Journal of Traffic and Transportation Engineering-English Edition最新文献

The creep damage evolution of asphalt binder plays a significant role in investigating the formation mechanism of rutting. The rutting is the common distress at high temperatures for asphalt pavements. However, the reliability of existing creep damage parameters is under questioned, and these parameters cannot accurately illustrate the change of intrinsic microstructure for asphalt binder. In this paper, a new test protocol was given access to study the evolution of viscoelastic parameters during creep damage. It was completed by inserting the frequency sweep during creep test. The frequency sweep curve clusters were fitted by the generalized Kelvin-Voigt model for obtaining the change law of model parameters. Based on the change law and sensitivity analysis of model parameters, (E₂ + E₃)/2 was proposed as the creep damage variable. According to the curve of (E₂ + E₃)/2 versus loading time, two stages during the creep test could be identified: an approximate constant value in phase Ⅰ and a linear decrease in phase Ⅱ. Intrinsic differences about creep property of binders could be determined by this new proposed parameter. Above results not only ensure better understanding of the creep damage mechanism of binders, but also lay the theoretical foundation on predicting the anti-rutting performance of binders.

This review evaluated research results on polyvinyl alcohol fiber cement-stabilized macadam (PVA-FCSM) to further improve the long-term durability of road structures and promote its in-depth study and high-quality application. The suitable PVA fiber technical indexes for ordinary cement-stabilized macadam (CSM) were recommended. The difference in the mechanical properties between CSM and PVA-FCSM was described. The extent to which PVA fibers enhance the durability of CSM were clarified. Additionally, the mechanism of enhancement of CSM by PVA fibers was revealed. Finally, the performance of each type of fiber cement-stabilized macadam (FCSM) was compared and evaluated. The results indicated that the suggested PVA fiber length and content for CSM were 12–30 mm and 0.6–1.2 kg/m³, respectively. At different ages, the mean degree of improvement in the unconfined compressive strength was 14%, 20%, and 14%, that in the compressive resilience modulus was 8%, 11%, and 6%, and that in the splitting strength was 29%, 15%, and 22%, respectively. At different ages, the mean degree of decreased in the dry shrinkage coefficient was 21%, 16%, and 15% and that in the temperature shrinkage coefficient (20 °C–30 °C) was 23%, 23%, and 18%, respectively. The coefficients increased with extended curing age. Moreover, at the same stress level, PVA-FCSM has a higher fatigue life compared to CSM. The bridging effect, high strength, and high modulus of PVA fiber enhance the strength and anti-cracking of CSM. The recommended fiber type for CSM is PVA fiber.

The exact evaluation of the fusion rate of virgin and aged asphalt is essential to optimize the performance of the recycled asphalt mixture. The fusion rate index was developed by tracing the distribution of tracer asphalt, which contains nano-ferrous ferric oxide (nano-Fe₃O₄) tracer. Laboratory fusion simulation tests were performed on three types of asphalt to obtain different fusion states, and fatigue tests were performed to evaluate the influence of the fusion rate on the fatigue life of the recycled asphalt. It was found that the tracer asphalt containing 4% nano-Fe₃O₄ shows the optimal trace effect, and the developed fusion rate index can quantitatively characterize the influence of different factors on the fusion state of the recycled asphalt. The fusion state is closely related to the fatigue performance of recycled asphalt, and the fusion rate index can fairly evaluate its fatigue performance. The relationship between the fusion rate and the fatigue life of recycled asphalt depends on the factors that cause the fusion rate variation. Under the influence of the amount of rejuvenator, the fatigue life of recycled asphalt grows exponentially with increasing fusion rate due to enhancement of molecular motion as well as a supplement of lightweight components. Under the influence of heat preservation treatment, fatigue life increases linearly with increasing fusion rate. The proposed fusion rate index can be utilized to quantitatively characterize the fusion state of virgin and aged asphalt, thus providing a simple way to guide the practical application of recycled asphalt.

Pervious concrete is a special type of concrete that is of high porosity and contains no or a small amount of fine aggregate, and it is an important basic material for sponge city construction. The presence of a large number of connected pores inside pervious concrete leads to a marked difference in durability failure mechanism compared with that of ordinary concrete.

In this study, the frost resistance and anti-clogging of pervious concrete were introduced in detail, and the methods to improve their performance were summarized systematically. The cracking pattern of pervious concrete is influenced by geometric characteristics and three-dimensional morphological features of pores, resulting in its crack generation, development, and geometry being significantly different from those of ordinary concrete, thus leading to different freeze-thaw cycle mechanisms. In addition, due to its different pore structure compared to ordinary concrete, three types of clogging mechanisms, affecting the long-term permeability of pervious concrete were elaborated systematically (i.e., physical clogging, biological clogging, and chemical clogging). And the ways to improve the anti-clogging of pervious concrete are systematically presented from multiple perspectives. Finally, in order to broaden the engineering applications of pervious concrete, some research proposals are presented in this study.

The autonomous vehicle (AV) technology has the potential to significantly improve safety and efficiency of the transportation and logistics industry. Full-scale AV testing is limited by time, space, and cost, while simulation-based testing often lacks the necessary accuracy of AV and environmental modeling. In recent years, several initiatives have emerged to test autonomous software and hardware on scaled vehicles. This systematic literature review provides an overview of the literature surrounding small-scale self-driving cars, summarizing the current autonomous platforms deployed and focusing on the software and hardware developments in this field. The studies published in English-language journals or conference papers that present small-scale testing of self-driving cars were included. Web of Science, Scopus, Springer Link, Wiley, ACM Digital Library, and TRID databases were used for the literature search. The systematic literature search found 38 eligible studies. Research gaps in the reviewed papers were identified to provide guidance for future research. Some key takeaway emerging from this manuscript are: (i) there is a need to improve the models and neural network architectures used in autonomous driving systems, as most papers present only preliminary results; (ii) increasing datasets and sharing databases can help in developing more reliable control policies and reducing bias and variance in the training process; (iii) small-scaled vehicles to ensure safety is a major benefit, and incorporating data about unsafe driving behaviors and infrastructure problems can improve the accuracy of predictive models.

In the context of the increasing scale of bridges and the increasing service life of bridges, it is very important to carry out efficient, accurate and intelligent bridge operation and maintenance. In recent years, advanced equipment, technology and intelligent algorithms have developed rapidly. It is necessary to apply advanced equipment and algorithms to bridge operation and maintenance business to facilitate the digitalization and intelligence of bridge operation and maintenance. To grasp the research progress on the bridge intelligent operation and maintenance, this paper summarizes the research progress in recent years from the aspects of intelligent detection equipment and technology, intelligent monitoring equipment and technology, intelligent data analysis, intelligent evaluation and early warning, and intelligent repair and maintenance. According to the review, more and more smart devices have been used to replace human beings to detect dangerous and hidden bridge components. At the same time, image processing, radar and other technologies have been used to analyze component damage more objectively and quantitatively. To solve the shortcomings of traditional sensors such as short life and low robustness, more non-contact measurement methods have been proposed. Scholars have proposed various intelligent algorithms to process the massive amount of bridge health monitoring data to improve the quality of the data. To achieve the rapid perception of bridge status and timely early warning of structural abnormalities, different from traditional theoretical calculations, scholars have tried to use data-driven methods to intelligently evaluate and early warning of bridge structural status. In terms of intelligent repair and maintenance, more intelligent algorithms have been used to optimize structural maintenance strategies and determine the best maintenance time by integrating multi-source heterogeneous data. All these provide strong support for the automation, digitization and intelligence of bridge operation and maintenance.

Fiber-reinforced polymer (FRP) bars have been increasingly recognized in the field of civil engineering due to their advantages of light weight, high strength and excellent durability. FRP bars can replace steel bars in concrete beams and effectively improve the durability of beams. In this paper, the literature relevant to the short-term mechanical properties of FRP bars and FRP-reinforced concrete beams was reviewed based on previous studies and practical engineering application. Firstly, the mechanical properties of FRP bars were reviewed. Different types of fibers or steel and fibers can be combined to obtain hybrid fiber-reinforced polymer (HFRP) or steel-fiber composite bars (SFCB) with excellent mechanical performance, respectively. The bond performance and bond-slip model between FRP bars and concrete were discussed. Several common bond-slip models were usually used to study the bond performance between carbon fiber-reinforced polymer (CFRP) bars or glass fiber-reinforced polymer (GFRP) bars and concrete, but changing the type of FRP bars will lead to larger dispersion. Then, the experimental studies, theoretical calculation methods and finite element simulation methods of flexural/shear behavior of FRP-reinforced concrete beams were presented. Finally, their applications in practical engineering were discussed and the prospects of further research were proposed. It is pointed out that FRP-reinforced ultra-high performance concrete (UHPC) beams, FRP-reinforced geopolymer concrete (GPC) beams, engineered cementitious composites (ECC)-FRP-reinforced concrete beams, prestressed FRP-reinforced concrete beams and steel/FRP hybrid-reinforced concrete beams can effectively improve the deformation resistance and poor ductility of pure FRP-reinforced concrete beams.

Global aging has brought attention to addressing the elderly mobility dilemma, and a commitment to address inclusive transport in aging. Transport inclusion for older adults aims at establishing an age-friendly transport system. As a direct policy goal and promoting active aging as an indirect social goal, to help older populations gain access to transport and social opportunities. Based on the analysis of scientific knowledge mapping over the past 30 years, this study visualizes the hotspots and trends in elderly mobility research. Through a qualitative analysis of 138 papers, this paper reviews the theoretical foundations for transport inclusion and three themes of elderly mobility research, proposes a framework for public transport (PT) inclusion research as well as future research directions. The study suggests that transport inclusion can help enhance elderly health, social participation, and subjective well-being. It can improve their travel opportunities for active aging in four ways: opportunity accessibility, physical accessibility, age-friendly informationalization, and cost affordability. Future research should pay attention to examining the mechanism of perceived transport inclusion on active aging, expanding the multilevel research space of the capability approach (CA), and exploring the subjective-objective integrated research model for PT inclusion. This research contributes to the overall knowledge of the theoretical and empirical researches on PT inclusion for the elderly and promotes the integrated application of interdisciplinary knowledge in the field.

Sustainable travel behavior intervention is an essential strategy to promote the development of urban transportation. The interventions offer personalized strategies based on certain scenario and participants to promote its effectiveness over hard travel restrictions. However, personalized strategies may also bring about difficulties to identify the actual effect of the measures. Furthermore, based on current practice, to make full use of travel behavior interventions, it is necessary to construct a unified methodological evidence-based framework to assess the reliability and effectiveness of travel behavior intervention studies. In response to these issues, we applied evidence-based knowledge graph to the field of sustainable travel behavior interventions to help decision supporters design sustainable travel behavior interventions wisely and in turn avoid excessive use of hard travel restrictions. We introduced concept of evidence-based practice to conduct a systematic analysis concerning reliability and validity of current full volume empirical studies by dimensions of scenarios, types of interventions and targets. In addition, we took advantage of high extensivity and integrability of knowledge graph to organize evidence-based related elements. Result of the systematic analysis shows that in terms of reliability of evidence, school intervention is the best scenario, knowledge incentive is the best intervention type and promoting public transit and walking proportion are the best targets. Oppositely, the reliability of interventions in workplace, belonging to reward and threat along with aiming at changing travel patterns generally and lowering travel carbon emission need to be enhanced. From the study, various research prospects are raised to promote evidence quality in the field of travel behavior intervention implementation. As a pioneer study, our research contributes to the field of urban transportation in introducing concepts of evidence-based practice and enabling optimization and extension of our achievement via the usage of knowledge graph, enhancing reliability and objectivity in urban transportation decision-making.

One of the main factors affecting the safety of signalised intersections is the stop/go behaviour during the yellow interval. Although previous research has exhaustively examined drivers' stop/go decision-making, the expected autonomous vehicles' (AVs') stop/go behaviour has not yet been thoroughly investigated. Through a series of simulation experiments developed for conventional and autonomous vehicles using different car-following, lane-changing, lateral placement and stop/go model parameter values, we examine here whether the default VISSIM stop/go parameter values can adequately replicate the observed drivers' behaviour at the considered intersection and assess the suitability of using the currently available options, albeit referring to human drivers, to simulate the expected stop/go behaviour of AVs. We also propose a policy framework for determining the desired behaviour of AVs in yellow interval, which is integrated into an AVs logic and achieved in the last simulation to explore the effect of automation on the stop/go outcome and, hence, on the safety level of signalised intersections. Several data analysis and modeling techniques were used for the formulation of certain scenarios, including binary choice models. The default stop/go parameter values were found unfit to replicate the observed stop/go behaviour and subjected to calibration. Compared to the currently available options, the proposed AVs logic proved to produce the most accurate results, in terms of the stop/go simulation outcome. Regarding the impact of automation on the stop/go outcome, the simulation experiments showed that AVs preferred a more conservative behaviour in favor of road safety, as indicated by the significant reduction (≈15%) in the number of vehicles crossing the stop line during the yellow light and zero instances of red light violation. However, compared to the conservative drivers represented by the default stop/go parameter values, AVs preferred a more rational behaviour in favor of intersection capacity without compromising road safety.