High Traffic Volume Research Articles

Lessons Learned from the Construction and Initial Performance of a Double Chip Seal over a Paving Mat Pilot Project

Single chip seals are used by many agencies to maintain or preserve their roadways. While the construction and performance of single chip seals can be easily found from literature, the construction of double chip seals with and without paving fabric or paving mats is still not common. This paper investigates four double chip seal strategies used in a pilot project constructed on US 395 in Inyo County, California, by Caltrans. Within the double chip seal project limits, eight Performance Evaluation Sections (PESs) using four treatment strategies were established for detailed performance monitoring and evaluation: 1—a 3/8-inch asphalt rubber chip seal followed by a 1/4-inch PME chip seal without pavement-reinforcing fabric (PRF) or a paving mat as a control section; 2—a 3/8-inch PME chip seal over PRF, followed by a 1/4-inch PME chip seal; 3—a 3/8-inch PME chip seal over a paving mat, followed by a 1/4-inch PME chip seal; and 4—an asphalt rubber 3/8-inch chip seal over a paving mat, followed by a 1/4-inch PME chip seal. This pilot project was monitored during construction and evaluated 1 year later to help identify any construction issues and was used to improve the specifications and performance of Caltrans’ chip seals. This paper presents the initial findings following construction, and the one-year performance of the pilot project and lessons learned. The findings presented were accomplished by using these four treatment strategies on a highway with a very adverse high desert climate type and high traffic volumes. Project reviews are also planned for up to seven years to determine the long-term project performance.

RANKING PARENTS CONCERNS ABOUT ROAD SAFETY AT SCHOOL USING AN ANALYTIC HIERARCHY PROCESS

School road safety concerns include the drop-off location for children at the school entrance, traffic congestion around the school, and road safety amenities. Most research is done by analyzing data with descriptive statistics, but these don't give a clear order of the factors that lead to these incidents. So, the Analytic Hierarchy Process (AHP) has been used to help figure out which ways of intervening are the most effective at cutting down on accidents. The following objectives have been outlined: (i) to identify the most critical factors that contribute to road safety measures in the school area, such as high traffic volume, speeding, or a lack of pedestrian infrastructure, and (ii) to prioritize potential interventions for improving road safety. The study's methods include four main steps: making an instrument, collecting data, analyzing the data with AHP, and coming up with a list of actions to take based on priority. Results show that the most significant outcome was 33% peak hour management, and 33% of the needs of parent car management are equally critical. The other concerns are on the children's path. The outcome presented herein gives an insight into how to prioritize roads for safety mitigation, which is expected to be useful to various decision-makers.

Trend of traffic on inland waterways of Port Harcourt urban coastal environment: a comparative safety imperative for a Ghanaian coastal regional province

The purpose of the study is to compare mobility and access in Sub- Saharan Africa urban cities of Nigeria and Ghana by analysing trends and accident probabilities on the inland waterways to improve safety standards. Primary data from100 respondents through structured data and interview from boat and ferry operators were used. The responses were ranked on a four-point scale based on the selected routes’ average accident probabilities in percent: Very Safe {0-20}, Fairy Safe {21- 50}, Unsafe {51- 80}, and Very Unsafe {81- 100}. Secondary data from the National Inland Waterways Authority (NIWA) and Ghana Maritime Authority (GMA) and the Volta Lake Transport Company (VLTC) were subjected to probability, percentage and trend analysis. Results indicate that in the Niger delta for every journey there is approximately 59% likelihood of fatal accident; while on the Volta Lake there is a likelihood of 7% fatal accident occurrence. The trend of traffic was high in the Niger delta noticeably in the routes of Akwa- Ibom. Cross Rivers and Rivers State. The Volta Lake recorded high traffic volumes on the routes of Yeji,Tapa Abo and Bidi on market days while on non-market days, Makango. Kwamekrom and Kpechu had high passenger volumes. Estimated annual passenger traffic on the Niger delta routes outweighed that on the Volta Lake routes on a ratio of 4:1. Safety analysis further reveals that the water ways of Port Harcourt in Rivers state were unsafe for travel while the water ways of the Volta Lake were relatively safe as revealed by the average probability ratio of 8:1 in comparative terms. The log linear regression analysis reveals a price elasticity of demand for boat transport of 1.00 and 0.97 for the selected route of Port Harcourt Nigeria and Volta Lake, Ghana respectively. It further supports the fact that more passengers were responsive to travel by waterways in Nigeria than Ghana. The study concludes that waterways of Niger delta basin have high risk indices and likelihood of accident occurrence than the Volta basin; and recommends that VLTC and NIWA should invest optimally and partner with the private sector to enforce and regulate the waterways operations so as to increase safety and mobility of users of the waterways.

Analysis and Research on Interchange and Expansion options of Expressway

China's road network consists of numerous older expressways experiencing high traffic volumes and severe congestion necessitating urgent reconstruction and expansion efforts. This study discusses the reconstruction and expansion project of the Yinkun Expressway's Chongqing High-tech Zone to Rongchang District section with a detailed exploration of the entire design process. Through a comprehensive analysis the strengths and weaknesses of different plans are examined so as to determine the optimal plan. The design chosen saves costs while effectively addressing traffic demands. Additionally the study summarizes the valuable design insights gained from this interchange transformation aiming to provide valuable reference for similar interchange projects in the future.

Analisis Volume Lalu Lintas Pada Simpang Bersinyal Studi Kasus Persimpangan Jl. Rajawali – Jl. Hiu Putih Di Kota Palangka Raya

Crossroads are nodes in the road network where road segments meet and vehicle traffic trajectories intersect. At the intersection of Jl. Rajawali – Jl. Hiu Putih, traffic flow during peak hours will increase so it needs to be handled. The purpose of this study was to determine the traffic volume at the signalized intersection at Jl. Rajawali – Jl. Hiu Putih which will later be useful as information needed for the planning, design, management and operation phases of the road. The research method used is a direct survey in the field to obtain primary data in the form of road geometry, environmental conditions, and traffic volume. Secondary data is in the form of a map of field conditions around the intersection, and population data. Data collection was carried out for one week from Monday 05 September 2022 to Sunday 11 September 2022. The data taken was in the form of road width and the amount of traffic flow at each intersection. The research results obtained are the highest traffic volume at the intersection of four Jl. Rajawali – Jl. Hiu Putih is on Friday (north) approach of 256 lvu/hour, on Sunday (east) approach of 238 lvu/hour, on Monday (south) approach of 299 lvu/hour and on Thursday (west) approach of 142 lvu/hour. This data is used as an analysis to determine traffic volume. Data were analyzed using the Indonesian Road Capacity Guidelines (PKJI) 2014.

Contribution of non‐orthogonal multiple access signalling to practical multibeam satellite deployments

SummaryThis work explores the contribution of non‐orthogonal multiple access (NOMA) signalling to improve some relevant metrics of a multibeam satellite downlink. Users are paired to exploit signal‐to‐noise ratio (SNR) imbalances coming from the coexistence of different types of terminals, and they can be flexibly allocated to the beams, thus relaxing the cell boundaries of the satellite footprint. Different practical considerations are accommodated, such as a spatially non‐uniform traffic demand, non‐linear amplification effects and the use of the DVB‐S2X air interface. Results show how higher traffic volumes can be channelized by the satellite, thanks to the additional bit rates which are generated for the strong users under the superposition of signals, with carefully designed power levels for DVB‐S2X modulation and coding schemes in the presence of non‐linear impairments.

Centralized vehicle trajectory planning on general platoon sorting problem with multi-vehicle lane changing

Platooning of connected and autonomous vehicles has been extensively researched for its potential benefits in energy consumption, safety, comfort, traffic flow, and capacity. However, little attention has been given to the general platoon sorting problem of how to regulate the platoon to a desired formation and order. The problem poses a challenge as it involves multiple vehicles changing lanes in various directions, which makes them vulnerable to conflicts. This paper proposes a centralized trajectory planning method to address this problem. We construct a time–space-velocity network and formulate the problem as a multi-commodity flow model. To handle the large-scale network, we decompose the proposed model into several time-dependent least-cost path sub-problems using Lagrangian relaxation- and ADMM-based decomposition algorithms. Our method was tested through a series of experiments, which demonstrated its superiority in facilitating a faster and safer platoon sorting process compared to the existing method and achieving significant travel time savings at high traffic volumes compared to the simulations with SUMO.

Evaluating expressway traffic crash severity by using logistic regression and explainable & supervised machine learning classifiers

The number of expressway road accidents in Sri Lanka has significantly increased (by 20%) due to the expansion of the transport network and high traffic volume. It is crucial to identify the causes of these crashes for effective road safety management. However, traditional statistical methods may be insufficient due to their inherent assumptions. This study utilized explainable machine learning to investigate the factors that affect the severity of traffic crashes on expressways. The study evaluated two groups of traffic crashes: fatal or severe crashes, and other crashes that included non-severe injuries or only property damage. Five factors that contribute to crashes were analyzed: road surface condition, road alignment, location, weather condition, and lighting effect. Four machine learning models (Random Forest (RF), Decision Tree (DT), extreme gradient boosting (XGB), K-Nearest Neighbor (KNN)) were developed and compared with Logistic Regression (LR) using 223 training and 56 testing data instances. The study revealed that the machine learning algorithms provided more accurate predictions than the LR model. To explain the machine learning models, Shapley Additive Explanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME) were used. These methods revealed that all five features decreased the possibility of occurrence of fatal accidents. SHAP and LIME explanations confirmed the known interactions between factors influencing crash severity in expressway operational conditions. These explanations increase the trust of end-users and domain experts on machine learning models. Furthermore, the study concluded that using explainable machine learning methods is more effective than traditional regression analysis in evaluating safety performance. Additionally, the results of the study can be utilized to improve road safety by providing accurate explanations for decision-making processes for black-box models.

Automatically Refining Degraded and Occluded Lane Marking Information to Enhance the quality of High Definition Maps for Autonomous Vehicles

Autonomous vehicle technology has been advancing over the past decade with many challenges and obstacles. One obstacle to achieving fully autonomous driving is the feasibility of efficiently producing robust high definition (HD) maps of existing road infrastructure in a sustainable manner. HD maps are digital twins of road infrastructure that include 3-D representation of road features critical to a vehicle’s ability to navigate a road and maintain a consistent trajectory. This includes lane markings, barriers, and road edges. HD maps are often produced by first surveying roads using remote sensing technology. The collected data are then segmented using computer vision and machine learning algorithms to produce an HD map of the features of concern. One common challenge that is specific to extracting lane marking information is that the markings are occasionally occluded or degraded by high traffic volumes. This results in failure to detect lane markings and the existence of significant gaps in the extracted information. These gaps are manually filled in by quality control staff in a tedious and time-consuming process. To help overcome such challenges, this paper proposes a novel algorithm through which Kalman filtering is combined with Bézier curve fitting to automatically refine lane marking information. The proposed algorithm is tested on multiple roads where mobile lidar data were collected and segmentation was first applied using deep learning technology. The proposed algorithm was then used to refine the lane marking information which helped close all the gaps and recreate missing portions of the extracted lane markings.

Developing Sustainable Asphalt Mixtures Using High-Density Polyethylene Plastic Waste Material

There is growing interest in sustainable road pavement technologies to protect the environment and provide economic benefits. Post-consumer recycled (PCR) plastics are considered for construction to address the threat of plastic waste materials (PWM) and to improve sustainability. Asphalt pavement construction is highly considered for PWM recycling due to its large daily production. The purpose of this study is to investigate the performance of asphalt mixture containing PWM, specifically high-density polyethylene (HDPE), and compare its performance with two conventional mixtures. Three asphalt mixtures were considered: (1) mixture with asphalt binder PG 76-22 (SBS-modified); (2) mixture with asphalt binder PG 70-22 (SBS-modified); and (3) mixture with binder PG 67-22 and 3% HDPE (the plastic mixture). The rheological properties of the modified asphalt binders and the performance of the modified asphalt mixtures were evaluated. The long-term field performance of the pavements was modeled using AASHTOWare software (v.1.1.6) for the three mixtures considered. The results showed that all the mixtures were able to comply with the cracking threshold specified by the Louisiana Department of Transportation and Development (LaDOTD) for high-traffic volume roads. In addition, the plastic asphalt mixture showed similar performance to the one containing PG 70-22 (SBS-modified) asphalt binder.

Sensor based real time air pollutants monitoring for an urban industrial area


 
 
 
 Introduction: This study used economical sensors and an Unmanned Aerial Vehicle (UAV) to examine real-time air pollution assessment for an urban industrial area.
 
 
 
 
 Materials and methods: Using a DJI Phantom 3 Pro, the concentrations in the research area were measured. In the study, Carbon monoxide (CO) and Nitrogen dioxide (NO2) were measured using metal oxide sensors, and Particulate Matter (PM10) was determined using a dust smoke particle sensor. Pollutants were measured at heights of 0.8 m and 10 m for a period of one month.
 
 
 
 
 Results: With an increase in elevation, a gradual drop in pollutant concentration has been seen. High traffic volumes and fuel combustion are to blame for this increase. The concentration of CO, NO2 and PM10 at 0.8 m has been found to be 22.53%, 42.90% and 45.86% respectively higher when compared at 10 m. The main finding of this study is the use of an UAV integrated with sensors for vertical monitoring of the pollutant concentration.
 
 
 
 
 Conclusion: The CO concentration was found to be less than the standard value but near to it, when the data were compared to the Central Pollution Control Board (CPCB) standards. While it was discovered that the measured PM10 concentration was higher than the CPCB standard value, the observed NO2 concentration was determined to be lower than the standard value. Also, given that they produce satisfactory results, low-cost gas sensors can be employed to conduct concentration measurement studies.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Evaluasi Putaran Balik (U-Turn) Di Ruas Jalan G. Obos Kota Palangka Raya

Evaluate the U-turn on Jalan G.Obos Palangka Raya, to be precise the U-turn adjacent to the Temanggung Tilung intersection and the Galaxi intersection. The purpose of this research is to determine traffic performance on the U-turn, evaluate the distance between U-turns to intersections according to the geometric U-turn, and provide recommendations for improving road performance for U-turn facilities. Calculating the road performance level using vehicle volume data to get the road capacity. This data was obtained by direct observation/field survey. Road Geometric Data, Traffic Volume, where the data on the volume of vehicles at a specified location in a unit of time. Types of vehicles that can be classified are light vehicles (Kr), heavy vehicles (Kb), two-wheeled motorized vehicles (SM). Traffic performance on U-Turn A and U-Turn B from both sides 1 and 2 has an average value of C, which means: Flow with stable conditions but the speed and movement of vehicles is greatly influenced by higher traffic volumes, for density medium traffic due to increased internal traffic resistance, vehicles have limitations in choosing speed, changing lanes or overtaking. Traffic performance on U-Turn A and U-Turn B from both sides 1 and 2 get an average performance result with a value of C. The distance between U-turn openings is smaller than the standard distance of at least 500 meters, while the distance between U-turn -turn A and U-Turn B 282 meters, to improve U-Turn performance is to move the U-turn to fit the standard minimum distance

Application of non-excavation technology in the transition section of highway deep soft foundation road and bridge

Highway road and bridge transition section for the bridge and general roadbed combined with the lot, due to stiffness and deformation differences triggered by the bridge head jump phenomenon. For the deep soft foundation section, it is more serious. For the operation of highway bridge head jump phenomenon, the use of traditional excavation treatment measures can no longer meet the high traffic volume of road preservation needs. Non-excavation treatment is the technology developed under the demand, in the premise of not affecting the vehicle traffic, the bridge transition section treatment, for the high traffic volume of the in-service highway incessant treatment has a greater advantage. This paper proposes the non-excavation technology applicable to the transition section of highway road and bridge, and conducts comparative analysis on its economy, technology and feasibility, which can provide relevant engineering reference for the treatment of deep soft foundation section of bridge head jumping without continuity.

Infrastructure-Based Performance Evaluation for Low-Speed Automated Vehicle (LSAV)

This study assessed the limitations of the EasyMile EZ10 Gen 3 low-speed automated vehicle (LSAV) while operating on public roadways. The primary interest was to evaluate the infrastructure elements that posed the greatest challenges for the LSAV. A route was chosen that would satisfy a legitimate transit need. This route included more operational complexity and higher traffic volumes than a typical EasyMile LSAV deployment. The results indicate that the LSAV operated at a lower-than-expected speed (6 to 8 mph), with a high frequency of disengagements, and a regular need for safety operator intervention. Four-way stop-sign controlled intersections, three-lane roads with a shared turning lane in the middle, open areas, and areas without clear markings were the most challenging for the LSAV. Some important considerations include the need to have LSAVs operate on roadways where other vehicles may pass more safely, or on streets with slower posted speed limits. Additionally, the low passenger capacity and inability to understand where passengers are located onboard make it hard for the LSAV to replace bus transits. Currently, the LSAV is best suited to provide first/last-mile services, short routes within a controlled access area, and fill in gaps in conventional transits.

Avoiding Disputes in PPP Road Contracts: Quantifying Impacts of Increased Allowable Truck Loads

Dealing with changes is one major concern in long-term public-private partnerships (PPP) concessions, especially during the implementation phase, as some changes might lead to disputes between PPP partners and disrupt the successful execution of the project. In the transport sector, a change in the law regulating truck loading standards inevitably influences the financial stability of road projects procured through PPP. That is, the government’s decision of increasing the permissible truck load can lead to an accelerated deterioration of the pavement, and accordingly imposes additional expenditures that are borne by the concessionaire for maintaining the road condition at a satisfactory level, as required by the PPP contract terms. Given the fact that PPP concessions allow for additional compensations to the concessionaires in the case of modifications in the legislative and regulatory conditions, this study proposes two remuneration strategies for consideration by the concerned government to mitigate the adverse implications of increasing truck load limit on the concessionaire’s financial status and consequently to avoid the occurrence of disputes with the concessionaire. The work presented herein is twofold, as it quantifies the impact of the change in truck load regulations on two main contract terms: the toll regime and the concession period. Under the first approach, the government would provide direct compensation to the concessionaire through a shadow toll paid per overloaded truck. The value of the shadow toll was found to be largely influenced by the truck class, truck load, pavement structure, climatic conditions and traffic volumes. Moreover, it was found that the highest values of shadow tolls would apply to projects with relatively thin pavements and high traffic volumes. Under the second approach, an extension of the concession period was considered, which allows the concessionaire to recover the increased pavement maintenance costs. It was found that the length of the extended term depends, to a great extent, on the project’s characteristics in terms of the pavement structure, climatic conditions, traffic volumes, and more importantly on the toll revenues generated during the extended period. The two proposed alternative compensation techniques were devised and demonstrated through a methodology that involved flexible pavements performance prediction under varying loading conditions, using AASHTOWare Pavement ME. The proposed methodologies represent a framework that helps the two main parties involved in a PPP road project (i.e., the concessionaire and the highway agency) to accurately assess the effect of any increase in truck loading on the pavement performance and to decide on a fair compensation to be offered by the highway agency to the concessionaire, thereby contributing to the avoidance of dispute occurrence.

Motivational and deterrent effects of route attributes in cyclists’ route choice

Cyclists’ route choice is influenced by various route attributes as well as by individual characteristics or the purpose of cycling. Previous studies examined the extent to which those route attributes either motivate or deter to choose a certain route. However, one attribute, e.g. traffic volume, can both motivate and deter depending on the specific level, e.g. high vs. low traffic volume, and the effect of the levels may not be equal. Previous studies usually focused on either the motivational or the deterrent level. This study aims to compare both levels of several attributes, considering also individual factors and different cycling purposes. In an online questionnaire, (N = 169) participants were firstly separated into two trip purpose conditions by instruction (work vs. shopping). They were then presented with two routes representing the motivational and deterrent aspect of one attribute, and were asked for the maximum acceptable travel time for one route given the travel time of the alternative route and vice versa. Results indicate that commuter cyclists are more sensitive to deterrent aspects than to motivational aspects. In general, the gradient and the surface of a route have the highest impact, whereas advisory cycle lanes and traffic lights have the smallest. However, the impact of route attributes was influenced by individual aspects. This study is one of few that examined the impact of various route attributes by considering both the motivational and deterrent level of each attribute. It, thus, exceeds the existing literature by results of these effects and help to obtain a deeper understanding of cyclists’ decision to choose or avoid certain routes.

Solar Based Running Zebra Crossing System

An automatic road crossing system is crucial because in many developing and poor nations, the regulations and customs around crossing the street are not very strict. Additionally, the level of risk that is assumed around us on a daily basis only strengthens the case for an automatic zebra crossing system. This paper offers a straightforward, low-cost solution to this issue based on an Arduino-UNO-based system. Urban regions with high traffic volumes render pedestrian crossings dangerous. This essay seeks to prevent accidents from occurring when pedestrians are crossing at traffic lights. Because drivers disregard the signals, there are more collisions with pedestrians. The automatic barriers for the zebra crossing proposed in the study prevent these accidents. These barriers automatically rise when people are crossing and lower when cars are moving. The device can accurately measure the parameters required of an Automated Zebra Crossing system and is completely autonomous

Traffic flow modelling of long and short trucks using a hybrid artificial neural network optimized by particle swarm optimization

The significance of intelligent transportation systems and artificial intelligence in road transportation networks has made the prediction of traffic flow a subject of discussion among transportation engineers, urban planners, and researchers in the last decade. However, limited research has been done on traffic flow modelling of long and short trucks considering that they are among the major causes of traffic congestions and traffic-related accidents on freeways, especially freeway collisions between them and passengers’ vehicles. This study focused on the traffic flow of long and short trucks on the N1freeway in South Africa due to its high traffic volume and persistent traffic congestions caused by trucks. We obtained traffic data from this freeway using inductive loop detectors and video cameras. Traffic flow variables such as speed, time, traffic density, and traffic volume were identified, and the traffic datasets comprising 920 datasets were divided into 70% for training and 30% for testing. A hybrid ANN-PSO model was used in modelling the truck traffic flow due to its ability to converge to optimization quickly. The PSO's features (accelerating factors and number of neurons) assist in evaluating traffic flow conditions (traffic flow, traffic density, and vehicular speed). Also,PSO algorithms are simple and require few adjustment parameters. The results suggest that the ANN-PSO model can model long and short trucks traffic flow with a R2 training and testing of 0.999 0and0.993 0. This is the first study to undertake a longitudinal analysis of traffic flow modelling of long and short trucks on a freeway using a metaheuristic algorithm (ANN-PSO). The results of this study will provide knowledgeable insights (division of traffic flow variables and analysing of traffic flow data) to transportation planners and researchers when it comes to minimizing truck-related accidents and traffic congestions on freeways.

Effect of Surface Pavement Type on Traffic Noise

This paper investigates the issue of surface-type effects on traffic noise in Baghdad. Since the raw materials for both flexible and rigid paving are available from local sources, the decision on selecting the type of paving which depends on the budget of the project and the road's importance and function. Knowing that for high traffic volumes and a high percentage of heavy vehicles, rigid pavement is more suitable compared to flexible pavement. In Baghdad, some highways consist of flexible pavement and others of combined pavement (flexible segments and rigid segments), so the study of the effect of surface type on traffic noise becomes an important matter. This study selected three highways: one with flexible pavement and two with the combined pavement. The results showed that the traffic noise generated by traffic on rigid pavement generates more noise than traffic on flexible pavement by about 2 dBA. A prediction model was generated to predict traffic noise depending on five variables (vehicle speed, traffic volume, skid number, distance between the edge of the inner lane and the sound level meter, and surface type). The measured traffic noise levels ranged from 73.23 to 82.86 dBA, which exceeded the permitted limits compared to the permissible Iraqi standards.

Bi-level ramp merging coordination for dense mixed traffic conditions

Connected and Autonomous Vehicles (CAVs) hold great potential to improve traffic efficiency, emissions and safety in freeway on-ramp bottlenecks through coordination between mainstream and on-ramp vehicles. This study proposes a bi-level coordination strategy for freeway on-ramp merging of mixed traffic consisting of CAVs and human-driven vehicles (HDVs) to optimize the overall traffic efficiency and safety in congested traffic scenarios at the traffic flow level instead of platoon levels. The macro level employs an optimization model based on fundamental diagrams and shock wave theories to make optimal coordination decisions, including optimal minimum merging platoon size to trigger merging coordination and optimal coordination speed, based on macroscopic traffic state in mainline and ramp (i.e., traffic volume and penetration rates of CAVs). Furthermore, the micro level determines the real platoon size in each merging cycle as per random arrival patterns and designs the coordinated trajectories of the mainline facilitating vehicle and ramp platoon. A receding horizon scheme is implemented to accommodate human drivers’ stochastics as well. The developed bi-level strategy is tested in terms of improving efficiency and safety in a simulation-based case study under various traffic volumes and CAV penetration rates. The results show the proposed coordination addresses the uncertainties in mixed traffic as expected and substantially improves ramp merging operation in terms of merging efficiency and traffic robustness, and reducing collision risk and emissions, especially under high traffic volume conditions.