Benchmarking Multi-Platform APIs and Fuzzy-AHP for Enhanced HAZMAT Emergency Logistics: A Case Study of Bangkok’s Expressway Network

In many cities, Intelligent Transport Systems (ITS) are mainly based on sensing technologies installed on roads to monitor real-time traffic and predict journey time. Although the Transport Department in Hong Kong publishes the collected traffic data for the public to access, its ITS only covers some major roads, highways and tunnels. Recently, Web mapping services (e.g., Google Maps and Microsoft Bing Maps) are new popular sources for many location-based applications to access real-time traffic data, predicted journey time and other location-based services. In this paper, we conduct a comparative analysis on the journey time data derived from Google Maps and the ITS in Hong Kong. We first describe the underlying technologies of these two sources, and then conduct experiments to compare the journey time data derived from them for four route sets of a total of 35 major routes during two weeks in Hong Kong. Experimental results indicate that the p-values of the journey time data from the two sources are consistent with each other for most routes throughout the entire day; and the differences are acceptable. As a result, Google Maps provides high-quality real-time traffic data in Hong Kong. Due to the high deployment cost and limited coverage of the ITS, Google Maps is the promising source for location-based applications to access real-time journey time data.

Transportation is one of the most critical factors affecting the economic development and welfare of a country. Effective transport systems create socio-economic opportunities and benefits by facilitating access to markets, jobs, and investments. Moreover, transportation shows a rapid change in today's world of globalization and economic growth. With the rapid development of information and technology, the demand for higher, faster, safer, and more comfortable transportation is emphasized. On the other hand, with the development of the automotive industry, increased vehicle traffic volumes cause congestion, delays, travel time, resource consumption, environmental problems, and accidents. Systems need to be designed to be more efficient, effective, safe, and economical to reduce these adverse outcomes of transportation systems and meet user demands. For this reason, the concept of "Intelligent Transportation Systems (ITS)" has emerged. ITS provide economic, environmental, and socially sustainable solutions, in particular by ensuring that information is accessed quickly and efficiently. The analysis of ITS are very complicated since it has many conflicting objectives and many different criteria. Multi-criteria decision-making (MCDM) is a powerful tool widely used for solving this type of problems. Therefore, in this study, we aim to propose a strategic analysis of ITS by using MCDM methods. In the proposed methodology, ITS criteria are weighted with fuzzy Analytic Hierarchy Process (AHP) and fuzzy Evaluation Based on Distance from Average Solution (EDAS) is used to select the most appropriate ITS strategy. Finally, an application is provided to demonstrate the potential use of the proposed methodology

Chapter 52 - Hazardous Materials Response

When treating patients involved in hazardous materials (HazMat) incidents, rapid action is essential to stop exposure and provide appropriate care. Uncertainty about secondary exposure, however, may lead to unnecessary protective measures and delayed treatment. A clear distinction between exposure and contamination is crucial. Decontamination is only indicated when hazardous substances remain present on the patient's skin, hair, or clothing; it is not required after isolated ingestion or inhalation without skin involvement. Available evidence shows that the risk from secondary exposure of healthcare providers is very low. In most situations outside the source area, standard personal protective equipment (PPE: gloves and apron, supplemented with FFP2 mask and eye protection when particulate matter is involved) provides sufficient protection to safely perform triage and lifesaving interventions. More extensive PPE may be considered during prolonged decontamination procedures or large-scale incidents. Early communication and consultation with hazardous materials advisors support a proportional and safe approach to patient care.

The toxic release of aldehyde vapours during a hazardous material (HAZMAT) incident primarily results in respiratory concerns for the unprotected public. However, skin absorption may be an important concurrent exposure route that is poorly understood for this scenario. This study provides experimental data on the skin absorption properties of common aldehydes used in industry, including acetaldehyde, acrolein, benzaldehyde and formaldehyde, in gaseous or vapour form using an adapted in vitro technique. Two of the four tested aldehydes were found to penetrate the skin in appreciable amounts following 30-min exposure at HAZMAT relevant atmospheric concentrations: acetaldehyde (5.29 ± 3.24 µg/cm2) and formaldehyde (3.45 ± 2.58 µg/cm2). Whereas only low levels of acrolein (0.480 ± 0.417 µg/cm2) and benzaldehyde (1.46 ± 0.393 µg/cm2) skin penetration was noted. The aldehydes demonstrated differing levels of interaction with fabric. Formaldehyde and acetaldehyde adsorbed strongly to denim, whereas benzaldehyde and acrolein displayed no sink properties. However, denim was shown to be an initial protective barrier and reduced penetration outcomes for all aldehydes. This study provides important information to assist first responders and confirms the relevance of using physicochemical properties (e.g. solubility, molecular weight, partition coefficient) to predict skin permeation potential in the absence of empirical data during HAZMAT incidents involving different types of aldehydes.

Recent rapid development of intelligent transportation systems (ITS) makes it possible to improve the efficiency and reliability of transportation networks. Several articles have been presented regarding this topic in the Special Issue of Journal of Advanced Transportation. Wang and Khattak indicated that there is spatial heterogeneity in information acquisition and user decisions. Bekhor and colleagues showed that cellular phone technologies could be used to provide travel data for development of national travel demand model. Based on the deployment of automatic vehicle identification (AVI) technology in urban road network in Beijing, China, Feng and co-researchers proposed a particle filter method for vehicle trajectory reconstruction with the use of AVI and traffic count data. Yang and co-researchers proposed two proactive VSL control models for use on recurrently congested freeway segments. The embedded traffic flow relationships are adopted in the first proactive model to predict the evolution of congestion pattern and to optimize the speed limit on freeway segments with VSL. Using multi-source sensor data, Lu and researchers proposed a Kalman filter model for estimation of time-dependent origin?destination (OD) matrix that is a key input to the self-adaptive traffic control systems for real-time traffic management.

Compared to traditional logistics, the emergency logistics show the characteristics of sudden, uncertainty, time urgency. The regular commercial maps used in the traditional logistics system (such as Baidu map, Google map), cannot satisfy the need that the emergency logistics will plan the best route autonomouslyin order to ensure the rescue time under the condition of disaster. Openstreetmap (OSM) is an open sourcemap which the greatest strength is the open data and the free secondary development. In this paper, we designed three parts on the Android terminal including the view layer, the logic control layer and data interaction layer based on the OSM data and the REST service interface which the ArcGIS Server provides; The system has achieved the offline maps reading and parsing function and real-time locationfunction. So it will combine the open source OSM with emergency logistics demand and provide a reference for the emergency logistics to plan the bestroute.

Public transportation has been encouraged as a significant solution to overcome traffic congestion. An advanced technology, known as advanced public transport system (APTS), was introduced to enhance the effectiveness of public transportation. To support appropriate decisions on selecting application development, significant indicators representing the impacts of the proposed projects are highlighted. This study aims to determine the desirable indicators of developing APTS to achieve smart mobility using the fuzzy Analytical Hierarchy Process (fuzzy AHP) method and allocating weights to each indicator. The perception of a group of intelligent transport system (ITS) experts from three sectors in the Bangkok Metropolitan Regions (BMR) was examined to conduct a fuzzy AHP pairwise comparison. The ranking of 21 indicators categorized within six dimensions in accordance with the specific ITS master plan relating to APTS development is presented. The result presented that the safety dimension obtained the highest rank, and the three most important weight indicators are traffic accident reduction relating to public transportation, smart public transport network density and waiting time for public transportation. In addition, the perspectives towards APTS development and assessment framework development in BMR is highlighted to revise impediment of regulation and encourage integration among stakeholders. Then, the approaches of the APTS evaluation framework in BMR are proposed.

Mobility is essential to the economic growth of any modern country and the well- being of its population. This is especially true for the United States because of its size and diffuse population. Without the efficient transport of people and goods, U.S. industries cannot compete effectively with overseas producers. However, the rapid growth in demand and the slower growth in the capacity of highway systems have led to congestion that is estimated to cost more than $40 billion annually. In 1970, motorists in the United States drove approximately 1 trillion vehicle-miles; by 1985, this had increased to 1.8 trillion vehicle-miles; and, by 2000, to 2.8 trillion vehicle-miles. These increases have led to serious congestion problems. For example, peak-hour traffic operating in congested conditions on urban Interstate highways increased from 40 percent in 1970 to nearly 70 percent in 1990. From 1982 to 2002, the vehicle-miles traveled increased by 79 percent, whereas highway-lane miles increased by only 3 percent. The number of roadways considered congested grew from 34 to 58 percent. However, construction of the more than 40,000 miles of the multilane, controlled-access Interstate Highway System essentially is completed. Major new construction, especially in dense urban areas, generally is not feasible and definitely cannot keep up with future traffic demand. Although some growth of the highway system is inevitable, the more efficient use of the existing system is essential. In recent decades, there also have been tremendous changes in the areas of information technology, electronics, computers, and communications. The pace of these developments is simply astounding, and electronic devices have infiltrated every aspect of life, including vehicles (see Chapter 1). Intelligent Transportation Systems (ITS) (formerly known as Intelligent Vehicle Highway Systems [IVHS]), however, represent more than simply advances in automotive electronics. ITS incorporate a wide variety of electronic-based technologies, both on the vehicle and as part of the highway infrastructure, which collectively are moving the world into the next generation of highway operations. These technologies offer the promise of increased throughput on existing highways at reduced congestion levels as well as improved safety and convenience. The ITS vision encompasses smart (i.e., control, sensing, and communications) automobiles and highways collaborating for improved safety, mobility, trip quality, and productivity while also reducing congestion and environmental impact.

Several Intelligent Transportation Systems (ITS) rely on localization to enable services ranging from comfort to safety applications. Following this same idea, the use of Dedicated Short Range Communications (DSRC) devices based on the IEEE 802.11p standard, and the Vehicular Ad Hoc Networks (VANETs) paradigm, have resulted in the deployment of several protocols, services and applications that need different localization accuracy levels. The most common solution for localization is based on Global Navigation Satellite Systems (GNSS). GNSSs have problems of unavailability in dense urban areas, tunnels and multilevel roads. Moreover, GNSS have errors in the range of 5–15 meters. These unavailability and error problems are not acceptable for several VANET and ITS safety applications. In this work, we investigate and characterize the GNSS problems of error and unavailability based on datasets of real GNSS devices installed in vehicles and develop a Geodesic Dead Reckoning solution to overcome the GNSS unavailability issue.

Current map-matching algorithms for transport applications: State-of-the art and future research directions

Hazardous materials (HazMat) incidents pose significant risks to public health, safety, and the environment. This study aimed to characterize the temporal trends, geographic distribution, operational settings, and incident types of HazMat events reported in Oman. This retrospective descriptive study analyzed data from the national HazMat incident records maintained by the Civil Defence and Ambulance Authority (CDAA). All reported chemical, biological, or radiological incidents between June 1, 2019, and November 30, 2024, were included. A total of 55 HazMat incidents were recorded during the study period. Reported incidents increased over time, with the highest annual counts observed in 2023 (14 incidents) and 2024 (17 incidents). Muscat Governorate accounted for 39 incidents (71%). Residential neighborhoods were the most common operational setting (26/55, 47%), followed by other public areas (9/55, 16%), while airports, educational institutions, industrial areas, and transportation corridors each accounted for 5 incidents (9%). Gas leaks were the most frequently reported incident type, involved in 28 incidents (51%). HazMat incidents in Oman increased over the study period and were concentrated in Muscat Governorate. Incidents occurred across diverse operational settings, particularly residential and public environments, while gas leaks represented the most frequently reported incident type.

Transportation-Related Hazardous Materials Incidents and the Role of Poison Control Centers

Transport policy in Korea is driven by the need to cope with ever-worsening traffic conditions. The development of an intelligent transport systems (ITS) Master Plan for Korea is of particular interest and demonstrates the heavy reliance placed on ITS measures to facilitate both the management of congested (but expanding) highway networks and to encourage a shift to greater use of public transport. The paper highlights the major achievements of ITS in Korea by assessing the evidence provided by the widespread implementation of ITS technologies (such as the creation of 'showcase' demonstrations). Some observations from the implementation of ITS in (so-called) transitional economies are presented.

In this work, we propose the Road Data Enrichment (RoDE), a framework that fuses data from heterogeneous data sources to enhance Intelligent Transportation System (ITS) services, such as vehicle routing and traffic event detection. We describe RoDE through two services: (i) Route service, and (ii) Event service. For the first service, we present the Twitter MAPS (T-MAPS), a low-cost spatiotemporal model to improve the description of traffic conditions through Location-Based Social Media (LBSM) data. As a case study, we explain how T-MAPS is able to enhance routing and trajectory descriptions by using tweets. Our experiments compare T-MAPS' routes against Google Maps' routes, showing up to 62% of route similarity, even though T-MAPS uses fewer and coarse-grained data. We then propose three applications, Route Sentiment (RS), Route Information (RI), and Area Tags (AT), to enrich T-MAPS' suggested routes. For the second service, we present the Twitter Incident (T-Incident), a low-cost learning-based road incident detection and enrichment approach built using heterogeneous data fusion. Our approach uses a learning-based model to identify patterns on social media data which is then used to describe a class of events, aiming to detect different types of events. Our model to detect events achieved scores above 90%, thus allowing incident detection and description as a RoDE application. As a result, the enriched event description allows ITS to better understand the LBSM user's viewpoint about traffic events (e.g., jams) and points of interest (e.g., restaurants, theaters, stadiums).