Fast Traveltime Research Articles

Analysis of the Choice of Transportation Modes from Lhokseumawe City to Medan City Using the Analytical Hierarchy Process Method

Interprovincial movement activities from the city of Lhokseumawe to the city of Medan is a busy travel route because land routes connect many cities. Minibusses and buses serve transportation needs across these cities. Travelers tend to choose minibusses because of their convenience, fast travel time, and the excellent level of comfort provided. The bus mode also offers smooth and comfortable travel, making it a popular choice among travelers on the Lhokseumawe to Medan route. This research aims to determine the characteristics and percentage of transportation mode choices by travelers. The approach used is the analytical hierarchy process method. The results of the analysis showed that the percentage of travelers interested in choosing a particular mode resulted in 42% of passengers choosing the Hiace Minibus, 24% choosing the Sempati Star Bus, 20% choosing the Putra Pelangi Bus, and 14% choosing the Kurnia Bus. The criteria that influence the choice of transportation mode are convenience with a percentage of 22%, time with a percentage of 19%, comfort with a percentage of 16%, cost with a percentage of 15%, headway and safety with a percentage of 14%.

Perceptions of Service Enhancements in Shared Autonomous Vehicles: A Demographic Perspective

As the pressure on urban mobility rises, shared autonomous vehicles (SAVs) offer enhanced transportation efficiency and safety. This study investigates the valuations of additional services in SAVs, examining demographics’ impact on preferences for different service features. We use data from 1723 Norwegian respondents to an online survey. We find that women put increased value on a safety host. Younger respondents value fast travel time. More tech-savvy individuals showing a higher valuation for services enhancing personal utility and comfort. Intention to use strongly predicts valuation of utilities, but not social factors.

Implementasi Algoritma A* (A-Star) untuk mencari Rute Tercepat dari Bandara Soekarno Hatta ke Destinasi Kota Tua Jakarta

The tourism sector is an economic sector that is growing rapidly. One of the best destinations that can be used as a tourist destination in DKI Jakarta is the Old City of Jakarta. The Old City of Jakarta has easy access and very affordable costs. There are many roads to the Old City of Jakarta, but the road to the Old City of Jakarta is very far away and has traffic congestion, especially towards the weekend, which could potentially make it difficult for tourists who want to visit. Therefore, we need an effective method that can help find the route with the shortest distance and fastest travel time. In this research, the method that can be used to find the fastest path or route is the A*Star algorithm. The results obtained after examining three routes (Jalan Kapuk Kamal Raya, Jalan Peta Barat and Jalan Raya Daan Mogot), obtained the fastest route with a distance of 5,881.5 KM, namely the Jalan Kapuk Kamal Raya route. By applying this method, it is hoped that it can solve the problem of determining the fastest route to the tourist location of the Old City of Jakarta.

ANALISIS PROBABILITAS PEMILIHAN MODA PUBLIC BOAT DAN FAST BOAT RUTE PENYEBERANGAN BANGSAL – GILI INDAH

The most popular modes of transportation on the crossing from Bangsal Harbor to Gili Indah are public boats and fast boats. The respective advantages and disadvantages of these two modes are that fast boats excel in fast travel times, while public boats excel in cheaper travel costs. The aim of this research is to obtain factors that influence passengers' decisions in choosing a mode, to find out user characteristics and to obtain the probability that passengers choose public boats and fast boats.Data was obtained from the results of a questionnaire using the stated preference method which offers 7 change scenarios and related choices such as cost (X1), travel time (X2), and waiting time (X3) regarding the choice of public boat and fast boat modes (Y). The results of the choices of public boat and fast boat users will be known through the proportion of public interest in each scenario. Factors that influence mode choice can be identified using multiple linear regression analysis. Then a binary logit analysis of the difference is carried out to obtain the probability of mode choice. The research results show that the utility function equation is Y = -0.3864 – 0.04299X1 – 0.06177X2 – 0.02577X3. Factors that influence passengers' decisions in choosing public and fast boats are cost (X1), travel time (X2), and waiting time (X3). Using the binary logit difference method, the probability of choosing the mode for the Bangsal-Gili Indah crossing route is public boat 79% and fast boat 21%.

Pemilihan Moda Transportasi Udara Terhadap Frekuensi Penggunaan Transportasi Udara Bandara Matahora

This research aimed to determine the characteristics of users of transportation modes and to find out the frequency of using air transportation at Matahora Airport. The research method used was quantitative with a descriptive approach, which involved depicting and explaining in detail the issues studied based on the data collected in the field. The data collection technique in this research used a questionnaire, where respondents were asked to answer a number of questions about the characteristics and factors influencing the choice of air transportation. Data analysis was conducted using descriptive data analysis to explain the data obtained through a questionnaire. The research results indicated that the characteristics of mode selection for transportation were based on reasons influencing the selection of modes from a total of 60 respondents. The analysis of the characteristics of air passenger travelers showed the largest percentage in the male gender at 68%, age between 36-45 years at 41%, the highest education level being a bachelor's degree at 62%, self-employed occupation at 36%, the reason for using air transportation being faster travel time at 93%, and the influence of mode selection on the frequency of air transportation use simultaneously at 33.4%. Partially, the factors influencing the choice of air transportation mode on frequency were cost at 26.1%, security at 12.1%, and comfort at 9.1%.

Pengaruh Preferensi Waktu dan Biaya Pada Pemilihan Moda Penumpang Kelas Ekonomi Jurusan Jember – Surabaya

The construction of the Probolinggo-Pasuruan toll road has resulted in faster travel times along the Jember-Surabaya route. However, it has been observed that economy buses rarely use the toll road. To determine the likelihood of passengers switching between economy-class train and economy-class bus modes, a study on the selection of economy-seat modes between the cities of Jember and Surabaya is necessary. The study utilized the Stated Preference method for data collection, which involved distributing questionnaires to passengers at stations and terminals. The data collected were analyzed using the binomial difference method. The results of the study reveal that the Economy-Class Train mode is the most preferred mode of transportation. Experimentation on the travel cost attribute (ΔX1) with the value of Uka-Ubu Utility = 6.512 - 0.0887(X1) + 0.292(X2) revealed that 99% of passengers chose the train. On the travel cost attribute (ΔX1) with the value of Uka-Ubu Utility = 0.0205 - 0.0034 X1, 55.2% of passengers chose the train. Meanwhile, on the travel time attribute (ΔX2) with the value of Uka-Ubu Utility = 0.0202 - 0.0034 X2, 52.6% of passengers chose the train.

Data space inversion for efficient uncertainty quantification using an integrated surface and sub-surface hydrologic model

Abstract. It is incumbent on decision-support hydrological modelling to make predictions of uncertain quantities in a decision-support context. In implementing decision-support modelling, data assimilation and uncertainty quantification are often the most difficult and time-consuming tasks. This is because the imposition of history-matching constraints on model parameters usually requires a large number of model runs. Data space inversion (DSI) provides a highly model-run-efficient method for predictive uncertainty quantification. It does this by evaluating covariances between model outputs used for history matching (e.g. hydraulic heads) and model predictions based on model runs that sample the prior parameter probability distribution. By directly focusing on the relationship between model outputs under historical conditions and predictions of system behaviour under future conditions, DSI avoids the need to estimate or adjust model parameters. This is advantageous when using integrated surface and sub-surface hydrologic models (ISSHMs) because these models are associated with long run times, numerical instability and ideally complex parameterization schemes that are designed to respect geological realism. This paper demonstrates that DSI provides a robust and efficient means of quantifying the uncertainties of complex model predictions. At the same time, DSI provides a basis for complementary linear analysis that allows the worth of available observations to be explored, as well as of observations which are yet to be acquired. This allows for the design of highly efficient, future data acquisition campaigns. DSI is applied in conjunction with an ISSHM representing a synthetic but realistic river–aquifer system. Predictions of interest are fast travel times and surface water infiltration. Linear and non-linear estimates of predictive uncertainty based on DSI are validated against a more traditional uncertainty quantification which requires the adjustment of a large number of parameters. A DSI-generated surrogate model is then used to investigate the effectiveness and efficiency of existing and possible future monitoring networks. The example demonstrates the benefits of using DSI in conjunction with a complex numerical model to quantify predictive uncertainty and support data worth analysis in complex hydrogeological environments.

Heterogeneous traffic intersections control design based on reinforcement learning

AbstractTraffic light control is a cost‐effective method to alleviate traffic congestion and deep reinforcement learning (DRL) that is increasingly favored as a method for real‐time traffic light control. However, the complexities of modern urban intersections, including crossroads and T‐junctions, pose challenges for DRL‐based traffic light control systems that do not work well for such heterogeneous intersections. To address this problem, a Heterogeneous Advantage Actor‐Critic (HA2C) model is proposed to control traffic lights for heterogeneous intersections. First, HA2C employs an intersection structure transformation scheme to mask intersection heterogeneity. Second, it develops a two‐stage approach on top of an Advantage Actor‐Critic (A2C) reinforcement learning model to learn both general and structure‐specific policies, leading to more accurate decisions. The extensive simulations on both synthetic and real‐world maps demonstrate that HA2C outperforms the state‐of‐the‐art models in terms of higher throughput and faster travel time, while using a smaller model size in most scenarios.

Using the future wheel methodology to assess the impact of open science in the transport sector

Open Science enhances information sharing and makes scientific results of transport research more transparent and accessible at all levels and to everyone allowing integrity and reproducibility. However, what future impacts will Open Science have on the societal, environmental and economic development within the transport sector? Using the Future Wheel methodology, we conducted a workshop with transport experts from both industry and academia to answer this question. The main findings of this study point in the direction of previous studies in other fields, in terms of increased innovation, increased efficiency, economic savings, more equality, and increased participation of citizens. In addition, we found several potential transport specific impacts: lower emission, faster travel times, improved traffic safety, increased awareness for transport policies, artificial intelligence improving mobility services. Several potential negative outcomes of Open Science were also identified by the expert group: job loss, new types of risks, increased cost, increased conflicts, time delays, increased inequality and increased energy consumption. If we know the negative outcomes it is much easier to put in place strategies that are sustainable for a broader stakeholder group, which also increase the probability of taking advantage of all the positive impacts of Open Science.

Penerapan Algoritma Dijkstra pada Pendistribusian Bahan Bakar Minyak di Pontianak

Determination of the shortest path or the fastest travel time is a problem that occurs to drivers of trucks loaded with fuel oil (BBM) when delivering their tanks to one of the public refueling stations (SPBU) in Pal Lima. To get to the destination, several paths that can be passed. This study aims to determine the shortest path and fastest travel time using Dijkstra's algorithm. Dijkstra's algorithm can be used on both directed and weighted graphs. The first step that must be done is to determine the starting node and destination node. After that, the calculation is carried out from the initial departure node to the neighboring node, the node with the smallest weight is used as the next calculation node. The same is done until all nodes are evaluated. Crossroads are assumed as vertices and between intersections as edges in Dijkstra's algorithm. From the results of the study, the shortest path was obtained through the Kapuas 2 Toll Road, Jl. Adi Sucipto, Jl. Imam Bonjol, Jl. Tanjung Pura, Jl. Rahadi, Jl. Mr. Love, Jl. Hassanudin, Jl. H. Rais, Pal III, Pal V with a minimum distance of 12,768 Km. For the fastest route, it is through the Kapuas 2 Toll Road, Jl. Major Alianyang, Jl. Arteri Supadio, Jl. General Ayani, Jl. Abdurrahman, Jl. Sultan Syahrir, Dr. Sutomo, Jl. Dr. Wahidin, Jl. Pal V with the fastest travel time of 27 minutes.

Transit Response to Congestion Pricing Opportunities: Policy and Practice in the U.S.

This research assesses how U.S. transit agencies have taken advantage of congestion pricing projects and answers two questions: (1) what role has transit played in U.S. congestion pricing projects, and (2) how have transit agencies responded to congestion pricing projects through service planning, operating practices, capital investment, and institutional arrangements. First, transit is seen as a direct beneficiary of congestion pricing projects since transit systems operate free of charge, thereby achieving a more reliable and/or faster travel time, thereby as well as facilitating a shift to a higher occupancy mode (buses). Second, a micro-level analysis comparing two congestion pricing projects in Northern Virginia is made.

Developing a Consistent Travel-Time Framework for Comparing Three-Dimensional Velocity Models for Seismic Location Accuracy

Location algorithms have historically relied on simple, one-dimensional (1D) velocity models for fast seismic event locations. 1D models are generally used as travel-time lookup tables, one for each seismic phase, with travel-times pre-calculated for event distance and depth. These travel-time lookup tables are extremely fast to use and this fast computational speed makes them the preferred type of velocity model for operational needs. Higher-dimensional (i.e., three-dimensional—3D) seismic velocity models are becoming readily available and provide more accurate event locations over 1D models. The computational requirements of these 3D models tend to make their operational use prohibitive. Additionally, comparing location accuracy for 3D seismic velocity models tends to be problematic, as each model is determined using different ray-tracing algorithms. Attempting to use a different algorithm than the one used to develop a model usually results in poor travel-time prediction. We demonstrate and test a framework to create first-P and first-S 3D travel-time correction surfaces using an open-source framework (PCalc + GeoTess, https://www.sandia.gov/salsa3d/software/geotess) that easily stores 3D travel-time and uncertainty data. This framework produces fast travel-time and uncertainty predictions and overcomes the ray-tracing algorithm hurdle because the lookup tables can be generated using the exact ray-tracing algorithm that is preferred for a model.

Assessing the safety effect through Google Maps usage: FMEA approach (Case study: Indonesia)

As the most popular navigation application used in Indonesia, Google Maps provides route information with the shortest route or the fastest travel time. Unfortunately, Google Maps does not consider the safety aspect regarding warnings about the unsafe roads or the unsuitability of road conditions with the type of vehicles that may increase the safety risks for road users. This research aims to assess the safety effect of Google Maps usage by using the Failure Mode and Effects Analysis (FMEA) approach to identify the results or effects of an item’s failure on system operation and to classify each potential failure according to its severity. In the end, FMEA will also analyze the safety aspects of Google Maps by determining the Risk Priority Number (RPN) as the product of severity, occurrence, and detection to prioritize the anticipatory actions, mitigations, and strategies against the highest level of risk. The data source was received from questionnaires distributed to more than a thousand respondents through an online survey that represented the user characteristics of using Google Maps in Indonesia. As the result, the potential failure mode of “Google Maps doesn't give a speeding warning” is assessed as the highest risk level of RPN, thus indicating the recommended action is by providing a speeding warning in the form of audible notification, without disturbing the driver while driving.

Skip-Stop Strategy Patterns optimization to enhance mass transit operation under physical distancing policy due to COVID-19 pandemic outbreak

After the widespread impact of the COVID-19 pandemic, all public transport, including urban rail transit, inevitably adopted a vigorous physical-distancing policy to prevent the disease from spreading among passengers. Adoption of this measure resulted in a substantial reduction in train service capability and required control of the risk contact exposure duration. Thus, this paper proposes the Skip-Stop Strategy Patterns (3S–P) decision-support model to incorporate social distancing constraints in train operations. The 3S–P model is a two-stage, multi-objective optimization model for scheduling train skip-stop patterns to satisfy the study's two main objectives of minimizing the average passenger travel time and unserved passengers. In the proposed model, the first optimization identifies the optimal train skip-stop patterns, while the second assigns these patterns to establish an hourly train schedule. The paper's case study uses data from the Bangkok Mass Transit System (BTS) SkyTrain Silom Line in Bangkok, Thailand and considers the 0.5, 1, 1.5, and 2 m social distancing schemes. The results reveal that the optimal train skip-stop patterns are superior to the all-stop alternative with, on average, a 13.4% faster travel time at the same level of unserved passengers. Furthermore, the non-dominated schedules from the second optimization decrease the numbers of unserved passengers given equal average passenger travel times.

Studi Seismik Tomografi Waktu Tempuh Untuk Identifikasi Zona Lemah dengan Menggunakan Konsep Ray Tracing Berdasarkan Algoritma Dijkstra

Tomography is a popular method in describing the subsurface based on P and S waves parameter of the seismic wave. It can show the low velocity zone or the weak zone that usually associated with the structure or fluid evidence. However, it needs some informations about the hypocenter and stations location, and the initial velocity model as the geological model. Based on the information, then ray path on each grid/block in the research area is calculated along from the hypocenter to the each station. Ray path concept is based on the Snell Law, Fermat and Hyugens principle where the wave will be dispersioned when it faces to the different medium and it will choose the medium with the fastest travel time. Then by the inversion process, the tomogram can be resulted. Dijkstra Algorithm is choosen as the basic mathematical equation for the ray path calculation because it is easy and use in some digital platform. This algorithm is provened can result the good tomogram where it can be showed the structure of the geological model.

Evaluating the use of Google Maps as navigation application by identifying hazards and assessing risks using HIRA matrix

Google Maps as a navigation application provides route information with the shortest route or fastest travel time, but this technology has a weakness as it does not consider the suitability of road condition with the type of vehicles, therefore the choice of the routes does not accommodate traffic safety aspects. This research aims to evaluate the use of Google Maps as a navigation application by identifying hazards and assessing risks. The method used is based on an analysis using the HIRA (Hazard Identification and Risk Assessment) matrix to determine the level of risk thus the step of mitigation can be executed. The data source obtained was from the results of questionnaires distributed to 1,114 respondents. As the results of analysis, it was found that 11 hazards from the usage of Google Maps came from the driver’s aspect, Google Maps feature’s aspect, and road conditions aspect. Evaluation of risks came from the three sources of hazard classified into 2 risks in the intolerable risk category and 9 risks in the tolerable risk category. After the mitigation efforts were arranged to control the risk, all risks are expected to meet the acceptable risk level. To anticipate the road traffic accident due to the usage of Google Maps, the recommendation for this navigation application is to add more features to warn the users about the road characteristics in the form of voice notification or pop up if not disturb the driver while driving and providing a specific route for truck/heavy vehicle as now the Google Maps is only available for light vehicle.

Performance Analysis of ACO and FA Algorithms on Parameter Variation Scenarios in Determining Alternative Routes for Cars as a Solution to Traffic Jams

This study proposes several alternative optimal routes on traffic-prone routes using Ant Colony Optimization (ACO) and Firefly Algorithm (FA). Two methods are classified as the metaheuristic method, which means that they can solve problems with complex optimization and will get the solution with the best results. Comparison of alternative routes generated by the two algorithms is measured based on several parameters, namely alpha and beta in determination of the best alternative route. The results obtained are that the alternative route produced by FA is superior to ACO, with an accuracy of 88%. This is also supported by the performance of the FA algorithm which is generally superior, where the resulting alternative route is shorter in distance, time, running time and there is no influence on the alpha parameter value. But in each iteration, the number of alternative routes generated is less. The contribution of this research is to provide information about the best algorithm between ACO and FA in providing the most optimal alternative route based on the fastest travel time. The recommended alternative path is a path that is sufficient for cars to pass, because the selection takes into account the size of the road capacity.

Global Tonga tsunami explained by a fast-moving atmospheric source

Volcanoes can produce tsunamis by means of earthquakes, caldera and flank collapses, pyroclastic flows or underwater explosions1–4. These mechanisms rarely displace enough water to trigger transoceanic tsunamis. Violent volcanic explosions, however, can cause global tsunamis1,5 by triggering acoustic-gravity waves6–8 that excite the atmosphere–ocean interface. The colossal eruption of the Hunga Tonga–Hunga Ha’apai volcano and ensuing tsunami is the first global volcano-triggered tsunami recorded by modern, worldwide dense instrumentation, thus providing a unique opportunity to investigate the role of air–water-coupling processes in tsunami generation and propagation. Here we use sea-level, atmospheric and satellite data from across the globe, along with numerical and analytical models, to demonstrate that this tsunami was driven by a constantly moving source in which the acoustic-gravity waves radiating from the eruption excite the ocean and transfer energy into it by means of resonance. A direct correlation between the tsunami and the acoustic-gravity waves’ arrival times confirms that these phenomena are closely linked. Our models also show that the unusually fast travel times and long duration of the tsunami, as well as its global reach, are consistent with an air–water-coupled source. This coupling mechanism has clear hazard implications, as it leads to higher waves along land masses that rise abruptly from long stretches of deep ocean waters.

Determining Travel Time and Fastest Route Using Dijkstra Algorithm and Google Map

Dijkstra's algorithm is commonly used to determine the shortest route connecting a point as a starting node to another which acts as the end node. In this study, the UNP student dormitory acted as the starting node, while the library which is frequently visited by students was sampled from the campus as the end node. Due to the fact that students generally live around campus and move on foot, an alternative route is needed to determine the fastest travel time. Therefore, this study aims to determine the route with the fastest travel time from the start to the end of nodes using the Dijkstra algorithm, in comparison with the route displayed by Google Map. Data were obtained from Google Map, which showed the availability of many routes with the possibility of students taking the fastest travel time. The result showed that the fastest route using the Dijkstra algorithm and Google Map were 14 and 3 alternatives at 15 and 21 minutes intervals. Based on these data, it is concluded that the travel time through the fastest route obtained using the Dijkstra algorithm was 6 minutes faster than data found in the Google Map.

HUBUNGAN BUDAYA KESELAMATAN DAN PERILAKU BERKENDARA AMAN PENGEMUDI DI JALAN TOL PEKANBARU DUMAI

The role of transportation for the community has a tremendous impact, especially in daily life activities. In transportation sector, especially land transportation, toll road has a major role in determining the pace of the economy and the level of community prosperity. The condition of the toll road with the facilities available on it capable of supporting the movement of vehicles with a high average speed and in a fast travel time can be considered as an adjustment solution to increase mobility, but in fact these conditions lead to potential traffic accidents. Implementation of safety driving related to the phenomenon of traffic accidents which are the main concern or problem on toll road by creating a decent safety culture. Safety culture is a tendency of attitudes, beliefs, and perceptions that naturally spread within groups that are embodied in rules and values, which are seen in how they act in relation to risk and control systems. This study aims to determine the relationship between safety culture and safety driving among drivers of Pekanbaru Dumai toll road. The subject of this study found 60 drivers who use the Pekanbaru Dumai toll road. Researchers used a safety culture and safety driving questionnaire.The results of this study indicate a very significant positive relationship between safety culture and safety driving, with r = 0.732, p <0.01, r2 = 0.536. It can be concluded that safety culture is one of the factors safety driving among drivers Pekanbaru Dumai toll road with percentage of effect 53.6%, although only one dimension is significant with safety driving.