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Rockfalls are frequent and damaging phenomena that occur on steep or vertical slopes, in coastal areas, mountains and along coastal cliff. Water, in different forms, is the most common triggered factor of rockfalls. Consequently, we can consider that precipitation is the most influential factor for slope instabilities and it influences almost all other water parameters. Besides, the specific geology of the Anaga nature reserve in the volcanic island of Tenerife, together with its steep landscape, contributes to the instability of the slopes and frequent rockfalls. Recently, due to climate change and global warming, the annual precipitation/rainfall has declined but the number of heavy storms, associated with intense rainfall and strong winds, events that exceed precipitation thresholds in a brief period has increased which triggers slope movements. This paper describes the analysis of information on rainfall-induced rockfalls in Anaga, Tenerife (Canary Islands), to forecast rock failures of social significance and to improve the capability to respond and emergency decision making. To define reliable thresholds for a certain area, we analized information during the period 2010–2016, reconstructed the rockfall events, and statistically analyzed the historical rainfall conditions that led to landslides. The summary graph correlating precipitation to the probability of occurrence of an event was plotted. Statistical and probability graphs were made with the direct relationship between the number of rockfall events and total rainfall in that period by examining the maximum daily precipitation, not only on the day of the event but up to 3 days before. Hence, the results of this study would serve as a guide for the possible forecasting of rainfall-induced rockfalls, especially for road maintenance services, so that they can be on alert or mobilize the necessary resources in advance depending on the intensity of the expected rainfall.HighlightsWe have determined the correlation between the probability of occurrence of a rockfall event in a natural reserve (Anaga, island of Tenerife, Canary Islands) and the expected rainfall intensity.We have observed the time delay between the occurrence of rainfall and rock falls, corroborated by experience in this area, between the day of the event and the day of the maximum rainfall associated with it.We have provided a tool to be used by the Civil Protection and Emergency and Road Maintenance and Conservation Services of the island of Tenerife as part of their management to mobilise the necessary resources or means or to adopt traffic limitations or restrictions depending on the level of alert decreed for adverse meteorological phenomena related to rainfall.

Highway congestion is a persistent issue, and dynamically activating emergency lanes offers a promising mitigation strategy. However, traditional fixed-time or single-threshold methods often fail to balance traffic efficiency and safety. This paper introduces a dynamic optimization framework that integrates a Kriging surrogate model with the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to identify optimal activation strategies. By simultaneously minimizing total travel time (efficiency) and the duration vehicles spend in unsafe proximity (safety), our method generates a set of Pareto-optimal solutions. We calibrated and validated the model using real-world highway data. The results are compelling: the optimized compromise strategy reduced total travel time by 20.5% compared to having no activation, while keeping safety risks within an acceptable range. The use of a Kriging surrogate model sped up the optimization process by approximately 20 times compared to direct simulation, achieving a prediction accuracy of 97.8%. The optimal strategies characteristically involve opening the emergency lane at the downstream bottleneck during peak congestion and closing it promptly as traffic eases. This research provides a robust, efficient, and practical decision-support tool for intelligent traffic management, offering a clear pathway to safer and less congested highways.

The long segment scheme allowing contractors to oversee road maintenance still has drawbacks. For example, non-compliance, such as delaying preservation for road issues, persists due to small penalties. This leads service providers to neglect road performance without objection to fines. This research aims to provide sufficient incentives for contractors to comply with the implementation of the late delivery penalty rate of road service levels. This research used an experimental method to test two formulas for the late delivery penalty rate of road service levels on two road sections in Central Java and Special Region of Yogyakarta, Indonesia. During the experiment, the time taken by service providers to fulfill the road service level on the two different road sections was measured and recorded. In the first road section, the previously used formula resulted in a penalty of only$7.39, while the developed formula yielded $ 122.17. Furthermore, in the second road section, the government formula led to a penalty of$375.89, whereas the developed formula resulted in a fine amount of $ 1,468.99. The results showed that the penalty value given to contractors for two road segment trials using the research formula was 16 and 4 times higher than the formula used by the Directorate General of Highways. In addition, the developed formula takes into account other road performance indicators such as potholes with a diameter < 10 cm and depth < 4 cm, ponding, and uneven patching.

Road weather conditions such as ice, snow, or heavy rain can have a significant impact on driver safety. In this paper, we present an approach to continuously monitor the road conditions in real time by equipping a fleet of vehicles with sensors. Based on the observed conditions, a physical road weather model is used to forecast the conditions for the following hours. This can be used to deliver timely warnings to drivers about potentially dangerous road conditions. To optimally process the large data volumes, we show how artificial intelligence is used to (1) calibrate the sensor measurements and (2) to retrieve relevant weather information from camera images. The output of the road weather model is compared to forecasts at road weather station locations to validate the approach.

Efficient clustering algorithms are critical for enabling the timely dissemination of emergency messages across maximum coverage areas in vehicular networks. While existing clustering approaches demonstrate stability and scalability, there has been a limited amount of work focused on leveraging roadside units (RSUs) for cluster head selection. This research proposes a novel framework that utilizes RSUs to facilitate cluster head election, mitigating the cluster head selection process, clustering overhead, and broadcast storm problem. The proposed scheme mandates selecting an optimal number of cluster heads to maximize information coverage and prevent traffic congestion, thereby enhancing the quality of service through improved cluster head duration, reduced cluster formation time, expanded coverage area, and decreased overhead. The framework comprises three key components: (I) an acknowledgment-based system for legitimate vehicle entry into the RSU for cluster head selection; (II) an authoritative node behavior mechanism for choosing cluster heads from received notifications; and (III) the role of bridge nodes in maximizing the coverage of the established network. The comparative analysis evaluates the clustering framework’s performance under uniform and non-uniform vehicle speed scenarios for time-barrier-based emergency message dissemination in vehicular ad hoc networks. The results demonstrate that the proposed model’s effectiveness for uniform highway speed scenarios is 100% whereas for non-uniform scenarios 99.55% information coverage is obtained. Furthermore, the clustering process accelerates by over 50%, decreasing overhead and reducing cluster head election time using RSUs. The proposed approach outperforms existing methods for the number of cluster heads, cluster head election time, total cluster formation time, and maximum information coverage across varying vehicle densities.

This increase in transportation facilities causes the traffic volume of a road to be greater but is not supported by adequate road infrastructure, one of which is parking facilities. Parking is a phenomenon that affects the movement of vehicles when vehicles that have such a high intensity will be hampered by vehicles parked on the road, causing congestion. Vehicles parked on the roadside are generally around places or activity centres such as offices, markets, schools, and restaurants. Maximum vehicle volume without on-street parking occurs in segment 1 on Monday at 16:30, with the number of vehicles amounting to 2154.3 SMP/hour with a capacity value (C) = 2375 SMP/hour; the degree of saturation value (DS) is obtained. =0.91. This shows that the level of service is included in category E, which means that segment 1 has unstable flow, decreased speed, and vehicle motion is approaching capacity. When parking occurs on the road, the capacity value decreases to (C) = 1243.01 SMP/hour so that it affects the degree of saturation in each segment with the respective DS values: Segment 1 = 1.73, segment 2 = 1.44, segment 3 = 1.40. The flow becomes blocked or obstructed, and the vehicle speed is < 50 km/hour. As a result of vehicles parked on the road, the capacity of the road is reduced so that it has an impact on the movement of traffic flow, and eventually, congestion occurs

In the last two decades new emphasis has been given to the economic impact of geography, especially on the cost of being landlocked. From a development perspective, understanding the cost of being landlocked and its economic impact is critical, since one country of four in the world is landlocked (almost one out of three in Sub-Saharan Africa). Attempts to address the cost of being landlocked have mainly focused on regional and multilateral conventions aiming at ensuring freedom of transit, and on the development of regional transport infrastructure. The success of these measures has been limited, and many massive investments in infrastructure seem to have had a disappointing impact on landlocked economies. Although there may still be an infrastructure gap, this book, based on extensive data collection in several regions of the world, argues that logistics and trade services efficiency can be more important for landlocked countries than investing massively in infrastructure. Logistics have become increasingly complex and critical for firms' competitiveness, and a weakness in this field can badly hurt firms based in landlocked countries. This book proposes a revised approach to tackling the cost of being landlocked and a new analytical framework which uses a microeconomic approach to assess the trade and macroeconomic impacts of logistics. It takes into account recent findings on the importance of logistics chain uncertainty and inventory control in firms' performance. It argues that: (i) exporters and importers in landlocked developing countries face high logistics costs, which are highly detrimental to their competitiveness in world markets, (ii) high logistics costs depend on low logistics reliability and predictability, and (iii) low logistics reliability and predictability result mostly from rent-seeking and governance issues (prone to proliferate in low volume environments).

Road network is a critical component of public infrastructure,and the supporting system of social and economic develop-ment.Based on a modified kernel density estimate（KDE） algorithm,this study evaluated the road service capacity provided by a road network composed of multi-level roads（i.e.national,provincial,county and rural roads）,by taking account of the differences of effect extent and intensity for roads of different levels.Summarized at town scale,the population burden and the annual rural economic in-come of unit road service capacity were used as the surrogates of social and economic demands for road service.This method was ap-plied to the road network of the Three Parallel River Region,the northwestern Yunnan Province,China to evaluate the development of road network in this region.In results,the total road length of this region in 2005 was 3.70 × 104km,and the length ratio between na-tional,provincial,county and rural roads was 1∶2∶8∶47.From 1989 to 2005,the regional road service capacity increased by 13.1%,of which the contributions from the national,provincial,county and rural roads were 11.1%,19.4%,22.6%,and 67.8%,respectively,revealing the effect of ′All Village Accessible′ policy of road development in the mountainous regions in the last decade.The spatial patterns of population burden and economic requirement of unit road service suggested that the areas farther away from the national and provincial roads have higher road development priority（RDP）.Based on the modified KDE model and the framework of RDP evalua-tion,this study provided a useful approach for developing an optimal plan of road development at regional scale.

In order to conduct successful long-term service and system architecture development, permanent infrastructures and development environment are essential. For this purpose, FMI is operating a vehicle winter testing track with advanced communication capabilities within ITS-G5 and 5G test network, along with accurate road weather data and services supported by road weather stations, IoT road weather sensor network and onboard weather measurements. The track is in Sodankylä, Northern Finland, where the long arctic winter period of more than half year allows road weather services development in (and for) severe weather conditions. This environment provides appropriate conditions for the development of advanced ITS safety services equally for traditional, autonomous and alternate energy vehicles, tailored road weather services for each special use case and accurate estimation of performance. Not forgetting the energy efficiency of traffic and communication infrastructures themselves, which are critical elements in the development of the future ITS. This paper introduces the test track infrastructures, related research ambitions and future plans.

Road freight transport is indispensable to international economic cooperation and foreign trade. Across all continents, it is commonly used for short and medium distances and in long distance haulage when minimizing time is important. In all instances governments play a critical role in ensuring the competitive advantage of private sector operators. Countries often have many opportunities to minimize the physical or administrative barriers that increase costs, take measures to enhance the attractiveness and competitiveness of road transport, or generally nurture the integral role of international road freight transport in the global trade logistics industry. Road freight transport is critical to domestic and international trade. It is the dominant mode of transport for overland movement of trade traffic, carrying more than 80 percent of traffic in most regions. Generally, nearly all trade traffic is carried by road at some point. Therefore, the cost and quality of road transport services is of critical importance to trade competitiveness of countries and regions within countries. In fact, road transport is fundamental to modern international division of labor and supply-chain management.