Traffic Volume Levels Research Articles

Analysis of Level of Service (LOS) of Urban Roads Using Multiple Linear Regression Models

Population growth and economic growth cause a person's mobility to increase. Sutomo Street, Pematangsiantar City is one of the roads that is quite congested because Sutomo Street is the center of Pematangsiantar city. The existence of the largest shopping center in the city of Pematangsiantar, which is Horas Market, causes a high level of community mobility around Horas Market. This research aims to determine the traffic volume, road capacity, and Road Level of Service (LoS) based on PKJI 2023, as well as knowing the relationship model and effect of traffic volume and road capacity on the Level of Service (LoS) of Sutomo Street, Pematangsiantar City using multiple linear regression methods with the help of IBM SPSS Statistics software. This research was carried out from Monday to Saturday at 07.00-19.00 WIB on Sutomo Street, Pematangsiantar City, which is precisely in front of the Pasar Horas, Building I, 200 meters long. Data collection on traffic volume and side obstacles is carried out with the help of cameras. From this research, it was found that the highest degree of saturation occurred on Saturday, 02 September 2023 at 12.00-13.00 WIB with a traffic volume of 2380.2 SMP/hour and a road capacity of 4161.6 SMP/hour so that the degree of saturation (Dj) was 0.57 with the road Level of Service (LoS) value being C (stable volume, speed influenced by traffic). The effect of variables X1 (traffic volume) and X2 (road capacity) can be explained simultaneously on the largest variable Y (degree of saturation) which is 99,8% with the multiple linear regression model equation, which is Y = 0,468 + 0,000222X1 – 0,000103X2. Based on partial and simultaneous hypothesis testing, Ho is rejected so that there is an effect of the independent variable on the dependent variable. This means that variables X1 and X2 effect variable Y.

Component, design, and prospects of self-consistent energy systems for transport infrastructures

ABSTRACT This paper introduces a Transportation Self-Consistent Energy System (TSCES) to meet the increasing electricity requirements of transport infrastructure in various traffic environments, including highway, railway, and waterway. The TSCES consists of four primary components: power source, load, energy storage, and interconnected microgrid. The power source component can be categorized into natural energy endowment and energy-electricity conversion components. Load components can be classified, quantified, and forecasted based on diverse transportation facilities, traffic volume, and importance levels. Energy storage components necessitate thorough consideration of the technical attributes of various energy storage methods, along with the functional requirements of the traffic environment, power sources, and loads. Interconnected microgrid components establish connections among all components, followed by configuration optimization and choosing appropriate network topological structures based on techno-economic conditions, ensuring that all components adhere to constraints imposed by transportation space, regulations, and policy indicators. Additionally, the design procedure and architectural patterns of TSCES are presented, which indicates that the TSCES has excellent adaptability and research application value in the field of transportation.

EcoMRL: Deep reinforcement learning-based traffic signal control for urban air quality

As greenhouse gas (GHG) emissions from road networks significantly impact the urban environment, there has been a growing interest in integrating environmental factors into traffic controls. Traffic signal control (TSC) is an effective method to reduce air pollution by managing traffic congestion. Accordingly, several recent studies have applied artificial intelligence to TSC to improve traffic efficiency. Despite these efforts, there are a few limitations on the existing studies. First of all, a number of recent studies focus only on traffic performance rather than environmental effects. However, in some cases, the objective function related to traffic efficiency can have an adverse effect on the environment. Furthermore, the variable nature of emissions based on traffic demand is rarely considered. To address these issues, we propose a multi-agent deep reinforcement learning-based TSC to minimize GHGs in traffic networks. To this end, we first identify vehicle’s stop and delay as key factors in traffic efficiency that critically influence air quality. Subsequently, we integrate these factors into our model’s reward function. To validate the proposed model, we conduct experiments under various demand scenarios featuring different traffic volume levels. The results show that the proposed model outperforms comparative control methods in two aspects: traffic performance and environmental sustainability. Especially at a high congestion level, the proposed model reduces average delay time by 11.9–16.1% and increases total throughput by 11.5%. Additionally, it significantly lowers total CO2 emissions by up to 8.9% and average emissions by up to 18.3%.

Research on the Setting and Control Method of Centrosymmetric Short Straight Lanes for Signalized Intersections

A new traffic organization method has been proposed to address the issue of traffic congestion caused by oversaturation through traffic during peak hours at signalized intersections. This method involves the installation of approximately centrosymmetric short straight lanes (CSSLs) to facilitate the passage of through vehicles, aiming to improve the traffic efficiency at signalized intersections. Firstly, two types of intersection designs with CSSLs were investigated, along with their operational principles. Secondly, a capacity model for the CSSL was established, taking into account the probability theory and mutual blockage considerations, as well as a delay model based on vehicle accumulation under oversaturated conditions. Finally, the intersection of Nanxu Road and Huangshan South Road in Zhenjiang City was chosen as an example. A simulation scheme was designed using VISSIM software to evaluate the effectiveness of the proposed method by implementing CSSLs before and after the intersection. The simulation results indicate that this method effectively increases the capacity of the oversaturated intersection approaches at the intersection and reduces the average delay. Under different lengths of short through lanes and utilization rates, the capacity of the eastbound short through lane and its adjacent lane increased by 20.7%, and the average delay decreased by 14.2% in all cases. Furthermore, a sensitivity analysis was conducted to examine the impact of short through lane capacity and the number of short through lanes on intersection capacity under different traffic volume levels. This analysis provides further insights into the influence of the CSSL on intersection capacity.

Air pollution hindering a transit-oriented city: Examining the association of particulate matter concentration with public transit ridership and road traffic in Seoul, South Korea

In high-density metropolitan areas prone to air pollution, public transit may be less preferred when air quality is poor due to the difficulty of avoiding outdoor air exposure during their use. By applying seemingly unrelated regression models, we examined the association of particulate matter (PM) with both public transit ridership and, as an alternative to sharing vehicular traffic demands, private car road traffic in Seoul from 2015 to 2018. To control for fluctuations in ridership and road traffic associated with seasonalities such as the day of the week, we used nine-term moving averages transformed into residual form. Results show that higher PM concentration was negatively associated with not only transit ridership, but also road traffic volume and congestion level; yet, the reduction in subway ridership was found to be larger than that in road traffic. This suggests that (1) when PM concentration is severe, people could reduce overall travel rather than change travel modes from public transit to private cars, thus implying that both modes are complementary rather than substitutionary in terms of responding to air pollution; and (2) public transit still seems more susceptible to air pollution than private cars. The findings help us understand the adverse effects of air pollution on public transit use as well as better predict and respond to demand for public transit in poor atmospheric conditions, thereby providing future policy directions for sustainable transportation planning.

SINGLE CROSS-BORDER FREE ROUTE AIRSPACE CONCEPT IN THE ASEAN REGION

Single Cross-Border Free Route Airspace (FRA) represents the ultimate long-term idealistic routing rules allowing airspace users freely plan a route in en-route airspace, which is not immediately possible from the administrative and technological point of view. In Single Cross-Border FRA, the whole ASEAN airspace is treated as a single-large FRA where all 12 Flight Information Regions (FIRs) implement FRA, with direct routing between the entry (horizontal entry into FIR or end of Standard Instrument Departure Route, SID) and the exit (horizontal exit from FIR or beginning of Standard Arrival Route, STAR). Single Cross-Border FRA is the most fuel-efficient reference that we could ever reach in the future.All otherhypothetical routing rules fall between the Single Cross-Border FRA and those hypo-thetical routing rules in terms of fuel efficiency. In this paper, we described the potential in fuel efficiency (or benefit achievement scaling) with refer-ence to this ultimate basic fuel requirement and scaled the excess fuel with different routings. We evaluated the fuel burn with a fast-time simulation (FTS) in 12 different scenarios (3 traffic volume levels × 4 routing scenarios). As for the traffic volume scenarios, we simulated 1-day of commercial ASEAN flight schedule data of 3 traffic volume levels (100%, 150%, and 200% of pre-COVID19 traffic volume). As for four routing scenarios with increasing levels of directness: conventional Air Traffic Service route network (ATS) (R1), hypothetical Several-Small FRA route network (R2), Single Cross-Border FRA route network with Danger Areas (R3) and Single Cross-Border FRA network without Danger Areas (R4). Results showed that flight time, fuel burn, and distance travelled were less in R2, R3, and R4 than in R1. There was an average difference of 2.2% in flight time, 1.9% in fuel burn, and 2.2% in distance travelled from R1 to R4.

ANALISA PEMBOROSAN BAHAN BAKAR MINYAK AKIBAT KEMACETAN PADA RUAS JALAN DI KOTA MATARAM (STUDI KASUS JALAN DR. WAHIDIN REMBIGA KOTA MATARAM)

The increase in the population of Mataram City resulted in an increase in traffic volume, due to the increase in the use of private vehicles for various community activities. This is the cause of traffic problems, especially congestion on several road sections, one of which is the Rembiga Road Section. Congestion causes losses to road users, judging from the use of vehicle fuel oil. In connection with this problem, research was conducted with the aim of finding out how much waste of fuel oil caused by congestion. Analysis of vehicle fuel oil consumption using PdT-15-2005-B Highways guidelines and analysis of vehicle fuel oil waste by determining the difference in the value of fuel oil consumption, congestion current conditions and free flow conditions. From the results of the analysis, it was found that the value of fuel oil waste on Monday 341 lt / km / day with fuel costs of Rp. 3,242,056.00 / km / day, Saturday 240 lt / km / day (Rp. 2,294,864.00 / km / day) and Sunday 135 lt / km / day (Rp. 1,296,993.00 / km / day). On Monday there is a high waste of fuel oil due to rush hour heavy traffic volume and high level of side obstacles, so travel time increases due to low vehicle speed.

ASSESSMENT OF ROAD TRAFFIC NOISE IN SELECTED URBAN RESIDENTIAL AND CONSTRUCTION AREAS

The work presented in this paper includes a field investigation of road traffic noise between residential and construction areas in a selected urban area. The aim of this study was to assess the level of noise pollution from road traffic noise in Seri Kembangan, Selangor. Therefore, this study included measurements of traffic noise level, evaluation of the percentage traffic volume between residential and construction areas; and identification of the correlation between traffic volume and traffic noise level. An EXTECH 407764 sound level meter was used to take noise level measurements for 1 hour and 30 minutes in one-minute intervals at both study sites. The parameter collected in the noise level monitoring was average noise level (LAeq). The traffic volume study was conducted using manual counts for 30 minutes. Four types of vehicles were counted, namely cars, vans, motorcycles, and heavy vehicles. Based on statistical analysis, it can be concluded that both sites had high traffic noise levels which exceeded the maximum permissible limit of 60 dBA during daytime, according to Malaysian guidelines, due to several factors. The findings show that road infrastructure such as noise barriers need to be further implemented, especially in residential areas. Mitigation of noise pollution must be further carried out by contractors. Additionally, further investigations need to be conducted by the relevant authorities to reduce the level of noise which may affect the quality of life for the communities in the area.

Factors Affecting Traffic Noise and Annoyance from Different Types of Roads: A Case Study in Nakorn Pathom Province, Thailand

This study investigated factors associated with road traffic noise and residents’ annoyance from three distinct types of roads (major arterial, minor arterial, and collector roads). Nine sampling locations in Thailand’s Nakorn Pathom Province were chosen for the measurement of noise levels and three contributing characteristics: traffic volume, vehicle speed, and the proportion of heavy to total vehicles. Along with a housing survey, face to face interviews with a total of 387 roadside dwellers recorded their sociodemographic data, activity-based locations, and noise impacts experienced. A statistical analysis based on Spearman correlation revealed a positive relationship between traffic volume and traffic noise level on major arterial (r=0.607) and collector roads (r=0.885). Residents around collector roads were more sensitive than those along the main arterial road, in spite of having lower noise levels and less intense traffic patterns. Longer housing setbacks appeared to be a key factor in reducing noise annoyance from all road types, according to an exact logistic regression analysis (OR=0.11, 95% CI: 0.003, 0.73 for the major arterial road; OR=0.29, 95% CI: 0.10, 0.78 for the minor arterial road; and OR=0.32, 95% CI: 0.12, 0.84 for collector roads). However, performing activities in closed areas (OR=0.05, 95% CI: 0.01, 0.17 for the minor arterial road; OR=0.22, 95% CI: 0.54, 0.90 for collector roads) and living in soundproof structures (OR=0.05, 95% CI: 0.001, 0.31 for collector roads) played additional roles to reduce the annoyance of residents along the roads with shorter setback lines.

Location-specific demand forecasting for park and ride lots: The use of models in practice

The management of hundreds of Virginia park and ride lots requires substantial public investment, and forecasting their demand helps agencies use scarce resources to improve multimodal mobility. Unfortunately, direct application of existing demand estimation approaches yielded errors typically 14 to 141 times the mean occupancy of a lot. Accordingly, this paper reports on the development of 19 regional models that yielded an average demand forecasting error of 0.56 times the mean occupancy.Because of Virginia’s geographic diversity, the most appropriate forecasting technique varies by region: in some cases, the key step is to group lots by commuting boundary or population density; in other cases, diverse socioeconomic variables (e.g., population, commuting distance, rent relative to income); facility-specific variables (e.g., transit availability, lighting); or traffic characteristics (e.g., volume on the road serving the lot, highest roadway volume within 2.5 miles) were needed to improve model performance. Ultimately, such variables explained on average 76% of the variation in lot demand. In practice, the results demonstrated the necessity of regional calibration: in rural southwest Virginia, for instance, the only key determinants of demand were the number of commuters living near a lot and having a job more than 50 miles away. In the more urban area that encompasses the state capital (Richmond), the two determinants were traffic volume and congestion levels. Although the models themselves are not transferrable, the methodology underlying their development can be used by other agencies as the data and techniques are publicly available.

An Enhanced Cell Transmission Model for Multi-Class Signal Control

Existing multi-class cell transmission model (CTM) based methodologies for signal timing or traffic assignment may transfer prioritized transit vehicles from one cell to the next one before processing their preceding passenger cars. In addition, existing CTM-based methodologies process a proportion of a slow-moving transit vehicle in each time step. As such a portion of each transit vehicle remains in each cell and it never clears them. This paper presents constraints to project the position of transit vehicles based on the speed and cell occupancy variations between different classes of vehicles and incorporates them into the CTM. The resulting optimization program is a mixed-integer nonlinear problem. We used a distributed receding horizon control framework to solve it in real-time. The proposed formulation is executed in a simulated arterial street with four signalized intersections in Springfield, IL with different traffic volume levels and transit vehicle frequencies. The results showed that the proposed algorithm addressed the mentioned issues of the existing multi-class CTM, and yielded more efficient network performance than the conventional transit signal priority-based (CTSP) systems. The proposed formulation reduced average bus delay by 1% to 70% and car delay by 52% to 76% compared to CTSP.

Modelling traffic safety at uncontrolled median openings: A case study in India

Assessment of traffic safety is an essential study in transportation engineering. In a developing country like India, around 150,000 people die in road crashes every year. Furthermore, at uncontrolled median openings, the severity of road crashes is higher due to the presence of impatient U-turning road users who don't obey the rule of priority. Traditionally, road crash data have been used since long to analyze traffic safety. However, in developing countries, the main drawback of this conventional method is limited availability of accident data as very few accidents get reported. Moreover, the accuracy of these reported data is questionable. Therefore, now-a-days, various surrogate traffic safety measures like Post Encroachment Time (PET), and Time to Collision (TTC) are being used to examine the safety of road users. Among them, PET is regarded as the most consistent, and most widely used safety indicator. Therefore, in the present study, PET across different traffic volume levels has been determined. Videography data has been collected from selected median openings located on six-lane divided urban roads. PET values for different traffic volumes, and different category of vehicles have been analysed in detail. Further, the distribution of PET values across the full width of road has also been studied. Concept of critical speed is introduced which is compared with conflicting speed to assess unsafe conflicts and determine a critical PET. Finally, regression models have also been proposed with good levels of accuracy to determine the PET values for various category of vehicles travelling at different conflicting speeds.

A spatially based machine learning algorithm for potential mapping of the hearing senses in an urban environment

• Four modes of hearing senses (normal, annoying, stressful, and pleasant) were examined in an urban environment. • The relationship between people's perceived hearing senses and spatial criteria was examined. • Spatial modeling and potential mapping of hearing senses were performed using a random forest (RF) algorithm. • The results showed that the RF algorithm had good accuracy in the potential mapping of hearing senses. Mapping individuals’ sense of hearing in the urban environment helps urban managers and planners accomplish goals such as creating a favorable urban environment for the citizens. The present study has been conducted to address the lack of modeling and compilation of a sense of hearing potential map in the urban environment and can help urban managers and planners make decisions in this regard. The present study aims for spatial modeling of people's hearing senses and developing potential maps for various hearing states in Tehran, Iran, using a random forest (RF) machine learning algorithm. The four various states, including pleasant sound, annoying sound, normal sound, and stressful sound, have been considered in the present study for the sounds that can be heard in the city. First, a spatial database made up of dependent, and independent data was built. Dependent data included people's four states of hearing in the urban environment, and the respective data was collected through a questionnaire from 657 people. Independent data were categorized into four groups. The first group was traffic related noises including the criteria of traffic volume and equivalent continuous sound level (Leq), the second group included land use related criteria of distance to cemetery, distance to sports areas, distance to commercial areas, distance to primary streets, distance to secondary streets, distance to park, and distance to industrial areas. Furthermore, the public facilities related group includes the distance to airports and distance to public transportation stations, and the population related group includes population density. 70% of the data were used for training, and 30% were set aside for validation. The spatial database was used to develop the potential map for the four states of the hearing sense in the urban environment using the RF algorithm. The potential hearing sense map was evaluated using the receiver operating characteristic (ROC) curve and the respective area under the curve (AUC). The AUC values were 0.930, 0.957, 0.950, and 0.903 for each of the pleasant, annoying, normal, and stressful states, respectively. There was a higher potential for pleasant sounds in the northern districts and some of the central ones, for annoying sounds mainly in the central districts, for normal sounds in central and southern districts, and stressful sounds in some parts of the central and mainly southern districts.

THE EFFECT OF SIDE FRICTION ON DELAYS IN ONE-WAY URBAN ROAD SECTIONS

The effect of side friction activities on delays due to the reduced free-flow speed was investigated by conducting a series of traffic surveys and referring to the 1997 Indonesian Highway Capacity Manual (IHCM) parameters. The movement of pedestrians, parking/stopping vehicles, vehicles entering and exiting the road, and the slow-and-stop motion of vehicles on the road sections was observed in video footage and analyzed to estimate the effect of side friction on the delays occurring. A weighting factor was used to determine the total value of side friction on the road to test the combined effect of all activities. This study used a regression model for estimating vehicle delays, as a performance parameter, on urban road sections, taking into account the effect of side friction on the road section's vehicle free-flow speed (FFS). It was found that vehicle speed decreased when side friction increased at all levels of traffic volume. Low side friction produced a higher vehicle free-flow speed (FFS), and analysis of the free-flow speed (FV) showed a lower vehicle free-flow speed (FFS) than that in the 1997 IHCM analysis. Delays at undersaturated inseparable one-way road sections (2/1 UD) with low to high side friction were described by the equation: Y = 0.002 X + 0.028 (R2 = 0.704) for Panca Usaha Road, and Y = 0.0022 X + 0.0104 (R2 = 0.774) for Pejanggik Road, where Y = Delay, X = Traffic Flow. The results of the above study indicate the existence of new performance parameters on urban road segment type 2/1 UD in the form of delay, and that can be an early indication as input in the update of IHCM 1997 and other research that the author has done before, as well as other authors who have also written about similar topics about this manual that is more than 20 years old (1997-2021), in analyzing the performance of road networks in Indonesia.

Impacts of Autonomous Vehicles on Traffic Flow Characteristics under Mixed Traffic Environment: Future Perspectives

Vehicle automation and communication technologies are considered promising approaches to improve operational driving behavior. The expected gradual implementation of autonomous vehicles (AVs) shortly will cause unique impacts on the traffic flow characteristics. This paper focuses on reviewing the expected impacts under a mixed traffic environment of AVs and regular vehicles (RVs) considering different AV characteristics. The paper includes a policy implication discussion for possible actual future practice and research interests. The AV implementation has positive impacts on the traffic flow, such as improved traffic capacity and stability. However, the impact depends on the factors including penetration rate of the AVs, characteristics, and operational settings of the AVs, traffic volume level, and human driving behavior. The critical penetration rate, which has a high potential to improve traffic characteristics, was higher than 40%. AV’s intelligent control of operational driving is a function of its operational settings, mainly car-following modeling. Different adjustments of these settings may improve some traffic flow parameters and may deteriorate others. The position and distribution of AVs and the type of their leading or following vehicles may play a role in maximizing their impacts.

Urban road traffic noise on human exposure assessment using geospatial technology

The sounds produced by humans, industries, transport and animals in the atmosphere that pose a threat to the health of humans or animals can be characterized as noise pollution. Adverse effects due to noise exposure can involve speech communication interference and declining learning skills of children. Highway traffic noise contributes to 80% of all noise. It has grown to a massive scale because of growth in population along the roads leading to a rapid change in land use and has evolved into a common reality in various Indian cities. The main objective of this work is to develop a road traffic noise prediction model using ArcGIS 10.3 for the busy corridors of Chennai. The collected data includes traffic volume, speed, and noise level in lateral and vertical directions. Noise levels were measured in 9 locations using a noise level meter. It is observed that the noise levels vary from 50 dB to 96 dB. It is found that the noise problem is severe in 18% of the area, and 6.3% of people are exposed to the traffic noise problem. The results obtained in this study show that the city is affected by severe noise pollution due to road traffic.

Contrasting wolf responses to different paved roads and traffic volume levels

In some regions of the world, large carnivores, such as wolves, persist in landscapes with dense networks of paved roads. However, beyond the general impacts of roads on wildlife, we still lack information on carnivore responses to different types of roads and traffic volume levels. Using wolves in NW Spain as a case study, we show how wolves respond differently to paved road classes depending on road size, speed limit and traffic volume. All wolves evaluated (25 GPS collared wolves) crossed paved roads. Overall, during 3,915 sampling days, we recorded 29,859 wolf crossings. Wolf crossings of all paved road classes were recorded at a mean rate of 0.022 crossings/day/km (95% CI 0.016–0.027). Wolves crossed low speed and low traffic volume roads more frequently, and more often during the night, in order to lessen the chances of encountering traffic. We found mortality to be highest on roads with high speed and high traffic volume. How wolves interact with paved roads should be considered in landscape planning strategies in order to guarantee wolf long-term persistence in human-dominated landscapes. In our case, our results support an increasing focus on primary roads (class II) to identify segments of these roads where road mitigation efforts should be prioritised. Our study also highlights the importance of considering paved road classes when studying the impact of roads on wildlife.

Evaluation of a New Intersection Design, “Shifting Movements”

Several unconventional designs have been suggested to enhance traffic operation and safety at intersections. However, the operational benefits of implementing some of them are achieved only under certain traffic conditions. For instance, the operational performance of the restricted crossing U-turn (RCUT) intersection design manifests only under highly unbalanced traffic conditions. The RCUT intersection outperforms conventional intersections that are subjected to high major traffic and light minor traffic volumes, while its operational performance fades at intersections with moderate to heavy minor road traffic. In this technical paper, a new innovative four-leg intersection design has been proposed to replace the RCUT intersection under moderate and heavy minor road traffic volumes. The new intersection design which has been named the “Shifting Movements” (SM) intersection has a low number of conflict-points compared with conventional intersections, but similar to the RCUT intersection. Therefore, similar safety benefits are expected to be achieved by the implementation of the SM intersection. Operational evaluations and comparisons between conventional, RCUT, and SM intersections have been conducted in the microscopic simulation environment. Different traffic volume levels and left-turn proportions have been assumed to represent the peak hour with moderate to high left-turn traffic. The results indicate that the SM intersection design significantly outperforms conventional and RCUT intersections that are subjected to high traffic volumes in average control delay and throughput.

The impact of shipping CO2 emissions from marine traffic in Western Singapore Straits during COVID-19

The maritime industry plays a key role in reducing greenhouse gas (GHG) emissions, as an effort to combat the global issue of climate change. The International Maritime Organization (IMO) is targeting a 50% reduction in GHG emissions by 2050 compared to 2008. To measure Singapore's progress towards this target, we have conducted a comprehensive analysis of carbon dioxide (CO2) emissions from the Western Singapore Straits based on the voyage data from Automatic Identification System (AIS) and static information from Singapore Maritime Data Hub (SG-MDH). Two methodologies, the MEET and TRENDS frameworks were applied to estimate the emission volume per vessel per hour. The data analysis results were next aggregated and visualised to answer key questions such as: How did the carbon emission level change from 2019 to 2020, in general, and for specific vessel types? What are the top vessel types and flags that had the highest carbon emissions? Did the traffic volume and emission level decrease during the Circuit Breaker period in 2020? The results of this study can be used to review Singapore's emission control measures and will be of value to the Maritime and Port Authority (MPA) of Singapore responsible for managing CO2 emissions at the Singapore Port.

Impact of Side Friction on Travel Time Reliability of Urban Public Transit

Travel time reliability is the key aspect that indicates the quality of urban public transit service. The studies on travel time reliability of the public transit system in Indian traffic conditions are few. Also, the impact of side friction elements on travel time reliability has not been considered in the previous studies. Hence, the present study aims to quantify the different types of side friction elements and analyse their impact on the travel time reliability of the public bus transit system. The field data consisting of side friction elements, traffic volume, and travel time of public bus transit have been collected and extracted at two different road sections (divided and undivided) in the Mysore city (Karnataka, India) during weekdays and weekends. The data are grouped into static and dynamic side frictions. An approach has been proposed to represent different types of side friction elements with a single index called the Side Friction Index (SFI) using relative weight analysis. Travel time reliability is represented using measures such as Buffer Time Index (BTI), Planning Time Index (PTI), Travel Time Index (TTI) and Reliable Buffer Index (RBI). The impact of side friction on travel time reliability was found to be sensitive to traffic volume, and hence the thresholds for different traffic volume levels have been determined using K-means clustering method. It was observed from relative weight analysis that the static side friction has a higher weightage (0.509 and 0.327 for the undivided road and divided road respectively) than the dynamic side friction elements in describing the variation of travel time. The impact of side friction on reliability measures at different traffic volume levels has been studied and found to have a non-linear (exponential) relationship. The impact of SFI has been observed to be higher on TTI and PTI in comparison with BTI. The study outcomes show that the impact of side friction on TTI and PTI is sensitive to traffic volume, especially at higher traffic volume level and impact of side friction on BTI is less, especially at medium traffic volume level. The inference from the study shows that the impact of side friction elements varies with respect to the type of road (divided and undivided), traffic volume levels, different days of week (weekday and weekend), and different time periods of day.