using 0.25 miles and 0.50 miles as buffer widths. The relationships between the selected truck travel time performance measures and on-network and off-network characteristics were then analyzed using Pearson correlation coefficient analysis. The results indicate that urban areas, high-volume roads, and principal arterial roads are positively correlated with the truck travel time performance measures. Further, the presence of agricultural, light commercial, heavy commercial, light industrial, single-family residential, multi-family residential, office, transportation, and medical land uses increase the truck travel time performance measures (decrease the operational performance). The methodological approach and findings can be used in identifying potential areas to serve as truck priority zones and for planning decentralized delivery locations.

Validation and Calibration of Freeway Reliability Methodology in the Highway Capacity Manual: Method and Case Studies

2018 ◽  
Vol 2672 (15) ◽  
pp. 93-104 ◽  
Author(s):  
Nabaruna Karmakar ◽  
Seyedbehzad Aghdashi ◽  
Nagui M. Rouphail ◽  
Billy M. Williams
Keyword(s):  
Travel Time ◽  
Performance Measures ◽  
Traffic Congestion ◽  
Practical Implementation ◽  
Travel Time Reliability ◽  
Time Data ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Reliability Performance ◽  
The Impact

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

scholarly journals Delay Measurement of Manually Controlled Intersection Using GPS

2014 ◽  
Vol 8 (1) ◽  
pp. 130-135
Author(s):  
S. Nithya ◽  
D. Senthurkumar ◽  
K. .Gunasekaran
Keyword(s):  
Travel Time ◽  
Traffic Control ◽  
Weather Conditions ◽  
Heterogeneous Traffic ◽  
Gps Data ◽  
Peak Period ◽  
Control Delay ◽  
Average Travel Time ◽  
Vehicle Acceleration ◽  
Acceleration And Deceleration

The travel time studies are one of the most important measures used for evaluating the performance of road networks. The Global Positioning System (GPS) is a space-based system that provides position and time information in all weather conditions. GPS data could be used to obtain the values of traffic control delay, vehicle queue, average travel time and vehicle acceleration and deceleration at intersections.The task of estimation of delay becomes complex if it is performed for intersections carrying heterogeneous traffic and that to for over saturated conditions. Most of the urban signalized intersections are manually controlled during peak hours. GPS device fitted in a vehicle was run repeatedly during morning peak period and the period during which vehicles were allowed to cross the intersection was recorded with video graphic camera. The attempt to identify the control delay with the GPS data from the test vehicle while crossing manually operated major intersection is presented in this paper.

scholarly journals On the Benefits of Providing Timely Information in Ticket Queues with Balking and Calling Times

Mathematics ◽  
2021 ◽  
Vol 9 (21) ◽  
pp. 2753
Author(s):  
Gabi Hanukov ◽  
Michael Hassoun ◽  
Oren Musicant
Keyword(s):  
Performance Measures ◽  
Traffic Congestion ◽  
Real Life ◽  
Time Loss ◽  
Wide Range ◽  
New Type ◽  
Expected Waiting Time ◽  
Partially Observable ◽  
Steady State Probabilities ◽  
Different Levels

We study a phenomenon causing server time loss in ticket queues with balking and calling time. A customer who balks from the queue after printing a ticket leaves a virtual entity in the queue that requires server time to be cleared. The longer the queue, the larger the proportion of customers abandoning their place, and the larger the server time loss due to calling customers that left the queue. The solution is suggested by giving the customer the best possible estimate of her expected waiting time before printing a ticket, thus ensuring that, if she balks, no number in the queue is created that will waste server time. Although partially observable ticket queues have been studied in the literature, the addition of a calling time for absent customers creates a new type of problem that has been observed in real life but has not been formally addressed yet. We analyze this stochastic system, formulate its steady state probabilities, and calculate the system’s performance measures. The analytical solution provided here is robust and can be applied to a wide range of customers’ behavior functions. Finally, numerical analysis is performed that demonstrates the benefits of providing timely information to customers for different levels of traffic congestion.

Adaptive route choice model for public transit systems: an application of Markov decision processes

2012 ◽  
Vol 39 (8) ◽  
pp. 915-924 ◽  
Author(s):  
Behzad Rouhieh ◽  
Ciprian Alecsandru
Keyword(s):  
Travel Time ◽  
Real Time ◽  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Public Transit ◽  
Choice Model ◽  
Transportation Systems ◽  
Transit System ◽  
Transit Systems ◽  
The Impact

Over the past couple of decades the advancements in the areas of information and computational technology allowed for a variety of intelligent transportation systems developments and deployments. This study investigates an advanced traveler information system (ATIS) and (or) an advanced public transit system (APTS) adaptive and real-time transit routing component. The proposed methodology is applied to bus routes with fixed, predefined bus line alignments. It is shown that routing buses on such systems can be modeled in real-time by employing an associated Markov chain with reward model to minimize the impact of congested traffic conditions on the travelers and the overall operation cost of the transit system. A case study using a traffic and transit data from a real-world bus line was used to apply the proposed bus routing approach. It was found that under certain traffic congestion conditions buses should be re-routed to minimize their travel time and the associated system costs. The hypothetical congestion scenarios investigated show that individual bus travel time delays range between 50 and 740 s when the proposed adaptive routing is employed. The proposed methodology is also suitable for application to transit systems that run on a demand-adaptive basis (the bus line alignment changes with the travelers demand). Additional calibration and future integration of the system into specific ATIS and (or) APTS user services will be investigated.

scholarly journals PEMETAAN SUHU LAUT DI PERAIRAN TELUK BALIKPAPAN MENGGUNAKAN TEKNOLOGI AKUSTIK TOMOGRAFI PANTAI

2019 ◽  
Vol 11 (1) ◽  
pp. 25-36
Author(s):  
Teguh Arif Pianto ◽  
Henry M. Manik ◽  
Indra Jaya
Keyword(s):  
Travel Time ◽  
Seawater Temperature ◽  
Temperature Data ◽  
Acoustic Tomography ◽  
Inversion Method ◽  
Time Data ◽  
Sea Temperature ◽  
Tomography System ◽  
Wide Range ◽  
Temperature Depth

ABSTRAKSuhu laut dalam oseanografi merupakan faktor penting yang menunjukkan kualitas suatu perairan sehingga pemetaan secara spasial dan temporal perlu dilakukan. Salah satu teknologi yang potensial efektif untuk dapat digunakan dalam melakukan pemetaan suhu laut adalah dengan menggunakan teknologi akustik tomografi pantai Coastal Acoustic Tomography system (CATs). Penerapan teknologi akustik tomografi pantai di perairan teluk Balikpapan belum pernah dilakukan sebelumnya. Teknologi ini dapat menjangkau daerah yang luas dan dapat melakukan pemetaan suhu laut perlapisan kedalaman dengan resolusi temporal permenit. Tujuan dari penelitian ini adalah untuk merekonstruksi data akustik tomografi untuk mendapatkan nilai suhu laut dari data waktu tempuh yang diperoleh antar pasangan stasiun sehingga menjadi peta sebaran suhu laut di jejaring CATs. Penelitian dilakukan dengan menempatkan 4 stasiun akustik yang direkonstruksi melalui metode inversi dari waktu tempuh akustik yang diperoleh antar pasangan stasiun dan suhu rata-rata di lintasan terbentuk menggunakan formula Mackenzie. Hasil rekonstruksi suhu rata-rata pada lintasan jejaring CATs berkisar 28oC sampai 30oC. Uji validasi data suhu laut hasil pengukuran dengan metoda akustik tomografi pantai dengan alat ukur CTD (Conductivity Temperature Depth) diperoleh akurasi antara nilai suhu laut hasil pengukuran dengan data CTD mencapai 98%, nilai koefisien korelasi R=0,79. Kesimpulan penelitian didapati bahwa rekonstruksi data Akustik Tomografi telah berhasil mengakusisi data suhu laut dengan tingkat ketelitian pada pengukuran yang dilakukan di perairan Teluk Balikapapan mencapai lebih dari 97%. ABSTRACTSea temperature in oceanography is an important factor to figure out the quality of waters that the conducted mapping spatially and temporally. One of the potential technologies effectively can be carried out by mapping sea temperature is a coastal acoustic tomography system (CATs). This technology has never been implemented conducted in Balikpapan Bay before. The technology is able to reach out of a wide range of seawater area and to map sea temperature according to its depth layers.The purpose of this study is to reconstruct tomographic acoustic data to obtain ocean temperature values from travel time data that obtained between pair of stations, so it became a map of sea temperature distribution in CAT’s network. This research was taken by setting four reconstructed observational stations through inversion method of received acoustic travel time among paired stations. The average of temperatures in the formed tracks was analyzed by using Mackenzie formula.The results of reconstructing the seawater temperatures in the CATs tracking networks are in a range of 28oC – 30oC. Aalidation test of the seawater temperature data resulted from coastal acoustic tomography method by using a CTD (Conductivity Temperature Depth) generates the accuracies of the seawater temperature are more than 98% and a correlation coefficient R = 0.79. The finding of the study was the reconstruction of Acoustic Tomography data has succeeded in acquiring sea temperature data with a level of accuracy level of more than 97%.

scholarly journals Travel Time Reliability of Bus Operation in Heterogeneous Traffic Conditions of Dar es Salaam City, Tanzania

2020 ◽  
Vol 11 (2) ◽  
pp. 44-55
Author(s):  
Prosper S. Nyaki ◽  
Hannibal Bwire ◽  
Nurdin K. Mushule
Keyword(s):  
Travel Time ◽  
Traffic Flow ◽  
Traffic Congestion ◽  
Dar Es Salaam ◽  
Heterogeneous Traffic ◽  
Service Reliability ◽  
Travel Time Reliability ◽  
Activity Scheduling ◽  
Traffic Conditions ◽  
Deviation Coefficient

AbstractThe assessment of travel time reliability enables precise prediction of travel times, better activity scheduling and decisions for all users of the road network. Furthermore, it helps to monitor traffic flow as a crucial strategy for reducing traffic congestion and ensuring high-quality service in urban roads. Travel time reliability is a useful reference tool for evaluating transport service quality, operating costs and system efficiency. However, many analyses of travel time reliability do not provide true travel variation under heterogeneous traffic flow conditions where traffic flow is a mixture of motorized and non-motorized transport. This study analysed travel time reliability under heterogeneous traffic conditions. The travel reliabilities focused on passenger waiting time at bus stops, in-vehicle travel time, and delay time at intersections which were analysed using buffer time, standard deviation, coefficient of variation, and planning time. The data used were obtained from five main bus routes in Dar es Salaam. The results indicate low service reliability in the outbound directions compared to inbound directions. They also intend to raise awareness of policy-makers about the situation and to make them shift from expanding road networks towards optimising road operations.

scholarly journals Values of Travel Time for Recreational Trips under Different Behavioural Rules

2021 ◽  
Vol 13 (12) ◽  
pp. 6831
Author(s):  
Rosa Marina González ◽  
Concepción Román ◽  
Ángel Simón Marrero
Keyword(s):  
Travel Time ◽  
National Parks ◽  
Traffic Congestion ◽  
National Park ◽  
Revealed Preference ◽  
Discrete Choice Models ◽  
Model Specification ◽  
Regret Minimization ◽  
Random Regret Minimization

In this study, discrete choice models that combine different behavioural rules are estimated to study the visitors’ preferences in relation to their travel mode choices to access a national park. Using a revealed preference survey conducted on visitors of Teide National Park (Tenerife, Spain), we present a hybrid model specification—with random parameters—in which we assume that some attributes are evaluated by the individuals under conventional random utility maximization (RUM) rules, whereas others are evaluated under random regret minimization (RRM) rules. We then compare the results obtained using exclusively a conventional RUM approach to those obtained using both RUM and RRM approaches, derive monetary valuations of the different components of travel time and calculate direct elasticity measures. Our results provide useful instruments to evaluate policies that promote the use of more sustainable modes of transport in natural sites. Such policies should be considered as priorities in many national parks, where negative transport externalities such as traffic congestion, pollution, noise and accidents are causing problems that jeopardize not only the sustainability of the sites, but also the quality of the visit.

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