Merging Roads Research Articles

3D Road Lane Classification with Improved Texture Patterns and Optimized Deep Classifier.

The understanding of roads and lanes incorporates identifying the level of the road, the position and count of lanes, and ending, splitting, and merging roads and lanes in highway, rural, and urban scenarios. Even though a large amount of progress has been made recently, this kind of understanding is ahead of the accomplishments of the present perceptual methods. Nowadays, 3D lane detection has become the trending research in autonomous vehicles, which shows an exact estimation of the 3D position of the drivable lanes. This work mainly aims at proposing a new technique with Phase I (road or non-road classification) and Phase II (lane or non-lane classification) with 3D images. Phase I: Initially, the features, such as the proposed local texton XOR pattern (LTXOR), local Gabor binary pattern histogram sequence (LGBPHS), and median ternary pattern (MTP), are derived. These features are subjected to the bidirectional gated recurrent unit (BI-GRU) that detects whether the object is road or non-road. Phase II: Similar features in Phase I are further classified using the optimized BI-GRU, where the weights are chosen optimally via self-improved honey badger optimization (SI-HBO). As a result, the system can be identified, and whether it is lane-related or not. Particularly, the proposed BI-GRU + SI-HBO obtained a higher precision of 0.946 for db 1. Furthermore, the best-case accuracy for the BI-GRU + SI-HBO was 0.928, which was better compared with honey badger optimization. Finally, the development of SI-HBO was proven to be better than the others.

Robust estimation of traffic density with missing data using an adaptive-R extended Kalman filter

Traffic density is a crucial indicator of traffic congestion, but measuring it directly is often infeasible and hence, it is usually estimated based on other measurements. However, a challenge in measuring traffic parameters is the high probability of sensor failure, which results in missing measurement or missing data. To overcome this difficulty, in this paper, we propose a novel adaptive-R extended Kalman filter (AREKF) combined with a model-based data imputation technique to estimate traffic density. We show analytically that the AREKF is able to accurately estimate the density even when the noise covariance matrices are not accurately known. Microscopic traffic simulations demonstrated the efficacy of the AREKF, where the estimated density is fed into a real-time ramp metering control algorithm to control vehicle flow on a merging road, which is highly susceptible to traffic congestion. The results show that the proposed AREKF with data imputation is able to accurately estimate the traffic density even when data is missing, and the ramp-metering controller significantly improves the traffic flow and thus, alleviates congestion.

Traffic Priority Mechanisms

In the future world of self-driving vehicles, intersections will be managed by computers that send individual commands to each passing vehicle. This paper proposes to make traffic priority contingent on the self-reported value of time of vehicle occupants. A model of two merging roads with stochastic traffic is developed. Algorithms for calculation of optimal exit sequences, accounting for time value heterogeneity, are characterized. Welfare costs of a limited planning horizon are assessed. An incentive-compatible scheme of payment for priority is calculated. Under mild conditions, the mechanism is Pareto improving, that is, benefits all parties. The optimality of the traffic volume and composition under the optimal exit regulation is established.

Short-term Traffic Volume Prediction for the Merging Roads by Artificial Neural Network

Ana arterlerinde trafik sıkışıklığı yaşanan şehirlerin ikincil derecedeki yollarında trafik hacim tahminlerinin yapılması kritik konulardan biridir. Ekonomiden farklı mühendislik uygulamalarına kadar birçok alanda (satış tahminleri, endüstriyel süreç kontrolü, müşteri araştırmaları, veri doğrulama, risk yönetimi, hedef pazarlama ve inşaat mühendisliği gibi) kullanılan yapay sinir ağı (YSA) bu konuda umut verici bir çözüm olabilir. Geçmiş trafik verilerine dayanarak daha yüksek bir tahmin doğruluğu sağlayan YSA, son 30 yıldır ulaştırma mühendisliği alanındaki uygulamalarda çok popüler hale geldi. Bu makaledeki temel amaç, İstanbul'un Boğaz Köprülerinden birine katılan bir bağlantı yolunun kısa dönem trafik hacmini YSA'nın üç farklı uygulamasıyla tahmin etmektir. Bunlar İleri Besleme Geri Yayılımı (FFBP), Genelleştirilmiş Regresyon Sinir Ağı (GRNN) ve Radyal Tabanlı Fonksiyon (RBF) idi. Daha sonra elde edilen sonuçlar birbirleriyle ve Çoklu Doğrusal Regresyon (MLR) yönteminin sonuçları ile karşılaştırıldı.

Two-stage on-board optimization of merging velocity planning with energy management for HEVs

This paper proposes a two-stage hierarchy control system with model predictive control (MPC) for connected parallel HEVs with available traffic information. In the first stage, a coordination of on-ramp merging problem using MPC is presented to optimize the merging point and trajectory for cooperative merging. After formulating the merging problem into a nonlinear optimization problem, a continuous/GMRES method is used to generate the real-time vehicle acceleration for two considered HEVs running on main road and merging road, respectively. The real-time acceleration action is used to calculate the torque demand for the dynamic system of the second stage. In the second stage, an energy management strategy (EMS) for powertrain control that optimizes the torque-split and gear ratio simultaneously is composed to improve fuel efficiency. The formulated nonlinear optimization problem is solved by sequential quadratic programming (SQP) method under the same receding horizon. The simulation results demonstrate that the vehicles can merge cooperatively and smoothly with a reasonable torque distribution and gear shift schedule.

Coordination of Connected Vehicles on Merging Roads Using Pseudo-Perturbation-Based Broadcast Control

This paper proposes a coordination method for vehicles on merging roads to realize smooth traffic merging. The proposed method can be implemented with a low communication volume in an environment in which the automated/connected vehicles and manually operated vehicles are mixed. The method is based on a pseudo-perturbation-based broadcast controller (PBC), which has the potential to coordinate multiple vehicles with low-cost V2I communication without V2V communication. The PBC indiscriminately broadcasts an identical signal to the vehicles. The volume of such a broadcast communication is less than that of the commonly used unicast communication. This paper overcomes the following three issues to apply the PBC to the traffic merging problem. First, the time-invariant metrics are derived to design a time-invariant objective function corresponding to the traffic merging problem because the PBC is based on the minimization of such a time-invariant function. Second, a (locally) convex objective function to be globally minimized is designed. Finally, the collision avoidance between vehicles is guaranteed. The microscopic traffic simulations demonstrate the effectiveness of the proposed PBC-based coordination method in the presence of uncooperative manually operated vehicles.

Merging roads: chemical tools and cell biology to study unconventional protein secretion.

The endomembrane trafficking network is highly complex and dynamic, with both conventional and so-called unconventional routes which are in essence recently discovered pathways that are poorly understood in plants. One approach to dissecting endomembrane pathways that we have pioneered is the use of chemical biology. Classical genetic manipulations often deal with indirect pleiotropic phenotypes resulting from the perturbation of key players of the trafficking routes. Many of these difficulties can be circumvented using small molecules to modify or disrupt the function or localization of key proteins regulating these pathways. In this review, we summarize how small molecules have been used as probes to define these pathways, and how they could be used to increase current knowledge of unconventional protein secretion pathways.

Environmental Technology: Potential of Merging Road Pavement with Stormwater Detention

This study stresses on the concept of multi-functional urban land use incorporating permeable pavement integrated with underground storage. Permeable pavement that is available in the market consists of pavers and a thick layer of course aggregates that store water. Contrary to the mentioned pavement, this study tries to replace the underlying storage with blocks of concrete detention cells. Stormwater permeates through the openings of pavers and flows into the detention storage underneath. Investigation of such application is carried out using the SWMM software. Performance of a single hollow cube pavement block (0.25m x 0.25m x 0.25m) is demonstrated here. The block is virtually subjected to the worst scenarios of extreme rainfalls over a non-stop time span of three hours. Modelling outputs point to encouraging benefits of the anticipated size and storage volume are capable of capturing stormwater up to at least one hour. Thus, the system is suggested to be effective in limiting stormwater, and subsequently, promoting road structure as multi-purpose infrastructure.

Age, skill, and hazard perception in driving

This study examined the effects of age and driving experience on the ability to detect hazards while driving; namely, hazard perception. Studies have shown that young-inexperienced drivers are more likely than experienced drivers to suffer from hazard perception deficiencies. However, it remains to be determined if this skill deteriorates with advancing age. Twenty-one young-inexperienced, 19 experienced, and 16 elderly drivers viewed six hazard perception movies while connected to an eye tracking system and were requested to identify hazardous situations. Four movies embedded planned, highly hazardous, situations and the rest were used as control. Generally, experienced and older-experienced drivers were equally proficient at hazard detection and detected potentially hazardous events (e.g., approaching an intersection, pedestrians on curb) continuously whereas young-inexperienced drivers stopped reporting on hazards that followed planned, highly hazardous situations. Moreover, while approaching T intersections older and experienced drivers fixated more towards the merging road on the right while young-inexperienced drivers fixated straight ahead, paying less attention to potential vehicles on the merging road. The study suggests that driving experience improves drivers’ awareness of potential hazards and guides drivers’ eye movements to locations that might embed potential risks. Furthermore, advanced age hardly affects older drivers’ ability to perceive hazards, and older drivers are at least partially aware of their age-related limitations.

Impacts of road corridors on urban landscape pattern: a gradient analysis with changing grain size in Shanghai, China

Urbanization is one of the most important driving forces for land use and land cover change. Quantifying urban landscape pattern and its change is fundamental for monitoring and assessing ecological and socioeconomic consequences of urbanization. As the largest city in the country, Shanghai is now the fastest growing city in China. Using land use data set of 2002 and combining gradient analysis with landscape metrics, we analyzed landscape pattern of Shanghai with increasing grain size to study the impacts of road corridors on urban landscape pattern. Landscape metrics were computed along a 51×9 km2 transect cutting across Shanghai with a moving window. The results showed that the urban landscape pattern of Shanghai was greatly changed when road corridors were merged with urban patches and the variation of patch density would alter when grain size changed. As a linear land use type, road corridors exhibited a different spatial signature comparing with other land use types and distinctive behavior with increasing grain size. Merging road and urban patches resulted in a sharp reduction in patch density, mainly caused by segmentation of roads corridors. The results suggested that grain size around 7.5 m might be optimal for urban landscape analysis. Landscape patch density is significantly correlated with road percent coverage and the most important effect of road corridors in urban landscape is increased habitat fragmentation.

An investigation into the relationships between area social characteristics and road accident casualties

This paper reports on the analysis of a data base created by merging road casualty information and census data for the former Lothian region in Scotland. The data base was established by assigning resident postcodes to each casualty record and relating these postcodes to the census data for the relevant census output area. Initially, consideration was given to the relationship between casualty frequencies and the distance of the accidents from the zones of residence. As might be anticipated, the casualty frequencies were higher nearer to the zones of residence, possibly due to higher exposure. Subsequently, the relationships between casualty rates and social deprivation indicators for the casualties' zone of residence were investigated. In general it was found that the casualty rates amongst residents from areas classified as relatively deprived were significantly higher than those from relatively affluent areas.