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

Inaccuracies of traffic sensors during traffic counting and vehicle classification have persisted as transportation agencies have been prompted to calibrate sensors periodically. Detection of multiple objects, heavy occlusions, and similar appearances in congested places are some causes of computer vision model inaccuracies. This paper used the YOLOv5 model for detection and the DeepSORT model for tracking objects. Due to the nature of the reported problem caused by many misses and mismatches, the power of quantum computing with the alternating direction method of multipliers (ADMM) optimizer was leveraged. A basic Kalman filter and the Hungarian algorithm features were used in combination with a quantum optimizer to present robust multiple object tracking (MOT) algorithms. This hybrid combination of the classical and quantum model has fastened learning the occludes during frame matching of tracks and detections by generating minimum quantum cost function value. Comparisons with the existing models indicated a significant increase in the primary MOT metric multiple object tracking accuracy (MOTA) by 16% more than the regular YOLOv5-DeepSORT model when using a quantum optimizer. Also, a 6% multiple object tracking precision (MOTP) increases and a 6% identification metrics (F₁) score increase were observed using the quantum optimizer with identity switching reduced from 6 to 4. This model is expected to assist transportation officials in improving the accuracy of traffic counts and vehicle classification and reduce the need for regular computer vision software calibration.

The reduction of speed limits in urban roads through traffic calming schemes intends to ensure safer traffic conditions among road users by reducing the probability related to the occurrence of severe accident. Looking it from a different perspective, traffic calming measures can potentially resolve congestion problems at the same time by lowering the overall accessibility and attractiveness of private cars in urban areas. This study proposes a new methodological approach to explore and assess the direct impacts of traffic calming in the transport system efficiency of a metropolitan area. The multi-agent transport simulation (MATSim) and Open-Berlin scenario are utilized to perform this simulation experiment. By developing a new external tool, the free flow speed and road capacity of each network link is updated based on new speed limits and different compliance rates, which are defined per road hierarchy level. The test scenarios that are formulated present radical conditions, where the speed limit in most urban roads of Berlin drops to 30 km/h or even 15 km/h. The findings of this study show a considerably high increase in trips, passenger hours, and passenger kilometers using public transport modes, when traffic calming links are introduced, the reserve change is observed in private cars trips. Although the speed limits are decreased in inner urban roads in most of the scenarios, the decrease of average travel speed of private cars is not so high as it was expected. Surprisingly, private cars are used for longer distances in all test scenarios. Car drivers seem to use already existed motorways and private road to commute. In simulations, driver compliance to the new speed limits seems to be a determinant factor that is strongly influenced by the design interventions applied in a traffic calming area.

Pedestrian safety is at high stakes due to the non-compliance practices of pedestrians at signalized intersections. Additionally, when pedestrians are hurrying, they deliberately engage in such unsafe behaviour. Therefore, the purpose of this study was to understand how time pressure (i.e., feeling of hurry or saving time) affected pedestrians' decisions to follow traffic rules at signalized junctions. To achieve the study objectives, a pedestrian simulator setup was used to collect the crossing behaviour of forty participants at a four-legged signalized intersection. Non-compliance, one of the riskiest pedestrian behaviours, was examined with respect to three different forms, comprising dangerous temporal non-compliance (D-TNC), non-dangerous temporal non-compliance (ND-TNC), and spatial non-compliance (SNC) behaviour under two distinct conditions: baseline (i.e., no time pressure) and time pressure conditions. The effects of demographics, usual walking features, and time pressure on D-TNC and ND-TNC were investigated using a multinomial regression model, while SNC behaviour was investigated using a binary regression model. It was interesting to note that the majority of the factors related to pedestrians’ usual walking behaviour had an impact on all kinds of non-compliance behaviours. Importantly, the results also showcased that time pressure had a contrasting impact on D-TNC and ND-TNC behaviour whereas SNC behaviour increased under time pressure. Additionally, the varying impacts of D-TNC, ND-TNC, and SNC were also reflected in the occurrence of the crashes, which were probably triggered by discrepancies in the influence of time pressure on non-compliance behaviours. These findings highlight the need for technical solutions, educational outreach, and efficient enforcement practices to reduce pedestrians' non-compliant behaviour.

Sight obstructions along road curves can lead to a crash if the driver is not able to stop the vehicle in time. This is a particular issue along curves with limited available sight, where speed management is necessary to avoid unsafe situations (e.g., driving off the road or invading the other traffic lane). To solve this issue, we proposed a novel intelligent speed adaptation (ISA) system for visibility, called V-ISA (intelligent speed adaptation for visibility). It estimates the real-time safe speed limits based on the prevailing sight conditions. V-ISA comes with three variants with specific feedback modalities (1) visual and (2) auditory information, and (3) direct intervention to assume control over the vehicle speed.

Here, we investigated the efficiency of each of the three V-ISA variants on driving speed choice and lateral behavioural response along road curves with limited and unsafe available sight distances, using a driving simulator. We also considered curve road geometry (curve direction: rightward vs. leftward). Sixty active drivers were recruited for the study. While half of them (experimental group) tested the three V-ISA variants (and a V-ISA off condition), the other half always drove with the V-ISA off (validation group). We used a linear mixed-effect model to evaluate the influence of V-ISA on driver behaviour.

All V-ISA variants were efficient at reducing speeds at entrance points, with no discernible negative impact on driver lateral behaviour. On rightward curves, the V-ISA intervening variant appeared to be the most effective at adapting to sight limitations. Results of the current study implies that V-ISA might assist drivers to adjust their operating speed as per prevailing sight conditions and, consequently, establishes safer driving conditions.

Damage to semi-rigid base asphalt pavement is related to improper matching of the pavement structure moduli. This study mainly focused on the modulus matching of structural layers and the development of a pavement structure optimization method. First, the modulus loss of existing pavement structures was analysed, and a three-dimensional finite element model was established based on the existing pavement. Second, the influence of the modulus of each structural layer on the mechanical response indicators and fatigue life was analysed. Based on the results, a pavement structure design method using the smoothness of the stress-strain curve as the modulus matching criterion of the structural layers was proposed. And it was found that a strain convex point was present and that the stress mutation between the structural layers was significant when the modulus matching of the pavement structure was reasonable. Further, the evaluation indicators were divided into two groups, namely, mechanical indicators and fatigue life indicators. And it was proposed an optimized pavement structure design method based on modulus matching and multi-indicator range analysis. Finally, the optimal modulus combination of pavement structure was determined by this method. The research systematically studied the influence of the modulus of each structural layer on the mechanical response and fatigue life of the pavement, and proposed the concept and specific executive criteria of modulus matching for the first time. Meanwhile, it also provided an effective optimization method for pavement structure design.

The carbon emissions arising from road pavement infrastructures have emerged as critical issue in recent years. The life cycle of a pavement can be divided into five phases, namely raw materials and production, construction, use, maintenance and end of life. While the use phase generates the highest carbon emissions throughout the pavement's life cycle, it is usually neglected in most pavement life cycle assessment (LCA) studies due to its complexity and uncertainty. Therefore, this review selected 126 relevant references, focuses on quantification methods, influential factors and reduction technologies of carbon emissions in pavement use phase. Among the carbon accounting approached, the LCA approach, remains the most widely used for evaluating the environmental impact of pavements. Second, the primary influential factors on the use phase' carbon emission include pavement-vehicle interaction primarily affected by pavement roughness, pavement albedo and climate change. Most influential factors above indirectly cause changes in carbon emissions by influencing the pavement performance and subsequent vehicle emissions. Finally, the review surveys carbon emission reduction technologies during pavement use phase, focusing mainly on reducing pavement rolling resistance and constructing cool pavements. Reflective pavements and permeable pavements are the most widely used cool pavement technologies. Overall, the aspects involved in this paper hold significant promise for quantifying and reducing carbon emissions in the pavement use phase.

Good compatibility between waterborne epoxy resin (WER) modifier and styrene-butadiene rubber (SBR) latex modified asphalt emulsion (SBRE) is an essential premise for good pavement performance of WER and SBR latex compositely modified asphalt emulsion (WSAE). This study aims to explore the compatibility between WER modifier and SBRE. To achieve the goal, several WER modifiers produced by two methods were first selected to modify SBRE, thus the WSAEs were prepared. Next, storage stability and workability of the WSAEs themselves, and high-temperature performance, rheological behavior and temperature sensitivity of their evaporated residues were compared and evaluated via performing a series of experiments, respectively, thus the WER modifier possessing an optimal modification effect was recommended. Results show that the storage stability of WSAEs is sensitive to the amount of WERs. The incorporation of 1% WERs by the mass of SBRE improves the storage stability of SBRE, while WERs that exceed 1% weaken its storage stability. When the WERs reach 3% and 4%, the 5 d storage stability of prepared WSAEs will be beyond the limitation of specification. Incorporating WERs into SBRE negatively affects the workability of SBRE, and the workability of WSAEs is adversely influenced by the WERs content and the storage time. To ensure the construction, the WSAEs with 3% and 4% WERs should not be stored for more than 36 h and 48 h, respectively. The WERs effectively improve the high-temperature performance of SBRE residue, especially the 3% WERs. Besides, the WERs notably enhance the rheological property and thermal stability of SBRE residue. In contrast, the WER modifier produced by chemically modified method has a smaller adverse impact on the storage stability and workability of WSAE, and a larger enhancement on the high-temperature performance, rheological property and thermal stability of SBRE residue, which is thus recommended to modify SBRE.

The morphology of graded crushed stone (GCS) particles has an essential influence on the performance of aggregate mixtures. The impact of particle shape is a comprehensive effect that cannot be considered separately, leading to difficulties in establishing the relationship between the mixture properties and the aggregate morphology by using laboratory methods. The discrete element method (DEM) is an effective way widely adopted to reconstruct the morphology of particles and simulate performance tests of granular materials. However, selecting limited particles characterizing a real particle-assembly for simulation is still a challenge in current research due to the inherent rich variability of particle shapes. In this study, based on the acquisition of three-dimensional (3D) aggregate shapes by using laser scanning, ellipsoid index (EDI) translating the particle shape as a function of surface area, volume, and contour length is proposed to comprehensively evaluate aggregate morphology. Further, a particle library capable of characterizing aggregate morphology distribution is established based on the statistics of the corresponding morphological characteristics of particle samples. The model reliability is validated by carrying out a series of experimental and numerical penetration tests with nine different gradations. The established particle library can be used to model aggregate mixtures and the proposed simulation framework is promising for optimizing the mixture gradation design numerically.

The primary goal of this study is the design and construction of semi-flexible pavement (SFP) mixture in accordance with the engineering and mechanical criteria. This study involves the use of a range of gradation curves, air void contents, cellulose and synthesized fibers, and neat and modified asphalt binders to prepare the open-graded asphalt (OGA) mixtures. To analyze the characteristics of these mixtures, a variety of test, namely binder drainage, semi-circular bending (SCB), Cantabro, wheel tracking, indirect tensile strength (ITS), and permeability tests were conducted. Additionally, to analyze the prepared grouting material, flexural strength, compressive strength, and fluidity tests were conducted. In the final stage, SFP was compared to HMA in terms of engineering characteristics and performance. According to the results, SFP was more resistant to skid, rutting, fire, and moisture damage, while HMA had a better performance in fracture tests, including SCB test. According to the results of the mechanical performance tests conducted on OGA mixtures, the highest and lowest values for air void content to achieve the highest mechanical performance level were 30%–35% and 25%, respectively. Also, based on the laboratory results, it was determined that the required void ratio for constructing OGA mixtures was 24%–26% based on the bitumen type and fibers amount in the mixture. Finally, SFP mixture can be regarded as a viable alternative to common pavements thanks to its high resistance to rutting and moisture damage, long freezing-thawing fatigue life, and adequate fire and skid resistance.