Low Traffic Volume Research Articles

Short-Time Traffic Forecasting in Tourist Service Areas Based on a CNN and GRU Neural Network

The continuous development of highway construction projects has prompted the function of service areas to be improved day by day. A traditional service area gradually transforms from a single traffic service mode to a complex traffic service mode. The continuous enrichment and perfection of the service area’s function makes the surrounding highway network more attractive, which leads to a sudden increase in highway traffic volume in a short period of time. In order to better improve the service level of a tourist service area by predicting the short-term traffic volume of the toll station around the tourist service area, this paper proposes a model combining a convolutional neural network and a gated recurrent unit (CNN plus GRU) to solve the problem of short-term traffic volume prediction. The data from 17 toll stations of the Yu’an Expressway in Guizhou Province were selected for the experiment to test the prediction effect of the CNN plus GRU-based model. The experimental results show that the prediction accuracy, the MAE and RMSE, are 1.8101 and 2.7021, respectively, for the toll stations with lower traffic volumes, and 3.820 and 5.172, respectively, for the toll stations with higher traffic volumes. Compared with a single model, the model’s prediction accuracy is improved, to different degrees. Therefore, the use of a convolutional neural network operation is better when the total traffic volume is low, considering the algorithm’s time and error. When using the combined convolutional neural network and gated recurrent unit model and when the total traffic volume is high, the algorithm error is significantly reduced and the prediction results are better.

Hierarchy Descending SFC Provisioning Scheme With Load Balancing in Fog Computing

This letter presents a novel provisioning scheme for service function chain (SFC) requests for delay-sensitive applications. The SFC is comprised of virtual network functions (VNF) to be mapped on a multi-tier fog architecture composed of primary and secondary nodes with limited resources. Now existing provisioning methods establish service paths based on least delay or load, and then map single VNFs on each fog node. However, these approaches can yield early congestion at the primary nodes, thus leaving secondary nodes unoccupied due longer link delays. To solve this problem, the proposed scheme leverages a descending hierarchical approach to enhance admission and utilization rates and reduce provisioning delays. At low traffic volumes, it performs grouped VNF mapping on secondary nodes through shorter paths that skip underloaded primary nodes. At high traffic volumes, it performs single mapping on primary nodes over established paths.

Changes in Ultrafine Particle Concentrations near a Major Airport Following Reduced Transportation Activity during the COVID-19 Pandemic.

Mobility reductions following the COVID-19 pandemic in the United States were higher, and sustained longer, for aviation than ground transportation activity. We evaluate changes in ultrafine particle (UFP, Dp < 100 nm, a marker of fuel-combustion emissions) concentrations at a site near Logan Airport (Boston, Massachusetts) in relation to mobility reductions. Several years of particle number concentration (PNC) data prepandemic [1/2017–9/2018] and during the state-of-emergency (SOE) phase of the pandemic [4/2020–6/2021] were analyzed to assess the emissions reduction impact on PNC, controlling for season and wind direction. Mean PNC was 48% lower during the first three months of the SOE than prepandemic, consistent with 74% lower flight activity and 39% (local)–51% (highway) lower traffic volume. Traffic volume and mean PNC for all wind directions returned to prepandemic levels by 6/2021; however, when the site was downwind from Logan Airport, PNC remained lower than prepandemic levels (by 23%), consistent with lower-than-normal flight activity (44% below prepandemic levels). Our study shows the effect of pandemic-related mobility changes on PNC in a near-airport community, and it distinguishes aviation-related and ground transportation source contributions.

An analysis of the New York City traffic volume, vehicle collisions, and safety under COVID-19

Introduction and Method: We use the arguably exogenous intensity of COVID-19 as an instrument in order to study the relationship between traffic volume and vehicle collisions in a large metropolitan area. We correlate data from multiple sources and consider a time interval ranging from about one year before to one year after the pandemic breakout, which allows to account for preexisting seasonal patterns as well as the disruption brought by the pandemic. Results: We identify that increased traffic volume is associated with significantly more collisions with a robust elasticity varying between 1.2 and 1.7. At the same time, higher traffic volumes are associated with a significant reduction in casualties. Conversely, low traffic volumes are associated with high speeds and with particularly dangerous collisions. In terms of social cost, we separately calculated the cost of property damage and casualties. We measured that the reduction in the per-day social cost of collisions during the COVID-19 period is approximately $453,000 in property damage. However, the increase in casualties from collisions at lower traffic volumes are worth approximately $2.6 million in injuries and fatalities, entirely offsetting any benefit from reduced collisions. Practical Applications: This research provides valuable insights that policy makers may take into consideration when shifting traffic volume in relation to social cost and safety, such as congestion taxes.

An Evaluation Framework for Sustainable Development: The Challenge for Planners and Development

The continued urbanizing with rapid development has induced the changes of several urban environmentalaspects both positive and negative impacts. Although urban development has brought high technology improvementto support the demand of population, the transformations in term of replacement of natural resources andsocial value has become sustainability challenges, especially in the nonphysical terms. These changes has beenan evidence of influences of revolutionize on urban physical terms create on the structure of urban morphologyกรอบการประเมินการพัฒนาอย่างยั่งยืน:ความท้าทายของนักวางแผนต่อการพัฒนาเมืองAn Evaluation Framework for Sustainable Development:The Challenge for Planners and Developmentภาวิณี เอี่ยมตระกูล1 ชมพูนุท คงพุนพิน2 และ วิมลสิทธิ์ หรยางกูร3Pawinee Iamtrakul1, Chompoonut Kongphunphin2 and Vimolsiddhi Horayangkura3คณะสถาปัตยกรรมศาสตร์และการผังเมือง มหาวิทยาลัยธรรมศาสตร์ จังหวัดปทุมธานี 12121Faculty of Architecture and Planning, Thammasat University, Pathumthani, 12121, ThailandE-mail: iamtrakul@gmail.com186 JARS 10(1). 2013which has been essential for meeting this challenge to improve efficient urban development and planningphase. The conceptual and analytical framework covering different aspects both physical and nonphysicalcharacteristics with rational land use structure plays an essential role for objectively evaluating thesustainability of urban land use. Thus, to explore the association of those characteristics, this study identifiedthe potential neighborhood structure by applying a geographical analysis tool to quantify the spatial interactionof social space of the adjacent area. Consequently, social features could be determined in terms of socialcapital of different locations in dissimilar neighborhoods of Thakhlong municipality, Pathumthani province. Basedon the application of Potential Surface Analysis (PSA) and Urban Network Analysis (UNA), the major factors forevaluating the sustainability of urban land use could be used to explain. It was found that public spaces of thetraditional communities within the study area demonstrated poor urban potential. On the other hand, with goodlocal accessibility and low traffic volume, these areas have been important places of the community in term ofpublic spaces such as space in temple, market, etc. The more social capital could be induced within this typeof spaces rather than the community near by the industrial area which is represented of new development areaof good accessibility with higher hierarchy of roads. This finding could be applied for further suggestionsand recommendations for concerned government to design relevant policy in achieving the sustainabledevelopment of urban land use and planning. Also the framework of this study could be appropriate for anassessment of the sustainability of urban land use and planning.

Field Performance and Cost-Effectiveness of Chip Seals and Asphalt Concrete Overlays with and without Asphalt Concrete Stripping Damage

The objective of this study was to evaluate the effects of asphalt concrete (AC) stripping damage on the field performance and cost-effectiveness (CE) of chip seals and AC overlays in pavement maintenance and rehabilitation. To achieve this objective, in-service pavement sections were selected from the Louisiana pavement management system (LaPMS) database and the presence of moisture damage was confirmed through the visual inspection of extracted cores. Sections were categorized according to traffic volume and their pavement condition index before treatment (PCI-). Road sections in each group were then divided into two groups as stripped and non-stripped sections. The average deterioration rate (ADR), extension in pavement service life (ΔPSL), average condition improvement over the treatment service life (PI), and CE were compared for stripped and non-stripped sections. Results showed that for chip seal sections, moisture damage negatively affected the performance of the sections with PCI- &lt; 80 and low traffic volumes. For sections with PCI- &gt; 80, similar performance was observed for stripped and non-stripped sections. For AC overlays, moisture-induced damage significantly affected the long-term pavement performance at all traffic levels. On average, moisture-induced damage decreased ΔPSL, PI, and CE of AC overlays by 5 years, 24%, and 0.5%, respectively. Overall, results of the study demonstrated that moisture damage has a significant effect on the performance of chip seal and AC overlay. Therefore, it is critical to identify and repair stripped sections before the maintenance and rehabilitation of in-service pavements to ensure adequate performance and optimum CE.

Estimating Average Daily Traffic on Low-Volume Roadways in Louisiana

Traffic volume is an important parameter that agencies use as a decisive factor, especially at the time of design, maintenance, and operation of roadways. Thus, its correct estimation is very essential. There are already a few established proprietary products available on the market that can predict traffic volumes. In addition, past studies have used several mathematical models to predict traffic volume. Relatively fewer studies have been conducted on predicting traffic volume on low-volume roadways. To bridge the gap on the prediction of traffic volume for low- and high-volume roadways, this study seeks to find practical, cost-effective, and progressive methods of estimating and classifying traffic on low-volume rural roadways. Across the state of Louisiana, 395 locations with low traffic volumes of less than 500 vehicles per day were selected. Census tract data was used to extract demographic and socioeconomic information for each location. Two prediction models—linear regression and random forest regression models—were developed to predict traffic volumes on these low-volume roadways. The results showed that the linear regression model had the highest predictive accuracy, with R-square of 0.979 and root mean square error of 70.26 compared with the RMSE of 110.23 for the random forest regression model. Both models found functional class, land use, number of lanes, population density, median age, median household income, and household density significantly affecting the traffic volume.

Shared vs. dedicated lanes for automated vehicle deployment: A simulation-based assessment

• In shared lanes (SL), CAVs reduce delay and emissions by 38% and 52%, respectively. • An optimum percentage of CAV dedicated lanes (DL) is calculated for each MPR level. • SLs perform better at low traffic volumes, while DLs perform better at high volumes. • Emissions increase slightly below 40% MPR but are quickly reduced at higher MPRs. • Delay and throughput improvements occur mostly at MPRs above 30%. Connected and automated vehicles (CAV) will change the transportation world at an increasingly substantial pace. To realize the full potentials of CAV technologies, we need to investigate the transition period during which CAVs will share the roads with manually driven vehicles (MDV). This study provides a detailed assessment of the impacts of CAVs on freeways in the near future, which could serve as a basis for transportation officials and authorities to compare the different approaches for CAV deployment. The analysis was performed by modeling a hypothetical freeway segment using microsimulation. Three measures of effectiveness were used to quantify the impacts of CAVs, namely, average delay, throughput, and greenhouse gas emissions. The results reveal that at the baseline scenario of shared lanes (SL) with medium traffic volume, replacing MDVs with CAVs reduces 28.4 seconds (38%) in average delay. Additionally, throughput increases by 30%, and over 6,900 gCO 2 equivalent emissions (52%) are saved. Following the baseline analysis, an optimum percentage of dedicated lanes (DL) is derived for each market penetration rate (MPR) during the transition period. Finally, a comparison between DLs and SLs is conducted across multiple traffic volume scenarios. The findings indicate that SLs generally perform better at light traffic volumes, while DLs surpass them in congested conditions. When CAVs are deployed, both delay and throughput follow steady improvement in performance that is more evident at higher MPRs, i.e., above 30%. On the other hand, emissions experience a significant reduction in efficiency at 0 to 40% MPR but quickly make up for these losses at higher MPRs.

Estimating Road Mortality Hotspots While Accounting for Imperfect Detection: A Case Study with Amphibians and Reptiles

Wildlife road mortality tends to aggregate spatially at locations commonly referred to as road mortality hotspots. Predictive models can be used to identify locations appropriate for mitigation measures that reduce road mortality. However, the influence of imperfect detection (e.g., false absences) during road mortality surveys can lead to inaccurate or imprecise spatial patterns of road mortality hotspots and suboptimal implementation of mitigation measures. In this research, we used amphibians and reptiles as a case study to address imperfect detection issues when estimating the probability of road mortality hotspots using occupancy detection modeling. In addition, we determined the survey effort needed to achieve a high probability of detecting large roadkill events. We also assessed whether vehicle travel reductions associated with the COVID-19 pandemic travel restrictions led to reductions in road mortality. We conducted surveys at 48 sites throughout Rhode Island, USA, from 2019–2021. In total, we observed 657 carcasses representing 19 of Rhode Island’s 37 native species. Of the 19 native species, eight species of frogs, four species of salamanders, four species of snakes, and three species of turtles were observed. We documented a reduction in roadkill density and the proportion of dead versus live amphibians and reptiles in pandemic years (2020 and 2021), but we were unable to link reductions in roadkill density to reductions in traffic volume. Our model results indicated that large roadkill events were more likely to occur on roads near wetlands and with low traffic volume and were more likely to be detected as daily precipitation increased. We determined that there was a low probability of detecting large roadkill events, suggesting that imperfect detection influences detection of large roadkill events, and many were likely missed during our surveys. Therefore, we recommend using occupancy modeling to account for the influence of imperfect detection when estimating road mortality hotspots. This approach will more effectively guide the implementation of mitigation measures.

Comparing Traffic Noise Levels between Signalized Intersections and Roundabouts in an Urban Environment

This study aims to investigate and compare the traffic noise generated from signalized intersections and roundabouts. Hourly equivalent traffic noise level, traffic volume, and weather data were collected at four signalized intersections and four roundabouts of different sizes (two-lane and three-lane). Data were collected for a total period of 32 h during one weekday and one weekend at each intersection. A comparative traffic noise analysis that focused on peak hours was conducted between the different types of intersections. When comparing intersections of similar type and size, intersections with higher traffic volume produced higher traffic noise levels. However, when comparing intersections of different types and sizes, the two-lane roundabouts had lower traffic volume than the three-lane roundabouts but generated much higher traffic noise levels. When compared with two-lane signalized intersections, the two-lane roundabouts generated a much higher traffic noise with a slightly higher traffic volume. Similarly, the three-lane signalized intersections performed better than the three-lane roundabouts with marginally higher traffic noise levels and a much higher traffic volume. The results indicated that signalized intersections can be a better option than roundabouts from a traffic noise perspective when traffic volume is expected to be high.

A stochastic simulation model for assessing the masking effects of road noise for wildlife, outdoor recreation, and bioacoustic monitoring

Traffic noise is one of the leading causes of reductions in animal abundances near roads. Acoustic masking of conspecific signals and adventitious cues is one mechanism that likely causes animals to abandon loud areas. However, masking effects can be difficult to document in situ and the effects of infrequent noise events may be impractical to study. Here, we present the Soundscapes model, a stochastic individual-based model that dynamically models the listening areas of animals searching for acoustic resources (“searchers"). The model also studies the masking effects of noise for human detections of the searchers. The model is set in a landscape adjacent to a road. Noise produced by vehicles traveling on that road is represented by calibrated spectra that vary with speed. Noise propagation is implemented using ISO-9613 procedures. We present demonstration simulations that quantify declines in searcher efficiency and human detection of searchers at relatively low traffic volumes, fewer than 50 vehicles per hour. Traffic noise is pervasive, and the Soundscapes model offers an extensible tool to study the effects of noise on bioacoustics monitoring, point-count surveys, the restorative value of natural soundscapes, and auditory performance in an ecological context.

Study on the effect of vehicular pollution on the ambient concentrations of particulate matter and carbon dioxide in Srinagar City.

The present study was carried out to monitor the ambient concentrations of particulate matter and carbon dioxide caused by vehicular pollution in Srinagar City of Jammu and Kashmir, India, for a period of 12 months from June 2019 to May 2020 as the major contributions in these areas are due to vehicular movement. Out of five, four locations (viz. Dalgate, Jehangir Chowk, Parimpora and Pantha Chowk) had highest traffic density in the city and the fifth location (Shalimar) had low traffic volume. The sampling was done on every fortnight using AEROCET 831—aerosol mass monitor and CDM 901—CO2 monitor with each sampling being carried out three times a day, i.e. morning (9:00 am–10:30 am), afternoon (1:00 pm–2:30 pm) and evening (4:30 pm–6:00 pm) with three replications at each site based on the peak traffic hours. The results show that during the whole period, average PM1 concentrations ranged from 15.10 to 108.9 µg/m3, PM2.5 (28.70–577.50 µg/m3), PM4 (44.50–780.87 µg/m3), PM10 (57.13–1225.53 µg/m3), total suspended particulates (77.77–1410.27 µg/m3) and CO2 (332.4–655.0 ppm). The average concentrations of these parameters showed that the maximum PM1 concentration was found at Dalgate (53.77 µg/m3) and PM2.5 had its maximum average concentration at Jehangir Chowk (140.13 µg/m3). Other parameters like PM4, PM10, TSP and CO2 had a maximum average values at Jehangir Chowk (240.23 µg/m3, 633.40 µg/m3, 853.50 µg/m3 and 533.20 ppm, respectively). The pollution load was observed to be maximum during winter season followed by autumn, summer and spring. The lowest concentration of all pollutants except CO2 was observed in April 2020 and this might be due to COVID-19 lockdown observed in the country during the same period.

A review on soil stabilisation of unsealed road pavements from an Australian perspective

Unsealed roads are the backbone for many countries’ growth and development. Given low traffic volumes, economic considerations cannot justify higher class paved roads, as a result, are prone to distress. Research studies have shown that the targeted application of additives and specific techniques to unsealed pavements can improve its engineering and geotechnical properties. This paper covers a comprehensive up to date literature review of various techniques for improving unsealed road durability. The literature is categorised based on non-chemical and chemical additive techniques. These techniques are reviewed and discussed to provide a critical overview of the stabilisation mechanisms, properties, performance, durability, and suitability in unsealed roads. This review highlights the shift towards sustainable stabilisation without considerable impact to current unsealed pavement practices, but at the effect of a sound understanding of stabilisation approaches and longterm performance data. The review captures the current state-of-knowledge in the field of unsealed road pavements.

Toll roads in Turkey: Private versus public

The main objective of this paper is to compare the toll rates on publicly and privately financed toll roads in Turkey. Public toll roads have reasonable toll rates and generate revenues that cover their costs, but public funds are not sufficient to expand the network. Private toll roads, on the other hand, have relatively high toll rates, resulting in low traffic volumes. This places a significant burden on the budget due to traffic-revenue guarantees. Turkish case shows that PPPs lead to higher tolls, resulting in the underutilization of infrastructure and efficiency losses. In the long run, traditional public financing seems to be the better option for toll road projects.

Concentration and leachability of N-(1,3-dimethylbutyl)-N′-phenyl-p-phenylenediamine (6PPD) and its quinone transformation product (6PPD-Q) in road dust collected in Tokyo, Japan

A recently identified chemical, 2-((4-Methylpentan-2-yl)amino)-5-(phenylamino)cyclohexa-2,5-diene-1,4-dione (6PPD-quinone; 6PPD-Q), is a transformation product of an additive used in the manufacture of tire rubber and causes acute lethality in coho salmon (Oncorhynchus kisutch) in urban watersheds. Despite its potential presence and ecotoxicity in receiving waters worldwide, information on the occurrence and fate of 6PPD-Q is limited. Here, we investigated the concentrations of 6PPD-Q and its parent chemical, 6PPD, in road dust collected from arterial and residential roads in Tokyo, Japan from May to October 2021. 6PPD-Q concentrations were highest from May to June, when atmospheric ozone concentrations are the highest in Japan; a correlation between 6PPD-Q and photochemical oxidants, as an alternative to ozone, corroborated this finding. We also found that 6PPD-Q concentrations at photochemical oxidant concentrations ranging from 35 to 47 ppbv were higher in dust collected from roads with high traffic volumes (i.e., arterial roads; median: 8.6 μg/g-OC) than in dust collected from roads with lower traffic volumes (i.e., residential roads; median: 6.3 μg/g-OC), indicating that 6PPD-Q is generated from traffic-related sources. We also found that 6PPD-Q was leached from dust particles within a few hours, with a log partitioning coefficient between organic carbon and water (KOC) of 3.2–3.5. The present results will help to understand the environmental occurrence, fate, and behavior of 6PPD-Q.

Opportunities and Barriers for Truck Platooning on Norwegian Rural Freight Routes

Truck platooning can potentially make road freight transportation safer and greener. Technological readiness, business opportunities, and acceptance of truck platooning have mainly been studied for multilane highways with ample truck volumes. Less is known about truck platooning in areas with low traffic volumes and challenging roads and weather conditions. This paper investigates the opportunities and barriers for truck platooning on Norwegian rural freight routes, through stakeholder interviews and realistic case examples. Given modest freight volumes, dispersed industry clusters, and challenging road conditions, this study identified several prerequisites to deploying platooning and achieving economic savings. The paper discusses the future steps required to organize platooning across carriers, ensure appropriate infrastructure, and gain acceptance among truck drivers, motorists, and other road users.

Impacts of Real-Time Traffic State on Urban Expressway Crashes by Collision and Vehicle Type

With the rapid development of urban expressway systems in China in recent years, traffic safety problems have attracted more attention. Variation of traffic flow is considered to have significant impact on the safety performance of expressways. Therefore, the motivation of this study is to explore the mechanism of how the variation of traffic flow measurements such as average speed, speed variation and traffic volume impact the crash risk. Firstly, the crashes were classified according to crash type and vehicles involved: and they are labeled with rear-end collisions or side-impact collisions, they are labeled with heavy-vehicle related collisions or light-vehicle related collisions as well. Then, the corresponding crash data were aggregated based on the similarity of traffic flow conditions and types of crashes. Finally, a random effect negative binomial model was introduced to consider the heterogeneity of the crash risk due to the variance within the traffic flow and crash types. The results show that the significant influencing factors of each type of crashes are not consistent. Specifically, the percentage of heavy vehicles within traffic flow is found to have a negative impact on rear-end collisions and light-vehicle-related collisions, but it has no obvious correlation with side-impact collisions and heavy-vehicle-related collisions. Average speed, speed variation and traffic volume have an interactive effect on the crash rate. In conclusion, if the traffic flow is with higher speed variation within lanes and is with lower average speed, the risk of all types of crashes tends to be higher. If the speed variation within lanes decreases and the average speed increases, the crash risk will also increase. In addition, if the traffic flow is under the conditions of higher speed variation between lanes and lower traffic volume, the risk of rear-end collisions, side-impact collisions and heavy-vehicles related collisions tend to be higher. Meanwhile, if the speed variation between lanes decreases and the traffic volume increases, the crash risk is found to increase as well.

Experimental studies on pervious concrete reinforced with polypropylene fiber

We conducted strength tests on pervious concrete reinforced with polypropylene fibers as the part of the study. The goal of this study is to improve pervious concrete's mechanical qualities. Pervious concrete is one of the method of producing light weight concrete that is formed by completely ignoring fine aggregates (FA) or adding a limited amount of them in the mix. Pervious concrete offers qualities that allow it to be utilized as a stiff pavement for roads with low traffic volumes. The need for fine aggregate has risen in recent years. Pervious concrete is made by combining aggregates, cement, and water without including fine aggregates. In this investigation, a 4:1 aggregate cement ratio and a 0.45 water cement ratio were used. Polypropylenes were added to the cement in quantities of 0.5 percent, 1 percent, and 1.5 percent by volume. After 7 days and 28 days, mechanical properties were determined. In these strength tests, we found that 1 percent mix is ideal for compressive strength and 0.5 percent mix is for optimum tensile strength.

Determination of polycyclic aromatic hydrocarbons extracted from lichens by gas chromatography–mass spectrometry

Lichens are well-known biomonitors for semi-volatile pollutants, due to their ability to absorb and retain different chemical compounds such as Polycyclic Aromatic Hydrocarbons (PAHs), directly linked to levels in the atmosphere. Based on that, this paper proposes an analytical method capable of quantifying 16 EPA-PAHs from lichens found in an intertropical zone, as a natural alternative to typical capture methods, with the aim of monitoring atmospheres polluted by toxic compounds. An analytical protocol, including sample pre-treatment, followed by ultrasound extraction, clean-up in a chromatographic column, concentration and quantification by Gas Chromatography-Mass Spectrometry (GC-MS) using Selective Ion Monitoring has been developed. Additionally, a set of guidelines on lichen collection and sample handling is given, in order to achieve representative samples.•Limits of quantification (LOQ) and detection (LOD) varied from 2.0 to 16 µg/L and 1.0 to 5.0 µg/L, respectively. Calibration curves had correlation coefficients higher than 0.99 in all cases.•Validation of the method for determining PAHs concentration associated to 30 lichen samples collected along two roads, with high and low traffic volumes was carried out.•The method showed good performance according to the sources of PAHs, traffic patterns and gradient in roads.

Application of GIS to assess the accessibility of urban streets in Baghdad city

Accessibility has an important impact on shaping human activity patterns on all of the spatial scales. This study presented an evaluation of accessibility levels with private to commercial centers for three selected routes in Baghdad city. The study involved more than 45 days transport survey for private vehicles in Baghdad city using Global Positioning System (GPS) probe for recording indicators of traffic performance. Gravity model was used to measure accessibility index as an implementation of GIS-based model by using link geography and the spatial boundary of analysis in order to build route networks at three routes in Baghdad City, Bayaa intersection - Bab Al-Muatham intersection (Route 1), Bayaa intersection - Bab Al-Muatham intersection (Route 2) and 14 Ramadan Street - Bab Al-Muatham intersection (Route 3). It was found that Route 1 has the high accessibility index with 0.67 in compare with Route 2 and 3 (0.58 and 0.59), respectively. The reason that Route 1 had the highest accessibility index due to the high access point and low traffic volume as compared with the other two routes.