Exploiting Trip Patterns in Passenger Trajectory Streams for Bus Scheduling Optimization in Real Time

Aim. Threats of a non-physical nature have a significant effect on the security of intelligent transportation systems (ITS). They may have the form of unlawful interference in the development and implementation of ITS. The creation of a trusted framework for the development and implementation of ITS is examined as in the case of intelligent water transportation systems (IWTS). Problems. By decree of the President of the Russian Federation, ITS, telecommunications and security of information processing are among the priority areas of scientific and technological development. ITS technologies, as well as those involved in the creation of trusted, secure system and application software are among the most important critical high technologies. The operation of ITS involves wide use of computerised systems that implement the latest information and telecommunication technologies, automated and automatic control technologies, artificial intelligence that can pose security threats. ITS are to be developed and operated in a trusted environment. Methods. The paper used the methodology for ensuring the security of IWTS, development of secure hardware and software platforms for secure automated systems, methods of system analysis, dependability theory, information protection, and law. Results. The paper defines the problem of creating a trusted framework for the development and implementation of IWTS, the applicable terminology is developed. The author examined the effect of IWTS on the security of critical information infrastructure (CII) and national security, developed a model of relationships between the IWTS security domains taking into account threats of physical and non-physical origin. Examples of computer incidents within IWTS that caused consequences at the national and international levels are given. The composition of the IWTS facilities attributed to CII is defined, critical processes implemented by standard CII facilities as part of the IWTS are set forth. The author lists conceptual problems of IWTS security, defines the principles of creating a trusted framework for the development and implementation of IWTS. Conclusion. Ensuring the security of IWTS against modern threats requires solving a number of problems associated with the creation of a trusted framework for the development and implementation of IWTS. For the purpose of improving the timeliness and quality of their solution, the paper proposes an intuitive terminology that reflects the subject area and helps finding a common understanding of the security domain by experts from various industries. IWTS facilities have an effect on CII security and national security in general. That is taken into account in the model of relationships between IWTS security domains, demonstrated using cases of computer incidents within IWTS that caused consequences at the national and international level. Given the above, the paper lists IWTS facilities attributed to CII and sets forth examples of critical processes implemented by standard CII facilities as part of the IWTS. The defined list of conceptual IWTS security problems take into account the growing landscape of IWTS security threats that includes insecure software, hardware and software platforms, software and hardware systems and emerging technologies. When developing the principles for the creation of a trusted IWTS development and implementation framework, the author took into account the best practice of implementing the methodology for creating national secure hardware and software platforms of CII facilities that enables the creation of secure automated systems for various applications that are based on domestically-developed solutions. The examined matters are of a systemic nature, which allows using the findings in the development and implementation of ITS in other modes of transportation.

A customized bus (CB) system is a new emerging public transportation that provides flexible demand-oriented transit services for city commuters. Existing CB systems encounter two challenges of 1) collecting travel demands and discovering travel patterns effectively and efficiently and 2) planning profitable bus lines based on travel patterns. In this paper, we propose a bus line planning framework, called T2CBS, by taking full advantage of taxi trajectory data. In T2CBS, similar travel demands are discovered from passenger trajectories with a clustering algorithm, and CB stops are deployed at pick-up and drop-off points of trajectory clusters with integer linear programming. To plan profitable CB lines, we propose a profit estimation model, by considering the number of taxi passengers who can be attracted to CB buses. A routing algorithm (CBRouting) and a timetabling algorithm (CBTimetabling) are proposed to generate a CB line that can achieve the maximum profit for each trajectory cluster. We conduct experiments on one-month taxi trajectory data in Nanjing, China. Experimental results demonstrate that our T2CBS can generate CB lines with higher profit compared with baseline methods, and the moderate increase in travel time along the CB lines is significantly dominated by the savings in bus fare.

Over the past two decades many papers have been published on the impact of Information and Communication Technologies (ICT) on travel behavior, but the literature focusing on the impact of ICT on accessibility is relatively scarce. In this paper we give an overview of the impact of ICT on four components of accessibility as distinguished by Geurs and van Wee (2004): (1) the land-use component, (2) the transportation component, (3) the temporal component, and (4) the individual component. Conclusions are that first much more literature exists on the potential impacts of ICT on travel behavior than on its impact on accessibility. Second, we argue that ICT potentially has an impact on all four components of the concept of accessibility. Literature exists on the direct impacts but fails to incorporate impacts due to the interactions between the accessibility components. Third, there seems to be a major challenge in developing accessibility measures and indicators that include ICT, including those that measure the utility of accessibility. Fourth, in the area of ICT’s impact on travel behavior, many research gaps exist. Examples are the impact of ICT on overall activity and trip patterns, the impact of ICT on activities and trips at the household and social-network level, ICT as a means of avoiding congestion or mitigating its effects, and the role of the phenomenon of self-selection in the context of ICT use. Finally, a major challenge is to develop models for activities, including ICT-impacts, which combine high levels of behavioral realism with (econometric) tractability.

Prelims

High speed rail and buses are public transportation systems and possess the attribute of sustainable environment. A well-developed process for deciding bus lines, which are integrated with high speed rail, is essential for sustainable development. This study proposes an evaluation framework for shuttle bus lines with three evaluation dimensions and eleven evaluation indexes by adopting the Tainan high speed rail station as a case study. A questionnaire based on the analytic hierarchy process (AHP) is designed to interview with bus operators, scholars and public transportation authorities. By applying AHP, this study elicits interviewee opinions on evaluation indexes and analyzes the weight of each index. Results indicate that travel time, travel cost and bus schedule are significant evaluation indicators for shuttle bus lines. With respect to the priority of shuttle bus lines, lines 1, 3 and 4 rank as the leading three places based on the weighted sum of performance values.

Intelligent Transportation System (ITS) is the emerging transportation which comprises of the advanced technologies such as wireless communications, video vehicle detection, distributed system architectures, human machine interface, sensing and actuating, to improve safety of the passengers, traffic congestion, fuel consumption and optimize other services of the transportation system such as real time traffic situation, electronic toll collection, automatic road enforcement and hot lanes. The current ITS systems lacks self-adaptive capability to take spontaneous decisions. The environment of the ITS system is very complex so optimal decisions cannot be taken but a good enough decision can be taken which fulfills the requirement of the system. To build an ITS system having the capability to adapt itself, this paper presents the self-adaptive requirements for the ITS. To elicit the requirements for ITS, we use scenarios based model and goal based model using the requirements Engineering processes (Elicitation, Elaboration, Specification, Validation) with MAPE-K. We use Knowledge Acquisition on Automated Specification (KAOS) approach to build goal model using Objectiver tool, and use RELAX syntax to elicit adaptive requirements for ITS.

During the last decades, concepts of Intelligent Transportation Systems (ITS) were continuously adapted and improved based on new insights into human travel behavior. Drivers for improvements are the quantity and quality of available mobility data, which increased significantly in recent years. Based on travel behavior, literature proposes a large number of different solutions for next step or future location prediction. However a holistic spatio-temporal prediction, which could further improve the quality of ITS, creates a more complex task. The prediction of medium-term mobility for one to seven days is challenging in particular for atypical travel behavior, since the weekdays’ order delivers no reliable indication for the next day’s travel behavior. With our contribution, we explore the benefits of various prediction approaches for medium-term mobility prediction and combine them dynamically to predict individual mobility behavior for a period of one week. The derived framework utilizes an exhaustive search approach to benefit from a machine learning based clustering method on location data. In conjunction with an Artificial Neural Network, the prediction framework is robust against prediction errors created by atypical behavior. With two data sets consisting of smartphone and vehicle data, we demonstrate the framework’s real-world applicability. We show that clustering an individual’s historical movement data can improve the prediction accuracy of different prediction methods that will be explained in detail and illustrate the interrelation of entropy and prediction accuracy.

For several years, the United Kingdom (UK) transport policy has discouraged the construction of additional road space to meet the rising demand for road travel. Increasingly, Local Traffic Authorities (LTAs) in England are looking towards technology and Intelligent Transport Systems (ITS) for maximizing the efficiency with which they use their road networks. The aim of this paper is twofold. First, it provides a perspective on how English LTAs are using and planning to use ITS. Primarily, the recent UK Traffic Management Act influences these new strategies, which include the types of technology they are choosing. Findings are presented from some research carried out with a variety of English LTAs examining their use of and opinions concerning technology and ITS. Second, a case study is then provided on how one English LTA (Surrey County Council) is deploying ITS to help meet its new obligations. Conclusions are then drawn on the efficacy of setting central policy to influence LTAs in this manner.

Commuters and tourists in the Philippines heavily rely on buses as transportation links in cities and provinces, yet an issue that remains unsolved is the lack of real-time bus information readily available for bus passengers and operators. Victory Liner, Inc. is one of the country's largest provincial bus companies. However, their bus schedules are still drastically affected by unpredictable conditions, resulting to passengers cluelessly waiting for their buses' arrival. Hence, this paper explores the development of a real-time bus- tracking Android application called “BusTap” to address the gap in knowledge in the public bus transport service in Victory Liner Baguio using Global Positioning System (GPS) technology. With the use of Scrum methodology, the researchers were able to identify the necessary information requirements needed to create BusTap, determine the application's architectural framework, design and develop its features, as well as measure the app's extent of usability by floating Usefulness, Satisfaction, and Ease of use (USE) questionnaires to Baguio City bus passengers and Victory Liner Baguio drivers. It was concluded that: a) the identified information requirements were vital in developing the application's features, b)using a 4+1 architectural view model was helpful for project cohesion and organization, c) the features identified were crucial in eliminating the gap in knowledge between the bus operator and bus passengers, and d) based from the computed overall mean levelof agreement of 6.46 and 6.48 from the evaluation of passenger respondents and driver respondents respectively, BusTap users strongly agree that BusTap is a useful, easy to use, and easy to learn mobile application that satisfies its users' needs.

Studying on the coordinated development of conventional bus and subway dispatching, matching the departure interval and model configuration of connected bus based on subway passenger flow, can effectively reduce the waiting time for passenger. Firstly, an operational optimization model aiming at minimizing the passenger's transfer time and the total cost of bus operators is established, and the comprehensive threshold of dispatching coordination is determined. By analyzing the distribution characteristics of the passenger flow of connected bus line, the initial departure timetable of connected bus at the peak rush hour is made; Secondly, determining the initial model proposal with the full load rate as the constraint, and getting the initial dispatching coordination plan; Finally, analyzing the full load rate of the bus line. If the full load rate is too high or too low, adjusting the departure interval and model configuration to get the final bus and subway dispatching coordination plan.

Intelligent Transportation Systems (ITS) are increasingly shifting toward data-driven and artificial intelligence-based frameworks that integrate sensing, prediction, and control to enhance mobility efficiency, safety, and adaptability. This dissertation contributes to the development of next-generation ITS through three complementary studies focusing on flexible traffic monitoring, real-time traffic forecasting, and stability-aware vehicle control. The first study develops a multi-drone framework for wide-view corridor traffic analysis and origin-destination (OD) estimation. By coordinating multiple unmanned aerial vehicles, as demonstrated with two drones in this study, the framework enables continuous vehicle tracking across extended corridors. A deep learning-based pipeline combining vehicle detection and tracking automatically reconstructs vehicle trajectories and matches them across drone views. Field experiments conducted at a freeway weaving section achieved over 91% accuracy in OD flow estimation compared with ground-truth data, demonstrating the framework’s effectiveness for scalable and high-resolution traffic monitoring. The second study proposes a day-specific spatial-temporal graph convolutional network (Day-STGCN) for real-time traffic forecasting. Building upon the classical STGCN architecture, the model integrates rolling historical time-dependent features with day-type categorization to capture both short-term variations and long-term recurring patterns. Using real-world sensor data, the model significantly improves prediction accuracy over baseline graph neural networks, providing robust day-aware forecasting that reflects realistic daily traffic dynamics. The third study investigates cooperative adaptive cruise control (CACC) and its effects on traffic string stability under varying market penetration rates of connected and automated vehicles (CAVs). Analytical derivations establish explicit stability conditions linking controller parameters, time headway, and control intervals in both homogeneous and heterogeneous traffic flows. The results reveal that appropriately designed CACC controllers enhance string stability even in mixed environments with different types of vehicles. Collectively, these studies present an integrated framework that advances ITS through data-driven sensing, learning, and control, offering theoretical and practical foundations for more intelligent, responsive, and stable transportation systems.

A new method of vehicle identification in intelligent traffic command system is proposed, which is directed to some problems in the vehicle detection method of complex traffic conditions in intelligent traffic systems. The method extracts the vehicle structure sub-features according to the structural characteristics of the vehicle itself, and then combines the sub¬features. The identification of the vehicle is achieved by the identification of the combined features. Through experimental analysis, the method not only has a fast processing speed, but also has a high vehicle recognition accuracy. Therefore, this method has broad application prospects and value in intelligent traffic command system.

Since last decades world, predominantly urban areas, is experiencing huge voluminous road traffic growth, resulting in heavy congestion, air pollution, accidents, and poor efficiency. Many people every day are the victims of this poor management of tremendous traffic. Since many years, there had been some automation in managing the traffic namely Electronic Toll Collection (ETC), Electronic parking payment, normal traffic information etc. However, there are little efforts for making the system more advanced. Recently, several kinds of research are being launched by many countries to develop Intelligent Transport System (ITS), with the objectives to minimize congestion, ensure better safety, reduce air pollution etc. ITS are planned to establish robust communication between vehicle to vehicle (V2V), vehicle to pedestrian (V2P), vehicle to infrastructure (V2I), and vehicle to network (V2N). Initially, for communication links ITS, deploys Wi-Fi network, but because of limited capacity and huge requirement, some links use 5.8 GHz radio frequency for such purposes. IEEE, International Telecommunications Union (ITU) and other advanced research organisations are studying 700 MHz band and mm frequency bands for advanced ITS. ITS is poised to use Information & Communication Technology (ICT) networks for such purposes. ITU has established Study Groups/study questions for addressing ITS issues. The World Radio Conference (WRC-2019) has made a Recommendation 208 regarding harmonization of frequency bands for ITS applications. This paper presents a comprehensive overview of ITS, its applications and analysis etc. The radio frequency spectrum aspects and role of 5 G in ITS are also described in detail.

Most of the studies on travel patterns in behavioral geography have been done assuming single purpose trips. Recently, however, some attempts to explain human spatial behavior pay attention to multipurpose trips from the viewpoint of comprehensive explanation of actual behavior. These studies emphasize the importance of the temporal dimension. Paying attention to this trend, this paper examines the patterns of daily travel behavior, focusing upon multipurpose trips, through considering the relationship between cyclic trip patterns (i. e. home-to-home circuit) and the daily trip patterns of individuals, and the influence of accessibility and travel-activity time on multipurpose trips.The data used in this study are based on the personal trip survey conducted by the prefectural government in the city region of Hiroshima in 1978. The trip patterns are classified by the number of trips in each cycles, the sequence of activities, and the combination of cycles with that of trips per day, indicated by “B(a, b)”, where “a” refers to the number of cycles carried out per day and “b”refers to the number of trips carried out per day.The results obtained are as follows:(1) Multipurpose trips comprise 18.3 percent of all the cycles. The rate of multipurpose trips varies according to the characteristics of individuals due to the degree of obligation for activities they carry out.(2) The four main trip patterns, B(1, 2), B(1, 3), B(1, 4), B(2, 4), comprise more than nine-tenths of all the trips by individuals (Fig. 2). Relating the trip patterns by individuals to those of cycles, the more trips are contained in a cycle or the greater the degree of obligation for activities is, the fewer patterns occur with more than one cycle per day (Table. 7).(3) A positive correlation is detected between the rate of multipurpose trips and the accessibility from the destination of the first trip to other establishments. The relationship between the rate of multipurpose trips and the accessibility from the residence to other establishments, however, is more complicated. That is, as for the areas where the accessibilities are very high, the rate of mulpurpose trips decreases with the accessibility, although the rate has positive correlation with accessibility generally (Fig. 4).(4) Based on the combination of activities, a hypothesis for the generation of multipurpose trips is proposed and partly supported (Table. 8). The hypothesis is as follows;1) In cycles consisting of discretionary activities, travel time per stop in a multipurpose trip is shorter than that in single purpose trip, due to the principle of least effort.2) In cycles combining obligatory activities with discretionary ones, the longer the time of obligatory stay and movement, the fewer multipurpose trips occur, since obligatory activities have an effect on discretionary ones as constraints.3) The cycles consisting of business activities are highly influenced by the nature of occupation, so that the rate of multipurpose trips varies according to the occupation.As for unemployed housewives and employed housewives, however, the travel time of the first trip in each cycle and average travel time per stop are respectively related to multipurpose trips.

This article presents a study of the public transportation system in Montevideo, Uruguay, following a data science approach. More than 20 million records from the Intelligent Transportation System (ITS) are analyzed in order to characterize mobility in the city. Several useful pieces of information are obtained through data analysis, related to tickets sold, patterns of smart card utilization, most used bus lines and stops, and socioeconomic insights about passengers behavior. Practical case studies are also presented: anomaly detection in space and time, and a study of potential safety hazards due to reckless driving. The work reported in this article constitutes one of the first steps towards using data from the ITS in Montevideo to understand mobility in the city.