Highway System Research Articles

Exploratory Research on Drainage Structure of Highway Tunnel Based on Reducing the Risk of Crystallization Blockage

Crystal blockages of tunnel drainage systems severely undermine the tunnel lining structure and operation safety. In order to reduce the risk of crystal blockages of tunnel drainage systems, the distribution of highway tunnel defects was identified through a field survey, indoor test, and literature analysis, and an optimization method of tunnel drainage structures was proposed. The research suggested the following: (1) Lining water leakage and construction joint water leakage were the most common defects in the tunnel drainage system of Renhua–Xinfeng Expressway and Yingde–Huaiji Expressway in Guangdong Province, accounting for 60% and 32% of total defects, respectively. The number of defects that occurred in the drainage system of the tunnel was larger in the granite formation, with the number of road seepage and inspection chamber crystallization incidents reaching 2.5/km and 2.8/km, respectively. (2) The groundwater was mainly alkaline with a pH value of 8~12, Ca2+ (107 mg/L) was the cation with the largest ion concentration, and HCO3− (165 mg/L) was the anion with the largest ion concentration. The crystals in the tunnel drainage system were predominantly square, spindle, and rhombic calcite and aragonite composed of CaCO3, mixed with a small amount of sediment. (3) To reduce the risk of crystal blockages of the tunnel drainage system and ensure tunnel lining structure safety, a threefold optimization measure was proposed, namely, setting one-directional drainage pipes between the cable trench and the roadside blind drainage ditch, applying “π” type anti-crystallization drainage water-stop belts at the circular construction joints in the secondary lining, and both increasing the slope of the transverse drainage pipe and using an anti-crystallization drainage pipe. The research results will play an important role in guiding the design, construction, and maintenance of highway tunnel drainage systems in China.

Design of Taiwan High Speed Rail's Emergency Measures Using Petri Nets

Nowadays, high-speed trains (HST), called highspeed rail (HSR), are considered more energy-efficient or equivalent to other modes of transit per passenger mile. One main factor is that due to infrastructure design in many countries, highway and air travel systems are constrained, cannot expand, and are often overloaded. Based on the above situations, Taiwan High-Speed Rail (THSR) started being built in 2000 and started running in 2007, respectively. However, Taiwan is located in the Eurasian seismic zone, and many earthquakes occur every year. Undoubtedly, how to take correct emergency measures in THSR has become very important. It would cause incredible results if the emergency measure cannot efficiently and be fast enough to let every support units take their position, disperse the crowd and repair the rail immediately. Therefore, this paper tries to design the data flow of THSR's emergency measure using Petri nets. The final simulation results reveal that the proposed model is deadlock-free and practical.

Building a Strong Foundation for Public Health Transformation.

Building a Strong Foundation for Public Health Transformation.

On the Economic Impacts of Transportation Innovations: A Comprehensive Application to Quantifying the Impacts of an Hyperloop Technology

The purpose of this paper is to quantify the economic impacts associated with an investment in transportation systems. Here, we apply the methodology to projected comprehensive economic impacts of an Hyperloop route. The methodology is a low-frequency economic growth model that includes cumulative gains in real GDP, cost savings and the greenhouse gas savings of the proposed Hyperloop technology. To calibrate the model, we consider a route spanning from Texas to Chicago and covering 1,575 miles across the proposed hyperloop system. The infrastructure investment is obtained from construction cost estimates presented in previous feasibility studies. Our contribution is to present a simple general equilibrium approach to quantifying transportation economic impacts. To our knowledge, our is the first quantitative assessment of the Hyperloop technology. We include an analysis of the public finance aspects of the route, thus adding an answer to the question regarding the national merits of such an investment project. Our findings suggest that for returns comparable to the interstate highway system, the project could be paid for out of the stream of future tax revenues. There are additional gains through lower fares and travel times. Lastly, the environmental gains, especially from reduced air travel, are quantitatively significant.

GEOTECHNICAL INVESTIGATION OF BORROW PIT AS A SUBGRADE MATERIAL FOR ROAD CONSTRUCTION AT VICTOR ATTAH INTERNATIONAL AIRPORT, UYO, NIGERIA

One of the mass prompt practices of soils is for engineering projects such as the construction of roads, buildings, dams, and so on. Therefore, suitability of index and mechanical properties needs to be investigated. This study aims to determine the essential quality material required for road construction, thereby poses détente prospect for the disposal of ineffectual atrophy generated on sites. Such materials are classified into index and mechanical properties. Six subgrade samples were taken at the depth to bottom ranging from (1.0-5.0) m and tested. The sample was subdued to the laboratory tests, such as Sieve Analysis, Atterberg limits, compaction, California Bearing Ratio (CBR), and Specific Gravity (SG) respectively. The mechanical analysis which involved particle size distribution revealed that the subgrade was finely grated with a limit of ≤35% for subgrade passing sieve No. 200 (0.075 mm) with 29.1%, with an average Natural Moist Content (NMC) of 13.9%. The Maximum Dry Density (MDD) and Optimum Moisture Content (OMC) were 1.83 mg/m3 and 11.5%. The index analysis involved the liquid and plastic limits determination of Liquid Limit (LL) of 35.8%, Plastic Limit (PL) of 24.0%, and a Plasticity Index (PI) of 12%. California Bearing Ratio (CBR) results were 20.3% (soaked). The SG test results ranged from (2.68-2.94) kg/m3, employing the American Association of State Highway and Transport Officials (AASHTO) system of soil classification. The AASHTO grouped the materials into A-1, subgroups A-1-b and A-2-4 constituting 50% and 29.1%, with significant materials composed of stone fragments and sand rating the subgrade samples as excellent to good materials suitable for road construction.

Synchro Software-Based Alternatives for Improving Traffic Operations at Signalized Intersections

Traffic congestion is a considerable problem in urban arterials, especially at signalized intersections. Signalized intersections are critical elements of the highway system, thus improving their performance would significantly influence the overall operating performance of the system in terms of delay and level of service (LOS). The aim of this study is to assess the capacity performance of two signalized intersections in Duhok city, namely, Zari land intersection and Salahaddin Mosque intersection using the procedure in the Highway Capacity Manual and Synchro software. Total intersection delay, LOS, and volume to capacity ratio (v/c) were the measures of effectiveness used for comparison purposes. Different optimization alternatives have been tested to improve current and future performance. The results have shown that the Zari land intersection is currently operating at LOS F with an average delay of 590 s/veh and high values of v/c at specific movements. Results of optimization show that the scenario of creating an overpass with a change in cycle length and adding one additional lane in each direction is the best alternative to improve its performance to the LOS D with the maximum v/c ratio of 0.86. For Salahaddin Mosque intersection, the delay can be reduced from 544 s/veh (LOS F) with high values of v/c at the major street through movement to an average delay of 70 s/veh (LOS E) and maximum v/c ratio of 1, when cycle length and geometrics are changed, and approaching traffic from the minor street is prohibited.

Optimization Design and Performance Analysis of Improved IEEE802.11p MAC Mechanism Based on High Mobility of Vehicle

The high-speed movement of vehicles is the core factor affecting the rapid development of vehicular ad hoc network (VANET), especially the impact of vehicle mobility on data access and transmission performance. However, the classic IEEE802.11p data access and transmission protocol are still used in the multi-hop VANET under the highway system, which is adopted in the low-speed environment. Therefore, the impact of vehicle movement on the performance of the existing network is analyzed theoretically, and it is found that the network performance will be greatly reduced with the increase of vehicle speed. In order to improve the network performance in high-speed environment, an improved network access transmission protocol is proposed. Through Markov modeling, the analytic expressions of system delay, throughput, and packet loss rate are obtained. Finally, the effectiveness of the improved mechanism is verified by comparing the simulation results of two mechanisms.

High-performance optimal incentive-seeking in transactive control for traffic congestion

Traffic congestion has dire economic and social impacts in modern metropolitan areas. To address this problem, in this paper we introduce a novel type of model-free transactive controllers to manage vehicle traffic in highway networks for which precise mathematical models are not available. Specifically, we consider a highway system with managed lanes on which dynamic tolling mechanisms can be implemented in real-time using measurements from the roads. We present three incentive-seeking feedback controllers able to find in real-time the optimal economic incentives (e.g., tolls) that persuade highway users to follow a suitable driving behavior that minimizes a predefined performance index. The controllers are agnostic with respect to the exact model of the highway, and they are also able to guarantee fast convergence to the optimal tolls by leveraging non-smooth and hybrid dynamic mechanisms that combine continuous-time dynamics and discrete-time dynamics. We provide numerical examples to illustrate the advantages of the different presented techniques.

Simulation Analysis of Coupled Structural Vibration of Highway Railway Combined Bridge Induced by Overlapping Action of Vehicle and Train

In order to study the dynamic response of bridge coupling caused by the overlapping of vehicle and railway dynamic loads, by using the time-domain samples of pavement irregularity compiled by MATLAB software and the secondary development function of ANSYS software, the vehicle, bridge, and train models are established in ANSYS software at the same time, and the train supported beam bridge coupling program is compiled with MATLAB software. The model considers the influence of initial conditions and vehicle speed on the system before entering the bridge, the interaction between the coupled large-scale highway and railway bridge system, and the influence of different adverse factors on the system. The influence of a vehicle or train on the bridge structure when the vehicle or train passes through the continuous steel truss bridge under different factors is calculated, respectively, and the displacement and acceleration limits of the bridge are evaluated in combination with the corresponding specifications.

Real-time Automated License Plate Recognition using R-CNN

The extraction of vehicle license plate information from a picture or a succession of photographs is known as automatic license plate recognition (ALPR). Many applications, such as electronic payment systems (toll payment, parking fee payment), and highway and arterial monitoring systems for traffic surveillance, can use the extracted data with or without a database. The ALPR takes pictures with colour, black-and-white, or infrared cameras. The quality of the acquired photographs is critical to the ALPR's success. As a real-world application, ALPR must process license plates swiftly and successfully in a variety of environments, including inside, outdoors, day or night. It should also be generic enough to handle license plates from other countries, provinces, or states.

Review: Tokyo before Tokyo: Power and Magic in the Shogun’s City of Edo

Review: <i>Tokyo before Tokyo: Power and Magic in the Shogun’s City of Edo</i>

Vehicles Loads Influence on Box Girder Bridges

Abstract Box girders bridges are widely used in modern highway systems because of their efficiency and attractive appearance. Vehicles loads represent one of the mainly factors that influence the structure reliability of the box girders bridges. Calculation of bridge resistance with different stress due to vehicles loads as close as possible to the real ones constitute the premise of a correct design of the structure. The goal of this study is to realize a description regarding the behavior of box girders bridges analyzed under different vehicles loads conditions. Nowadays the finite element methods (FEM) are highly used because of their capacity to simulate and evaluate the structure efficiency of bridges. By highlighting where the maximum stress values appear we will help the constructor to avoid dangerous sections. Based on this study, we will outline future research directions, aiming to identify and improve the mechanical and strength characteristics of box girders bridges.

Criticality Trend Analysis Based on Different Types of Accidents using Data Mining Approach

Safety on roads and prevention of accidents are the prime concern of any highway system. Data mining is a source of retrieval of information for knowledge discovery approach. Many data mining methodologies have been applied to accident data in the recent past years. There is need to analyze the relationship between different factors related to accidents i.e. number of persons affected by fatal, minor, grievous, non-injury, road feature (ROF), road condition (ROC), cause of accident (CAU) and vehicle responsible (VR) according to daily, fortnightly, semi-fortnightly and monthly basis. The objective of this study is divided into three sub-objectives. The First sub-objective of this study is to divide number of accident dataset of National Highway sections of Karnataka state implemented by Project Implementation Unit i.e. PIU (Bangalore, Chitradurga, Dharwad, Gulbarga, Hospet and Mangalore) during January 2012 to January 2017 collected from NHAI (National Highway Authority of India) in homogeneous clusters using K-means clustering. The second sub-objective is to reflect the relationship between different factors i.e. a number of persons affected by fatal, minor, grievous, non-injury, CAU, ROC, ROF and VR using Apriori association rule. The last sub-objective is to perform temporal trend analysis for each cluster on the basis of rules generated by Association Rule Mining.

High Volume Freeway Travel Time Reliability and the COVID-19 Pandemic

This paper examines the effect of the COVID-19 pandemic on travel time reliability (TTR) performance on two high traffic volume freeway corridors (I-90 and I-405) in the U.S.A. Specifically, the travel time distributions (TTDs) during and before the pandemic are compared. The paper also examines which TTR metrics best capture the effect of the pandemic on reliability performance. There were statistically significant differences, at the 95% confidence level, between TTD in 2020 and corresponding TTDs in 2018 and 2019. Not surprisingly, all measures of central tendency and all measures of dispersions were reduced during the pandemic. Consequently, it was concluded that TTR performance improved during the pandemic regardless of what TTR definition was used. Travel time index (TTI), planning time index (PTI), and the level of travel time reliability (LOTTR) metrics improved during the pandemic, albeit at different rates. In contrast, the buffer index and coefficient of variation increased. In other words, whether an analyst would identify that TTR improved or decreased during the pandemic, and by how much, would be a function of which TTR metric was applied. Not surprisingly, the more congested the roadway section, the greater the impact the pandemic-related interventions had on TTR. It was found that, practically speaking, there are no differences in TTI, PTI, or LOTTR values when TTDs are formulated using a 5 min or 15 min aggregation interval. It was concluded that analysts need to have a deep understanding of the underlying TTD and the various TTR definitions when evaluating changes in freeway systems’ TTR.

Vehicle Detection and Counting for Toll Plaza

Many highway toll collection systems have already been developed and are widely used in India. Some of them contain manual toll collection, RF tags, barcodes and license plates recognition. All of these systems have drawbacks that lead to some errors in the corresponding system. At toll plaza, all lanes have a mixed lane system that is, both MTC and ETC. The delay and queue is mainly due to this two different charging methods vehicles pass through the same lane. In addition, with the help of collected data and visuals onsite investigation, some additional causes of traffic .Considering all these causes, this is the paper proposes solution to these problems. In this project we are using SSD_Mobilenet_V1 architecture. It uses the TenserFlow algorithm, which helps detect objects using images, videos, or CCTVs. It will contain study of areas such as Image processing, image enhancement. The proposed model can support government agencies to dynamically manage the toll plaza. It will help to tally all the cars at the end of the day to help avoid frauds which can conducted by the toll booth attendee.

The Value of Public–Private Partnerships

Public–private partnerships have withstood the test of time for centuries. Most large infrastructure projects and commercial innovations were brought to life with private investment, labor, and government support. The allocation of private capital with supportive fiscal and tax policies built the agricultural economy, brought about the industrial revolution, constructed the interstate rail and highway systems, developed the water and sewage public works projects that facilitated the development of urban centers, and developed the energy infrastructure supporting the high‐tech, clean energy economy. It is time again for the government to articulate its vision and harness the power of competitive markets to bring that vision to life.

A Network of X-Band Meteorological Radars to Support the Motorway System (Campania Region Meteorological Radar Network Project)

The transport sector and road infrastructures are very sensitive to the issues connected to the atmospheric conditions. The latter constitute a source of relevant risk, especially for roads running in mountainous areas, where a wide spectrum of meteorological phenomena, such as rain showers, snow, hail, wind gusts and ice, threatens drivers’ safety. In such contexts, to face out critical situations it is essential to develop a monitoring system that is able to capillary surveil specific sectors or very small basins, providing real time information that may be crucial to preserve lives and assets. In this work, we present the results of the “Campania Region Meteorological Radar Network”, which is focused on the development of X-band radar-based meteorological products that can support highway traffic management and maintenance. The X-band measurements provided by two single-polarization systems, properly integrated with the observations supplied by disdrometers and conventional automatic weather stations, were involved in the following main tasks: (i) the development of a radar composite product; (ii) the devise of a probability of hail index; (iii) the real time discrimination of precipitation type (rain, mixed and snow); (iv) the development of a snowfall rate estimator. The performance of these products was assessed for two case studies, related to a relevant summer hailstorm (which occurred on 1 August 2020) and to a winter precipitation event (which occurred on 13 February 2021). In both cases, the X-band radar-based tools proved to be useful for the stakeholders involved in the management of highway traffic, providing a reliable characterization of precipitation events and of the fast-changing vertical structure of convective cells.

Data Imputation for Detected Traffic Volume of Freeway Using Regression of Multilayer Perceptron

Traffic volume data are the important part of research and application of intelligent transportation systems (ITS). However, data loss often happens due to various factors in the real world, which may cause large deviations in prediction or bad accuracy of optimizations. Imputation is a valid way to handle missing values. A multilayer perceptron-multivariate imputation of chain equation (MLP-MICE) regression imputation method optimized by the limit-memory-BFGS algorithm is proposed, considering the temporal and spatial characteristics of traffic volume. Also, 32 groups of simulated imputation experiments based on the detected traffic volume of road sections in the Guangdong freeway system are conducted, which take the scenarios of continuous missing and jumped missing into account. The results of the experiments show that the MLP-MICE can optimize the imputation performance in the missing value of traffic volume with the MAPE of imputation results from 6.38% to 30%. Meanwhile, the proposed model has higher imputation accuracy for the traffic volume data with a lower degree of mutation. Lastly, the performance of the proposed model of imputation in short-term traffic volume prediction is discussed using the support vector machine. The results of it show that the MAPE of prediction under the proposed model is much lower than all-zero imputation. Therefore, the proposed model in this study is positive on improving the accuracy of traffic volume prediction and intelligent traffic control and management.

Generalized link cost function and network design for dedicated truck platoon lanes to improve energy, pavement sustainability and traffic efficiency

Recent development on autonomous and connected trucks (ACT) has provided the freight industry with the new option of using truck platooning to improve their fuel efficiency, traffic throughput, and safety. However, closely spaced and longitudinally aligned trucks impose frequent and concentrated loading on pavements, which often accelerates pavement deterioration and increase the life-cycle costs for the highway agency. Also, effectiveness of truck platooning can only be maximized in dedicated lanes, and its benefits and costs need to be properly balanced between stakeholders. This paper proposes a network design model to optimize (i) placement of dedicated truck platoon lanes and toll price in a highway network, (ii) pooling and routing of ACT traffic from multiple origins and destinations to utilize these lanes, and (iii) configuration of truck platoons within these lanes (e.g., lateral displacements and vehicle separations). The problem is formulated as an integrated bi-level optimization model. The upper level makes decisions on converting existing highway lanes into dedicated platoon lanes, as well as setting user fees. The lower level decisions are made by independent shippers regarding the choice of routes, use of platoon lanes vs. regular lanes, and they collectively determine truck traffic in all lanes. Link cost functions for platoon lanes are obtained by simultaneously optimizing, through dynamic programming, pavement rehabilitation activities and platoon configuration in the pavement’s life cycle. A numerical case study is used to demonstrate the applicability and performance of the proposed model framework over the Illinois freeway system. It is shown that the freight traffic is effectively channelized on a few corridors of platoon lanes and, by setting proper user fees to cover pavement rehabilitation costs, system-wide improvements for both freight shippers and highway agencies can be achieved.

An empirical study on fuel consumption of commercial automated vehicles

Increasing commercial vehicles are equipped with automated driving features. Adaptive cruise control, a critical longitudinal control system of commercial automated vehicles (AVs), may have significant impacts on fuel consumption. To investigate the impacts, this paper collected high-resolution trajectory data of commercial AVs with different operating scenarios, speed ranges, and headway settings on the highway system. The AVs’ fuel consumption was calculated by several state-of-the-art or classical vehicle fuel consumption models. From empirical analyses, we found that as the AV headway setting increases, the corresponding fuel consumption decreases. Also, we found that as the speed of AV traffic increases, the impacts of AV headway settings on fuel consumption decrease. Moreover, we compared the fuel consumption of AVs and human-driven vehicles (HVs). We found that for the same settings, the AVs always require less fuel consumption than the HVs. Following these findings, a set of managerial insights were provided into relevant stakeholders for future AV traffic.