Real Route Research Articles

Transfer of Personal Driving Styles to Autonomous Vehicles

This paper presents a learning model that can be implemented on autonomous vehicles, using a dedicated software platform, based on physics, which can also be used to track the behavior of components and subsystems of the vehicle. In order to prepare the data for entering the software platform, data (position, orientation, acceleration, instantaneous speed) were recorded from a vehicle driven by several drivers on a previously established route. By processing the data, a driving style was established based on the average values recorded, for each subject who participated in the experimental tests. A virtual environment was created to correspond to the real route in which an autonomous vehicle was modeled and the data on the previously established driving style (instantaneous speeds vs. positions) were transferred. Following the running in the virtual environment and the registration of the data about the behavior of the vehicle on the established route, the data obtained by the classical method and the virtual simulation were compared. Thus, corrections can be made on the speed profile implemented for the autonomous vehicle, in order to comply with the limits imposed by the use of this vehicle with passengers: speed limits, longitudinal and lateral acceleration limits, braking limits.

PENTANAAN JARINGAN TRAYEK ANGKUTAN PERKOTAAN DI KOTA BOGOR

Bogor city is mostly occupied by public transport. Nowadays, the number of routes of public transport routes in Bogor city is 24 routes. However, in the implementation there are mostly routes of public transport that are overlapping. This study is doing because the overlapping of routes of public transport is beyond 50% and it made the load factor in each route become low. The method that I did was collecting data with dynamic survey and static survey for anlalyzing the real condition of public transport routes and other data like interviews, Home Interview, and Road Side Interview for predicting the demand of trips that are processed in VISUM app to get the demand of trips on each road as a basis to make new suggestion routes for public transport. The last step is to analyze and to compare the real routes and the suggestion routes. Both performance of routes and performance of operational. After all of those analyses we only need 14 routes of public transport, so it is expected to increase the load factor of public transport by 70%

RENUMBERING IN CITY WITH HIERARCHICAL CLUSTERING METHOD OF BUS STATION NUMBERS: THE CASE OF KAHRAMANMARAŞ PROVINCE

Bus stations are one of the most widely used components of the public transportation system by citizens. Many critical information, such as the list of bus lines passing through the station, the station-based schedule of the bus lines and when the vehicle operating in the transportation system will pass through the station, are calculated and published according to the station number. For this reason, the station number is being memorable by the citizens and the station numbers of the bus stations, which are spatially close to each other, are numerically very close to each other, are very important in terms of easy learning of the station number. Bus station numbers are usually numbered according to the order in which the line routes pass through the stations. However, considering this case, there is a huge difference between the inconsistency in the station numbers and the station numbers of the stations that are spatially close to each other, when the line route is changed or when the station numbers and the order of passing from the stations are different for different lines passing through the same station. In this study, a hierarchical clustering-based new approach has been proposed to eliminate the problems in bus station numbers and to set bus station numbers that are spatially close to each other. The proposed approach was carried out using the real bus line route and bus station data of Kahramanmaraş Metropolitan Municipality. In the experimental evaluations, the difference between the bus station numbers created by the classical method and the difference of the bus station numbers created by the hierarchical clustering method that spatially close to each other were compared. Experimental results show that the proposed hierarchical-based clustering method creates a closer number of station that are spatially close to each other when compared to the classical method.

ANALISA OPTIMASI RUTE TRANSPORTASI ANTAR JEMPUT SISWA MENGGUNAKAN METODE CGVRP DAN ALGORITMA DIJKSTRA DI SDIT SAMAWA CENDEKIA

The school bus is one of the means of transportation prepared by several schools as a means of shuttle to make it easier for their students to travelin school activities, so that in the pick-up process a better route is neededoptimally to save fuel. The purpose of this research is to compilemodel of shuttle transportation routes for students with the Clustered Generalized modelVehicle Routing Problem (CGVRP) then the model is solvedusing Dijkstra's Algorithm and comparing the distance between real transportation routespick-up with route distance using the CGVRP model and Dijkstra's Algorithm. ModelCGVRP uses the Djikstra Algorithm which is applied to the shuttle case studystudents at SDIT Samawa Cendekia are more efficient than the longer distancesused before. It is known that the real distance at SDIT Samawa Cendekia is2,627,424 meters at a cost of Rp. 2,118,384 in a month. While the distance on the routethe proposal obtained 2,389,128 meters at a cost of Rp. 1,926,757 in a month. Sothe difference between the distance from the real route and the proposed route is 238,296 meters with a difference ofcost Rp. 191,604 in a month.

Collision avoidance path planning of tourist ship based on DDPG algorithm

Objective As the core issue of ship navigation safety, ship collision avoidance always depends on the captain's personal status and judgment, which has certain potential safety hazards. In order to coordinate all ships (cruise ships, cargo ships, etc.) in key waters and predict their paths, it is necessary to establish an anti-collision early warning mechanism. Methods Using the deep deterministic policy gradient (DDPG) algorithm and the ship domain model, the electronic chart is used to simulate the ship's navigation path, and the improved strategy of DDPG algorithm based on the key learning of failure region and the improved parameters of ship domain model according to the characteristics of cruise ships are proposed, Improve the accuracy of route prediction and anti-collision. Results Using the improved DDPG algorithm and the improved ship domain model, compared with the previous algorithm, the accuracy of ship collision avoidance is improved from 84.9% to 89.7%, and the average error between the simulated route and the real route is reduced from 25.2 m to 21.4 m. Conclusion Through the ship collision avoidance path planning based on the improved DDPG algorithm and the improved ship domain model, the ship route supervision function in water area can be realized, and when the predicted route intersects with other ships, the dispatcher will be alerted to realize the anti-collision early warning mechanism.

Genre Originality of Travel Cycle in Modern Russian Poetry (“Indian cycle” by V. Polozkova)

The article is devoted to the study of genre features of the lyrical cycle of travel in modern poetry on the example of “Indian Cycle” (2008) by Vera Polozkova. The relevance of the study is due to the need to comprehend the lyrical cycle of travel as a synthetic genre form, in the structure of which various kinds of changes take place, first of all, genre features of the lyric cycle and travelogue are synthesized. The study of this genre form makes it possible not only to determine the originality of the author's creative manner and his place in the modern literary process, but also to trace the main trends in the development of the lyric cycle of travel in modern Russian poetry as a whole. The novelty of the research lies in the identification of genre, problem-thematic, compositional features of the “Indian Cycle”, which makes it possible to draw a conclusion about the expansion of the genre-typological features of the travel cycle due to additional lyrical motives (landscape, philosophical, love). It is established that the lyrical cycle of V. Polozkova’s travel is built along a real geographical route, the image of the country being visited becomes a plot-forming basis. In the course of the study, the peculiarities of the artistic perception of the geographical, cultural and historical space of the eastern country, national spirit and attributes are revealed. The features of the influence of the travel route on the inner world of the lyrical heroine are analyzed. Cultural codes and clichés associated with stereotypical perception of India are being rethought. The work proves that V. Polozkova's "Indian Cycle" clearly demonstrates the trend of genre synthesis emerging in contemporary poetry.

Estimating congestion zones and travel time indexes based on the floating car data

Efficiently predicting traffic congestion benefits various traffic stakeholders, from regular commuters and logistic operators to urban planners and responsible authorities. This study aims to give a high-quality estimation of traffic conditions from a large historical Floating Car Data (FCD) with two main goals: (i) estimation of congestion zones on a large road network, and (ii) estimation of travel times within congestion zones in the form of the time-varying Travel Time Indexes (TTIs). On the micro level, the traffic conditions, in the form of speed profiles were mapped to links in the road network. On the macro level, the observed area was divided into a fine-grained grid and represented as an image where each pixel indicated congestion intensity. Spatio-temporal characteristics of congestion zones were determined by morphological closing operation and Monte Carlo simulation coupled with temporal clustering. As a case study, the road network in Croatia was selected with spatio-temporal analysis differentiating between the summer season and the rest of the year season. To validate the proposed approach, three comparisons were conducted: (i) comparison to real routes' travel times driven in a controlled manner, (ii) comparison to historical trajectory dataset, and (iii) comparison to the state-of-the-art method. Compared to the real measured travel times, using zone's time-varying TTIs for travel time estimation resulted in the mean relative percentage error of 4.13%, with a minor difference to travel times estimated on the micro level, and a significant improvement compared to the current Croatian industrial navigation. The results support the feasibility of estimating congestion zones and time-varying TTIs on a large road network from FCD, with the application in urban planning and time-dependent routing operations due to: significant reduction in the data volume without notable quality loss, and meaningful reduction in the pre-processing computation time.

Methodological Approach to the Formation and Evaluation of the Quality of Operation of Urban Public Transport Services

In this work, the theoretical aspects of the formation of operational qualities of rolling stock used in urban public transport, its services on the basis of operational characteristics are studied, and a methodology for assessing the operational quality of real routes served by bus companies is proposed.

Spatiotemporal Features—Extracted Travel Time Prediction Leveraging Deep-Learning-Enabled Graph Convolutional Neural Network Model

Travel time prediction is one of the most important parameters to forecast network-wide traffic conditions. Travelers can access traffic roadway networks and arrive in their destinations at the lowest costs guided by accurate travel time estimation on alternative routes. In this study, we propose a long short-term memory (LSTM)-based deep learning model, deep learning on spatiotemporal features with Convolution Neural Network (DLSF-CNN), to extract the spatial–temporal correlation of travel time on different routes to accurately predict route travel time. Specifically, this model utilizes network-wide travel time, considering its topological structure as inputs, and combines convolutional neural network and LSTM techniques to accurately predict travel time. In addition to their spatial dependence, both coarse-grained and fine-grained temporal dependences are fully considered among the road segments along a route as well. The shift problem is formulated in the coarse-grained granularity to predict the route travel time in the next time interval. The experimental tests were conducted using real route travel time obtained by taxi trajectories in Harbin. The test results show that the travel time prediction accuracy of DLSF-CNN is above 90%. Meanwhile, the proposed model outperformed the other machine learning models based on multiple evaluation criteria. The RMSE (Root Mean Squard Error) and R2 (R Squared) increased by 18.6% and 22.46%, respectively. The results indicate the proposed model performs reasonably well under prevailing traffic conditions.

Fatigue life prediction for locomotive bogie frames using virtual prototype technique

Current research papers use simulated load spectrums to assess bogie frames’ fatigue life but seldom consider traction and braking loads. Traction and braking loads play important roles in predicting fatigue life in high-speed and heavy haul operational scenarios. Hence, there is a research gap in terms of the consideration of longitudinal load spectrums while assessing bogie frames’ fatigue life. This paper presents research about this topic. A virtual prototype technique available in literature has been extended for this purpose; it uses multibody dynamics and finite element techniques to simulate the behaviour of bogie frames under real operational service loads. As a result, the special simulation methodology has been developed in this work and it includes the unique integration of simulation approaches that includes train dynamics, locomotive dynamics with the consideration of a traction control algorithm and the adopted fatigue life calculation method. This paper gives numerical examples of a rigid-flexible coupled dynamic railway vehicle model subjected to longitudinal forces. Road Environment Percent Occurrence Spectrum (REPOS) load spectrums of the bogie frame were developed from a whole-trip train simulation on a real route. The spectrums are then used to predict locomotive the bogie frame’s fatigue life. The results of the bogie frame fatigue life evaluation performed in this paper show that fatigue lives at the roots of traction rod seats under longitudinal load spectrums are shorter than their fatigue life under vertical load spectrums.

Theoretical research of the external temperature influence on the traction and speed properties and the fuel economy of cargo-carrying vehicles

The aim is to develop a methodology for determining analytically the fuel consumption in a hot climate and substantiate reliability, as well as the possibility of its application by comparison with test results. The article proposes analytical methods for calculating fuel economy and traction-speed properties when modeling the movement of cargo-carrying vehicles on real routes, based on theoretical and experimental studies in a hot and dry climate, which allows for determining the efficiency of cargo-carrying vehicles objectively in terms of traction and speed, fuel and economic indicators. Using the statistical processing of experimental, theoretical research data, the authors calculate the coefficient X2, which allows for evaluating the adequacy of the mathematical model and experimental data. The paper provides for an assessment of fuel economy and traction and speed properties. The authors presented the results in graphs for the ease of evaluating the effect of external temperature on fuel consumption and the average speed of a road train. The authors' methodology allows for determining the efficiency of cargo-carrying vehicles in a hot and dry climate.

Energy method of assessing and systematizing open pit automobile transport operating conditions

Research aim is to develop the method of assessing and systematizing open pit automobile transport operating conditions. Research relevance. Pit depth growth and the introduction of modern models of dump trucks capable of working on 18–24% slopes complicate the conditions of industrial vehicles operation. In this regard, the development of the method and indicators of rock mass transportation difficulty becomes relevant as well as the systematization of vehicles operation conditions. Research methodology. The method of evaluating the difficulty of transportation is based on calculating diesel consumption per one haul cycle and reducing the actual length of the route to the relative horizontal distance with the use of rock mass vertical haul horizontal equivalents. Experimental and analytical dependences for horizontal equivalents have been determined. As a criterion of transportation difficulty evaluation, the use of operation conditions difficulty coefficient has been substantiated showing how many times truck’s power consumption when moving along the real route is higher than power consumption when moving along the horizontal macadamized route of the same length. Results. As a result of the research, the method of assessing and systematizing the operation conditions of open pit automobile transport. It has been determined that maximum values for conditions difficulty ISSN 0536-1028 «Известия вузов. Горный журнал», № 8, 2020 25 coefficients for the trucks with 4 × 2 wheel configuration are 2.6–3.0, and for all-wheel drive trucks – 5.0–6.5. By the difficulty coefficient, all operating conditions are divided into 5 classes (relatively easy, medium, difficult, very difficult, and extremely difficult). It has been determined that operating conditions in the most of diamond-mining open pits of ALROSA PJSC refer to class 3 and 4 (difficult and very difficult). The introduction of the all-wheel drive trucks will go along with the transition of operating conditions to class 5 (extremely difficult). For most of Ural pits classes 2 and 3 are typical (medium and difficult). Scope of results. Research results are to be used in open pit automobile transport design and operation when assessing and systematizing operating conditions, in technological calculations when regulating and planning diesel consumption and dump trucks capacity, and when correcting the regulatory standards of maintenance support, etc.

Adaptive real-time energy management control strategy based on fuzzy inference system for plug-in hybrid electric vehicles

A novel control strategy for the adaptive real-time energy management of a commuter pull-in hybrid vehicle is proposed. The proposed strategy can adapt to various driving conditions so that fuel economy can be improved further in practice. Its main feature is that a fuzzy inference system (FIS) for online estimation of the reference SOC and an adaptive update law with traffic recognition are blended into the main frame of an adaptive-equivalent consumption minimization strategy (A-ECMS). The FIS is established through an adaptive neuro-fuzzy inference system (ANFIS) that is offline trained by the traffic information extracted from historical traffic data and the reference state of charge (SOC) optimized by dynamic programming (DP). The adaptive update law with traffic recognition means that the adaptive equivalent factor (A-EF) of the real-time A-ECMS is adjusted online according to the traffic information in the real route besides the SOC of the vehicle battery. This is because the initial A-EF and the proportional–integral coefficients of the A-EF adjuster are mappings of the SOC and the traffic road segment, and the mappings are optimized by particle swarm optimization (PSO) according to the different initial SOC and the real historical driving cycles of each segment. The proposed strategy is carried out on the simulation test platform integrated GT-Suite simulator and MATLAB/Simulink. The simulation results show that the proposed strategy can reach an optimal energy distribution on a near global optimal level (close to the level of dynamic programming (DP) under the deterministic driving condition). Compared with a rule-based (RB) strategy, the traditional ECMS, an A-ECMS with the linear SOC reference, an A-ECMS with the EF optimized by PSO and an A-ECMS with the A-EF adjusted by a fixed PI feedback controller of the SOC, the fuel consumption is reduced by an average of 22.98% 10.26% 6.52% 2.33% and 5.91% respectively.

Mental Maps and the Use of Sensory Information by Blind and Partially Sighted People

This article aims to fill an important gap in the literature by reporting on blind and partially sighted people's use of spatial representations (mental maps) from their perspective and when travelling on real routes. The results presented here were obtained from semi-structured interviews with 100 blind and partially sighted people in five different countries. They are intended to answer three questions about the representation of space by blind and partially sighted people, how these representations are used to support travel, and the implications for the design of travel aids and orientation and mobility training. They show that blind and partially sighted people do have spatial representations and that a number of them explicitly use the term mental map. This article discusses the variety of approaches to spatial representations, including the sensory modalities used, the use of global or local representations, and the applications to support travel. The conclusions summarize the answers to the three questions and include a two-level preliminary classification of the spatial representations of blind and partially sighted people.

Automatic ship route design between two ports: A data-driven method

With the forced installation of the ship's automatic identification system (AIS), a large amount of ship trajectory data in the world is generated. These data provide information on latitude, longitude, speed and course, and plenty of materials for maritime pattern extraction and vessel behavior prediction. And how to dig into these AIS data deeply to discover the ship behavior pattern is an important job. There are two key points on the automatic ship route design research: the turning area generation and the turning area linkage. In this paper, we integrate DBSCAN and Artificial Neural Network capable of automatic ship route design based on massive AIS data between certain ports. The main purpose of this study is to recognize the key regions by applying DBSCAN algorithm and then connect these regions automatically by cluster similarity measuring. Then artificial neural network has been used to learn the relationship of turning regions and generate a reasonable route with different ship dimensions. The main achievement of this study have twofold. First, a research framework for automatic generation of ship route is proposed. We can process big AIS data and use them to generate ship route. Second, generation of different routes according to ships of different dimension under the research framework. The method is capable of generating ship route automatically according to different ship dimensions, which has been evaluated on two real routes around the world.

Pedestrian navigation system based on the inertial measurement unit sensor for outdoor and indoor environments

Abstract. With the continuous improvement of the hardware level of the inertial measurement unit (IMU), indoor pedestrian dead reckoning (PDR) using an inertial device has been paid more and more attention. Typical PDR system position estimation is based on acceleration obtained from accelerometers to measure the step count, estimate step length and generate the position with the heading received from angular sensors (magnetometers and gyroscopes). Unfortunately, collected signals are very responsive to the alignment of sensor devices, built-in instrumental errors and distortions from the surrounding environment. In our work, a pedestrian positioning method using step detection based on a shoe-mounted inertial unit is arranged and put to the test, and the final results are analyzed. The extended Kalman filter (EKF) provides estimation of the errors which are acquired by the XSENS IMU sensor biases. The EKF is revised with acceleration and angular rate computations by the ZUPT (zero velocity update) and ZARU (zero angular rate update) algorithms. The step detection associated with these two solutions is the perfect choice to calculate the current position and distance walked and to estimate the IMU sensors' collected errors by using EKF. The test with a shoe-mounted IMU device was performed and analyzed in order to check the performance of the recommended method. The combined PDR final results were compared to GPS/Beidou postprocessing kinematic results (outdoor environment) and to a real route which was prepared and calculated for an indoor environment. After the comparison, the results show that the accuracy of the regular-speed walking under ZUPT and ZARU combination in the case of outdoor positioning did not go beyond 0.19 m (SD) and for indoor positioning accuracy did not exceed 0.22 m (SD). The authors are conscious that built-in drift errors coming from accelerometers and gyroscopes, as well as the final position obtained by XSENS IMU, are only stable for a short time period. Based on this consideration, our future work will be focused on supporting the methods presented with radio technologies (WiFi) or image-based solutions to correct all IMU imperfections.

Pre-Control Strategies for Downstream Bus Service Reliability With Traffic Signal

As an undesired behavior of the transport system, headway fluctuation or even bus bunching reduce reliability of bus stop service for waiting passengers. This paper proposes a pre-control method to improve the balance of service intervals at downstream stop through an adjustment of green time for bus passing, in which priority and delay of bus passing can be achieved. The proposed pre-control strategies at intersection are triggered based on prediction of service intervals at downstream stop to select priority or delay strategy that includes adjusting starting and ending time of green light. Meanwhile, the influence of adjustment of green time on surrounding traffic delay of vehicle is also considered. The traffic delay is estimated for vehicles arriving during phases within associated two signal cycles induced by the signal adjustment. To derive optimal adjustment of green time, a multi-objective function is established and the objectives include deviation of the bus service intervals and traffic average delay. An exhaustive search algorithm is programmed to solve the objective function. The effects of control strategies are tested by numerical experiments based upon a real bus route in Changchun. Results show that the bus service reliability can be improved through a proper signal pre-control and, compared with the single control strategy with only bus delay, the standard deviations of service intervals with the average running time and the stochastic running time are improved by 8.53% and 7.31%, respectively.

The Challenging Relationship between Contemporary Art and Intellectual Property

Nowadays, the contemporarily concept of intellectual property rights is a challenging problem, because it includes many ideas like innovation, invention, copyright, trademark and creativity and/or others of these kind. The legislation of intellectual property right is one of the most challenging ones not only in Albania but also in the most developed countries. A successful entrepreneur (Craig Venter) thinks that it is the key for the economic development and prosperity. The intellectual property plays a crucial role while being applied in the business, biotechnology and artificial intelligence. Its legislation is very recent and needs to be updated or modified so that countries should be able to anticipate any gaps of the legal framework that may be generated in future due to innovation and invention. Soon, Albania is going to join the European Union, so additional to the efforts to ratify the domestic legislation with the Acquis Communautaire, the government is facing with another huge challenge. According to international reports “Mapping the Real Routes of Trade in Fake Goods”, the country has become a main path for the international transit regarding counterfeit goods. The vigilance of domestic intuitions is underperforming that are incapable to stop this phenomenon.

Analisa Optimasi Rute Transportasi Antar Jemput Siswa Menggunakan Model CGVRP dan Algoritma Dijkstra di SDIT Darus Sunnah

School transportation is one of the facilities provided by the school in the process of picking up students. In the process of picking up, taking the optimal route is needed to save costs and time. The purpose of this study is to develop a model School transportation routes using the Clustered Generalized Vehicle Routing Problem (CGVRP ) model and the Dijkstra algorithm to get a more optimal route from the route that has been used. Furthermore, comparing the real distance from the shuttle transportation routes with the distance from the results of this case study using the CGVRP model and the Dijkstra algorithm. From the research results obtained by using the CGVRP model and the Djikstra algorithm which is applied to the case study of shuttle students at Darus Sunnah SDIT We found that our result has shorter distance when compared to the distance of the usual route.. The total distance on the SDIT Darus Sunnah route is 2.746.416 meters and costs Rp. 2.214.288 in a month. While the distance from the proposed route obtained 2.333.616 meters for at Rp. 1.881.478 in a month. Therefore the difference in the distance from the real route and the proposed route is 357.288 meters with a difference in cost of Rp. 332.820, - in a month.

The consideration of road longitudinal slopes in automobile fuel consumption rationing

Nowadays the consideration of longitudinal slope when rationing automobile fuel consumption is hardly taken into account, and it is received just impliedly when paying attention to the area relief. Along with this, the influence of slopes of flat and slightly hilly terrain on fuel consumption is not taken into consideration at all. This article presents an easy calculation approach to the consideration of the quantitative effects of road slope angels (rise and descent) on the final fuel consumption of a vehicle on real routes. The notion of a reduced slope angle is inroduced,a substantial increase of fuel consumption on descents in comparison with rises is ascertained.