Highway Facilities Research Articles

A New Environmentally Friendly Utilization of Energy Piles into Geotechnical Engineering in Northern China

In the past 30 years, because of built-in advantages, energy saving, pollution control, and sustainability, the energy pile system has had a rapid development around the world. Many scholars did numerous researches on the parameters’ optimization, heat exchange efficiency, and structure-soil response. Also, the researches of evolutional GSHP system using high temperature in deep mine and lager collection surface of tunnel lining were learned. At present, most of researchers are discussing the geothermal collection for the heating or cooling the building, and plenteous and significant research achievements have been obtained. It is a novel attempt to apply energy pile to geotechnical engineering, and good results have been achieved in engineering practice in Northern China. The area of northern China is a typical seasonal frozen region: the high temperature in summer and the cold weather and accumulated snow in winter will result in huge challenge and resource consumption of maintaince on highway tunnel, pavement, and other geotechnical engineering facilities. In this paper, taking example of using the geothermal heat exchanger to melt snow, the novel idea of using energy piles to prevent track in summer and crack in winter of pavement, and guaranteeing the safety of frost crack on tunnel lining were discussed. Also, through simulation research, we propose a buried pipe form with good heat transfer uniformity-spiral buried pipe, which has better engineering applicability. This shows us that the application of energy pile in geotechnical engineering will provide solutions to geotechnical problems, which will have a brilliant future.

Overview of Intelligent Transportation System Safety Countermeasures for Wrong-Way Driving

Wrong-way driving (WWD) crashes are rare but tend to cause severe injuries and fatalities. When they occur, WWD crashes are mostly head-on and tend to be more severe than any other crash type. Currently, most efforts to mitigate WWD crashes focus on the application of intelligent transportation systems (ITS) technologies. Since the mid-1960s, many agencies have proposed and tested a variety of countermeasures ranging from the conventional, including improvements in signage and pavement markings, to the more advanced, based mainly on ITS. The application of ITS in detecting and deterring WWD crashes involves a combination of several components, such as detection, warning, and action. The main objective of this paper is to provide a comprehensive overview of ITS technologies implemented by different transportation agencies in the mitigation and prevention of WWD crashes. This study proves the importance of ITS technologies that have seen widespread application in recent years. Moreover, according to the evaluation studies of different ITS-related countermeasures, it shows that the countermeasures deployed have been effective in detecting wrong-way drivers and reducing the rate of wrong-way incidents. The results will provide insights for policymakers, engineers, and researchers into the application of ITS for reducing the severity and frequency of WWD crashes and other incidents on highway facilities.

Deep Learning and YOLOv3 Systems for Automatic Traffic Data Measurement by Moving Car Observer Technique

Macroscopic traffic flow variables estimation is of fundamental interest in the planning, designing and controlling of highway facilities. This article presents a novel automatic traffic data acquirement method, called MOM-DL, based on the moving observer method (MOM), deep learning and YOLOv3 algorithm. The proposed method is able to automatically detect vehicles in a traffic stream and estimate the traffic variables flow q, space mean speed vs. and vehicle density k for highways in stationary and homogeneous traffic conditions. The first application of the MOM-DL technique concerns a segment of an Italian highway. In the experiments, a survey vehicle equipped with a camera has been used. Using deep learning and YOLOv3 the vehicles detection and the counting processes have been carried out for the analyzed highway segment. The traffic flow variables have been calculated by the Wardrop relationships. The first results demonstrate that the MOM and MOM-DL methods are in good agreement with each other despite some errors arising with MOM-DL during the vehicle detection step due to a variety of reasons. However, the values of macroscopic traffic variables estimated by means of the Drakes’ traffic flow model together with the proposed method (MOM-DL) are very close to those obtained by the traditional one (MOM), being the maximum percentage variation less than 3%.

Factors affecting injury severity and the number of vehicles involved in a freeway traffic accident: investigating their heterogeneous effects by facility type using a latent class approach

The number of vehicles involved in a traffic accident can be representative of the severity of the accident and provide profound insight into the diverse factors affecting severity, which cannot be identified through the victim fatality rate. This paper presents an analysis and comparison between the effects of factors affecting injury severity and the number of involved vehicles. In this study, a latent class model was used to investigate the unobserved heterogeneity of the accident factors. Freeway facility types are latent factors that affect the heterogeneity of the effects of accident factors. The class mainly including accidents at the freeway mainline sections included more injury/fatal accidents and multiple-vehicle accidents and more significant accident factor estimation results than the other class including accidents at the tollgates or ramps. Among these factors, night-time, faults made by the driver, and heavy vehicle accidents were found to increase the accident severity. Investigating accident factors affecting both the injury severity and number of involved vehicles is important as the number of people who are injured or dead is likely to increase when multiple vehicles are involved in the accident.

Development of integrated asset management model for highway facilities based on risk evaluation

Highways are vital infrastructures that play a crucial role in providing social welfare. Highway structures could experience different types of deterioration (e.g. pavement ageing, pavement cracking, potholes, bridge structure deteriorations, and rockfall due to unstable slopes). Minimal attention has been directed towards developing a comprehensive model to effectively reduce the potential hazards for the entire highway network while considering the associated individual and overall risks. An integrated risk management model is used to separately assess each section's risk value and the extent of its impact on the network. An efficient model has been developed to identify the highway sections that its maintenance will effectively reduce the total risk within the highway network. The developed model competence is examined and verified after evaluating a four major highway network in Florida. The results of the highway's analysis were compared for all routes within the network. Also, the developed model's proficiency in optimally reducing the network's overall risk is presented. The proposed model could be utilized as a support-decision tool to decide which highway segments must be maintained to minimize the network's potential risk.

Freeway Network Travel Time Reliability Analysis Methodology and Software Tool Development

Applications in the field often require analysis of freeway travel time reliability (TTR) at the network level. While micro-simulation is suitable for performing network-level analysis, the computational burden can become unreasonable when TTR analysis is factored in. As for macro-simulation, most network analysis studies often use simplified link performance functions to represent the travel time and flow relationship. Such functions are not generally sensitive to the range of geometric and traffic conditions that can influence freeway facility operations. This research extends the Highway Capacity Manual (HCM) freeway TTR analysis methodology to the network level. The proposed freeway network TTR analysis methodology generates scenarios that represent the impacts of origin–destination (OD) demand variations, weather events, incident events, and work zone events on freeway network travel time. For each scenario, the methodology performs user equilibrium (UE) traffic assignment and the HCM freeway facility core methodology is applied to represent the travel time and flow relationship. The method of successive average approach is applied to solve the UE traffic assignment. Finally, scenario travel times (and/or other performance measures) are aggregated into various distributions of interest, such as the network-, facility-, and OD-level distributions, and TTR performance measures are calculated at the three different levels. A software tool is developed using C# language on the .NET Framework. The software tool provides a convenient and efficient approach for transportation planners and researchers to conduct the freeway network TTR analysis, which helps to bridge the gap between research and practice.

A Study on the Reduction Effect of Nitrogen Oxide in Photocatalyst using Highway Facilities

A Study on the Reduction Effect of Nitrogen Oxide in Photocatalyst using Highway Facilities

Hydrological ecosystem changes and impacts after the Zonag Lake outburst in Hoh Xil of Tibetan Plateau

After the iconic outburst of Zonag Lake in Hoh Xil of Tibetan Plateau (TP) in 2011, the causes of the collapse and its impact on the volume of water contained by the downstream lakes have highly been concerned, but the overall changes of the hydrological ecosystem and its impacts on the basin are yet not clear. This paper analyzes the hydrological system (lake area and hydrological connection) and ecosystem (sandstorm activity and vegetation growth status) changes and their impacts on the regional ecological environment after the outburst event, based on remotely sensed images from 2000 to 2020, meteorological observations, and field surveys. The results show that the outburst of Zonag Lake has not only changed the regional hydrology and ecosystem pattern but also caused a trend of degradation in the ecological environment of Zonag Lake Basin. Some lambing areas and active areas of Tibetan antelope in the area are being buried and eroded by the sandstorm. The downstream Yanhu Lake has risen to the highest level and overflowed through the emergency diversion engineering. These impacts are continuously threatening the health of the ecological environment of the world natural heritage site in Hoh Xil, the safety of Qinghai-Tibet highway, Qinghai-Tibet railway, and other engineering facilities, as well as the stability of fluvial geomorphology in the northern most sources of Yangtze River.

Influence of micropile parameters on bearing capacity of footings.

Micropiles, on account of their versatility, can serve as both a new foundation and a long-term option for prevailing foundations without disturbing the subgrade underneath. They can improve highway facilities, historically significant structures, or distressed structures. The present laboratory model study is conducted on a square footing installed with micropiles all around it and subjected to vertical concentric loading. A parametric analysis based on the impact of five micropile parameters is also performed. The results obtained from this study reveal that the inclination of micropiles has little effect on ultimate vertical load but can profoundly impact the horizontal load. As the diameter of micropiles is progressively increased from 10 to 20 mm, the bearing capacity improves by around 27%. As the micropile spacing decreases from five times diameter (5d) to three times diameter (3d), the footing system's bearing capacity increases nearly by 22.2%. The bearing capacity ratio shows a reduction beyond the value of L/b = 2. Installing micropiles nearer to the footing edge (ED/b = 0.3) provided approximately 76% improvement with respect to the unreinforced footing. The optimum value of the different parameters is equal to L/b = 2, d = 20 mm, ED/b = 0.3, and S/d = 3. There is a 98% improvement in bearing capacity at the optimum values for 30° inclined micropiles.

Modeling impacts of driving automation system on mixed traffic flow at off-ramp freeway facilities

This study aims to model a mixed traffic flow consisting of vehicles controlled by a driving automation system in the highway off-ramp system. The driving automation system includes no automation (NA), driver assistance (DA), partial automation (PA), and conditional automation (CA). Developing this model requires specifying the longitudinal and lateral driving characteristics of vehicles with different driving automation systems and then selecting appropriate car-following and lane-changing models. The proposed cooperative lane change model applied by CA considers the lane utility and car-following models of the following vehicles in adjacent lanes that can be obtained by vehicle-to-vehicle communication. The impacts of the market penetrations of PA and CA on traffic flow are investigated, and it is found that both PA and CA can improve traffic capability. Compared to PA, CA is more effective in improving the highway capacity near the off-ramp. The impact of CA on the headway indicates that CA enables vehicles that require changing lanes to find suitable gaps and changing lanes in a timely manner, which improves the capacity of the off-ramp and the overall freeway. By adjusting the lane change adventure factors, the contribution of CA to capacity can be further enhanced without compromising driving comfort and safety.

Discussion on operation safety and countermeasures of Highway tunnel Traffic Engineering Facilities

In order to further improve the condition of road tunnel traffic engineering facilities, and thus improve the safety of tunnel operations. The paper analyzes the inspection results of traffic engineering facilities in dozens of tunnels in China, and summarizes the common operational safety risks of traffic engineering facilities. Then puts forward corresponding risk prevention and control measures, which is helpful to improve the status of tunnel traffic engineering facilities. It has certain guiding significance for the safety management of road tunnel operation.

Evaluating the Effect of Incidents on Freeway Facilities and Updating the Incident Capacity Adjustments for HCM

This paper investigates the effect of incidents on freeway segment capacity. Currently, the Highway Capacity Manual (HCM) provides a look-up table linking the remaining segment capacity fraction during an incident to the total and closed number of lanes on the segment. In reality, segment capacity during an incident will tend to vary over time, with the most severe effects felt early on before any type of response is initiated, with congestion progressively improving as the appropriate incident management actions are implemented. By applying a genetic algorithm calibration method on each incident day and calibrating the incident capacity adjustment factors (CAFs), optimal time-dependent CAFs were derived that best represented the effect of incidents on the freeway segment capacity. By analyzing the optimal CAFs, the strongest relationship was revealed to be between the optimal time-dependent CAF and the temporal progression of the incident. A regression model was developed to represent this behavior. This was formulated in a manner that can directly adjust the current HCM’s fixed CAF values (for a specific lane closure configuration) for modeling incidents both in single day, seed file application, or for an entire year reliability analysis. A portion of WB I-540 in Raleigh, NC was selected as the study area in which the proposed method was tested. Between January 2014 and December 2018, the team identified 22 isolated incidents (away from the recurring congestion period) that closed one or two lanes of traffic, creating a distinct congestion pattern.

Research on Design Technology of Safety Facilities in Highway Traffic Engineering

In highway traffic, setting up the necessary traffic safety facilities can provide a guarantee for the safe driving of vehicles. To a certain extent, proper and reasonable setting of traffic safety facilities is an important indicator to measure the safety design of highway traffic engineering. In order to do a good job in highway traffic safety from the source, people gradually pay attention to how to improve the rationality of the design of highway traffic safety facilities. As people pay more attention to highway traffic safety facilities, their design technology has become an important research content to effectively avoid safety problems in highway traffic design, construction and operation, and reduce the high cost of subsequent upgrades. This paper takes the design technology of highway traffic engineering safety facilities as the research object, and analyzes the main structure of highway traffic road safety facilities and the main causes of safety problems on the side of highway traffic roads. On this basis, with the main purpose of effectively avoiding road traffic safety accidents and guaranteeing road traffic safety, targeted safety protection measures are provided. From the aspects of guardrail design technology, visual illusion deceleration marking design technology, warning signs and other aspects, research and discussion are carried out to provide a reference for effectively improving the overall level of traffic safety facilities design.

Predictive Model Construction for Smart Highway Facilities Deterioration Using Data Mining

Predictive Model Construction for Smart Highway Facilities Deterioration Using Data Mining

Modeling and Validating Traffic Responsive Ramp Metering in the Highway Capacity Manual Context

This paper presents a methodology for modeling traffic responsive (or adaptive) ramp metering in the freeway facilities method based on the sixth edition of the Highway Capacity Manual (HCM6). Currently, the HCM only provides an option to meter on-ramps as user input using 15-min average flow rates with a focus on planning-level analyses. As a result, the possibilities for simulating and modeling ramp meters with any traffic responsive ramp metering algorithm in the HCM context are limited. Moreover, the freeway facilities methodology in the HCM plays a vital role in the analysis of travel time reliability, which is built on a set of operational scenarios. However, with the lack of traffic responsive ramp metering, analysts are burdened with the task of manually entering average effective ramp metering rates for each on-ramp within the set of reliability scenarios. This process can require a substantial amount of time, in addition to increasing the potential for inaccuracy and bias in freeway and performance measure estimations. As a result, this paper is designed to fill a significant research gap by providing a method for analyzing traffic responsive (or adaptive) ramp metering, an active traffic and demand management strategy, using the core freeway facilities methodology in the HCM. The direct application of the method focuses on the MaxView metering algorithm. However, the proposed framework can be used to model any traffic responsive ramp metering algorithm. The results are validated using real-world sites located on the I-540 westbound freeway corridor in North Carolina.

Quantifying the Mobility Benefits of Express Lanes using Real-Time Traffic Data

Traffic congestion is one of the major problems facing transportation agencies, especially in urban areas. Agencies are exploring ways to use the existing transportation infrastructure efficiently by deploying appropriate traffic management strategies. One of these strategies is the use of express lanes, which are expected to effectively mitigate congestion and increase the reliability of highway facilities. Express lanes are managed toll lanes, separated from general-purpose lanes within a freeway facility. The goal of this study was to quantify the mobility benefits of express lanes by comparing the performance of express lanes with that of their adjacent general-purpose lanes, and by assessing the performance of the general-purpose lanes when the express lanes were open versus when the express lanes were closed. The Buffer Index (BI), a travel time reliability measure, was selected as the performance measure. The analysis was based on 95Express, express lanes along I-95 in Miami, Florida. Overall, the results indicated that BIs for the express lanes were significantly lower than the BIs for the general-purpose lanes, and the BIs for the general-purpose lanes were significantly lower when the express lanes were open compared with the periods when the express lanes were closed. The study results showed mobility improvements on both the express lanes and the general-purpose lanes, although the extent of the improvements varied by direction (i.e., northbound and southbound) and time of day (i.e., a.m. peak, p.m. peak, daytime off-peak, and nighttime off-peak). Transportation agencies may use these findings to quantify and evaluate the mobility benefits of the express lanes and the general-purpose lanes on express lane facilities.

Identification of contributing factors for interchange crashes based on a quasi-induced exposure method

Interchanges are important highway facilities by connecting two or more freeways/expressways; however, it has been considered more dangerous than basic segments because of drivers’ decision-making to stay or exit, weaving, variations in speeds, etc. In this study, we aim at contributing to the literature by using a quasi-induced exposure method and logistic regression modeling approach to identify contributing factors associated with the risk of causing an interchange crash. To this end, the 2014 traffic crash data, roadway and drivers’ characteristics were collected from Florida. The modeling results indicate that drivers’ age, gender, distraction, alcohol, and other factors have statistically significant effects. In addition, the finding suggests that drivers are more likely to cause crashes at cloverleaf and direct connection interchanges than at diamond interchanges. Furthermore, a support vector machine (SVM) model was applied to compare its predictability with the logistic regression model, and a sensitivity analysis was conducted. From the comparison of the areas under the receiver operating characteristic curve (AUC) of the two approaches, it shows that the SVM model outperforms the logistic regression model. It is expected that the findings would help establish effective strategies to reduce traffic crashes at interchanges by targeted education, engineering, and enforcement.

Safety Effects of Horizontal Curve Reliability Index

Recent advancements in analytical processes have used probabilistic approaches to examine the efficacy of the point mass model (and other Green Book models) to develop reliability-based approaches for geometric design. However, there has been minimal research establishing the link between reliability measures and substantive safety (expressed through crash frequency). The objective of this paper is to use empirical data supporting the calculation of reliability index for existing horizontal curves and to estimate the relationship between reliability index and crash frequency. Other horizontal curve-related characteristics that may have an impact on crash frequency on horizontal curves for rural two-lane highways and rural freeway facilities are controlled for in the evaluation. The safety analysis showed that the wet pavement reliability index was significantly associated with crash frequency for total curve-related crashes, single-vehicle run-off-road crashes, rollover crashes, truck-related crashes, and weather-related crashes. The relationship was strongest for the reliability index in its continuous form, meaning that the effect is continuous across the range of wet pavement reliability that was observed.

Victims of road accidents with serious injuries and dependence on some individual, climatic and infrastructure factors on federal highways in Brazil

Road or urban traffic accidents in Brazil have a large presence in external causes of mortality. The main goal of this study is to discover significant factors in the incidence of accidents on Brazilian highways based on a database with information on each person injured on federal highways in Brazil reported by the Federal Highway Police. Some factors are considered in the study as cause of the accident, type of accident, stage of the day, weather condition, highway type, highway facility, age of the victim, gender of the victim and type of vehicle. From the obtained results of chi-square tests and logistic regression models, it was observed statistical dependence (p < 0.05) of the occurrence of injured people with serious injuries and the factors cause of the accident, type of accident, day, highway type and vehicle type. Considering the dead victims, the covariates age, time of day, highway type, highway facility, gender and type of vehicle showed significance (p < 0.05). These results are of great interest for authorities to increase road enforcement, improve highway facilities and target the production of vehicles with better safety standards.

Safety and operational impact of connected vehicles’ lane configuration on freeway facilities with managed lanes

Managed lanes (MLs) have been implemented as a vital strategy for traffic safety and management improvements. Previous studies involving MLs didn’t examine the impact of connected vehicles’ (CVs) lane configuration on freeway facilities with managed toll lanes. CVs are quickly expanding in the transportation industry and are among the most recent promising developments in traffic and safety engineering. In this study, several scenarios were tested using microscopic traffic simulation to determine the optimal CV lane configuration strategies while taking into consideration the market penetration rate (MPR%) of CVs and traffic conditions (i.e., peak, off-peak). Both safety (i.e., conflict frequency, conflict reduction) and operational (i.e., average speed, average delay) performance measures were included in the analyses. A Negative Binomial model was developed for investigating the factors that affect the safety measures. Tobit models were used to evaluate traffic operation. The results of the safety and operational analyses suggested that an MPR% between 10 % and 30 % was recommended when the CVs were only allowed in MLs. By converting one of the general-purpose lanes (GPLs) to a managed lane, the MPR% could reach 60 %. It was also concluded that restricting CVs to only the CV lane was not recommended. Lastly, the findings suggested that by allowing CVs to use all the lanes in the network (MLs, GPLs and CV lane), the optimal MPR% could reach between 70 % and 100 %. This study has major implications for improving MLs by recommending the optimal CV lane configuration and market penetration rate for each design.