Cluster Analysis of Stations Based on Weight SimRank in Sharing Bicycle

With the increasing popularity of shared bikes, the indiscriminate parking of bicycles in cities has increasingly become a difficulty in urban management. The tidal phenomenon of large numbers of urban residents during rush hour is the root cause of the indiscriminate parking of bicycles in many subway stations and commercial areas. Optimizing the scheduling strategy of shared bikes is one of the effective solutions to solve the problem of random parking and reduce the scheduling cost. The cycle is a short - distance vehicle, and its circulation law is in line with the characteristics of the small world of urban traffic. That is, most of the bikes flow within the small world region, while only a small part of the bikes flow between the small world regions. With the massive accumulation of bike-sharing borrow and return data, the method of clustering the borrow and return stations and dividing regions according to the clustering results has attracted the attention of industry experts and researchers. it is effectively to apply in intelligent scheduling related industries. Although there have been some studies on the station clustering in the current literature, because these studies are basically based on the fixed features of the site (site location, pile number, etc.), the results cannot find an effective small world region of bicycles. In order to find out the effective small world region of bicycles, we introduced the idea of SimRank (that is, the similarity of a station is due to the similarity of its bicycle source station and destination station), and assigned weights to association relationships (the number of times of borrowing and returning) to define the similarity algorithm w-SimRank of stations. Then, the station clustering was done in line with skyline thinking. Finally, in order to verify the effectiveness of the algorithm, we implemented the station clustering based on SimRank algorithm, and compared the clustering effect with the W-SimRank algorithm proposed in this paper to verify the effectiveness of the W-SimRank algorithm, and analyzed the influence of the key parameters of the algorithm on the algorithm. And then

Real-Time Return Demand Prediction Based on Multisource Data of One-Way Carsharing Systems

One-way carsharing system has been widely adopted in the carsharing field due to its flexible services. However, as one of the main limitations of the one-way carsharing system, the imbalance between supply and demand needs to be solved. Predicting pick-up demand has been studied to achieve the goal, but using returned vehicles to reduce unnecessary relocation is also one of the important methods. Nowadays, trajectory data and other data are available for real-time prediction for return demand. Based on the return demand prediction, the relocation response can be more reasonable. Thus, the balance of demand and supply can be largely improved. The multisource data include trajectory data, user application log data, order data, station data, and user characteristic data. Based on these data, a return demand prediction model was used to predict whether the user will return the vehicle in 15 min in real time, and a destination station prediction model was applied to forecast which station the user will park at. Finally, a case study using ten stations’ one-week field data was conducted to test the benefit of the dynamic return demand prediction. The results showed that the return demand prediction improves the efficiency of the relocations by mitigating the condition that the station parking space is full or empty. The potential application of this study would effectively reduce unnecessary relocation and further formulate an active operation optimization strategy to reduce the system’s operational cost and improve the service quality of the system.

AUTOMATIC TRAIN DOOR PORTAL SYSTEM USING REGULATED STRAIGHT MOTION FORMULAS

The train station is an important facility. However, the services provided to train passengers are still not optimal. There are still several weaknesses, including the arrival and departure processes of trains that still rely on telephone communication with other station staff. Notification of train arrival will be sent by telephone by the officer at the previous station to the destination station. On receiving notification of arrival, station staff will close the train portal. This process can have a weakness, and namely, if there is the officers' negligence, it can cause an accident. This is due to the absence of an automatic operating system on the railroad crossing portals. Because the manual system must use human labour or operators to operate and open the railroad crossing portals, so that operator error or failure of manual operation of the portal can increase the likelihood of a train accident occurring at the crossing portal, the above problems can be overcome by implementing an automatic portal closure system. With an automatic portal system, the portal will automatically close if a train passes through the crossing.

Toward Campus Mail Delivery Using BDI

Autonomous systems developed with the Belief-Desire-Intention (BDI) architecture tend to be mostly implemented in simulated environments. In this project we sought to build a BDI agent for use in the real world for campus mail delivery in the tunnel system at Carleton University. Ideally, the robot should receive a delivery order via a mobile application, pick up the mail at a station, navigate the tunnels to the destination station, and notify the recipient. In this paper, we discuss how we linked the Robot Operating System (ROS) with a BDI reasoning system to achieve a subset of the required use casesand demonstrated the system performance in an analogue environment. ROS handles the connections to the low-level sensors and actuators, while the BDI reasoning system handles the high-level reasoning and decision making. Sensory data is sent to the reasoning system as perceptions using ROS. These perceptions are then deliberated upon, and an action string is sent back to ROS for interpretation and driving of the necessary actuator for the action to be performed. In this paper we present our current implementation, which closes the loop on the hardware-software integration and implements a subset of the use cases required for the full system. We demonstrated the performance of the system in an analogue environment.

Dockless bike-sharing system: Solving the problem of faulty bikes with simultaneous rebalancing operation

The Free-Floating Bike-Sharing System (FFBS) enables commuters to pick up and drop off a shared bike without going to a docking station before and after the trip. However, the specific sharing features of the FFBS can also be a problem for users because randomly scattered and faulty bikes within the system can result in bike unavailability and maintenance difficulties. This not only negatively impacts the company’s service quality but also causes user safety issues. In this study, a mechanism for the rebalancing of useable bikes and faulty bikes is presented in two steps: 1) gathering each faulty bike at a station determined by the model traversing the shortest path by light service vehicles; and 2) enabling the rebalancing operation to obtain optimal bike inventory levels at all stations and collect faulty bikes at a depot. The destination station from which each faulty bike is taken is considered a decision variable rather than shifting them to a closer station. The mechanism is based on minimizing the total cost of the rebalancing operation by optimizing the formulated problem, supported by time and capacity constraints. Using CPLEX solver, the validity of the model is tested through different numerical experiments.

A Method for Extracting Travel Patterns Using Data Polishing

With the development of ICT (Information and Communication Technology), interest in using the large amount of accumulated data for traffic policy planning has been increasing. In recent years, data polishing has been proposed as a new methodology for big data analysis. Data polishing is one of the graphical clustering methods. This method can be used to extract patterns that are similar or related to each other by clarifying the cluster structures in the data. The purpose of this study is to reveal travel patterns of railway passengers by applying data polishing to smart card data collected in Kagawa Prefecture, Japan. This study uses 9,008,709 data points collected during the 15 months from December 1st, 2013 to February 28th, 2015. This data set includes such information as trip histories and types of passengers. The study uses the data polishing method to cluster 4,667,520 combinations of information about individual rides: day of the week, time of day, passenger type, origin station, and destination station. As a result, 127 characteristic travel patterns were specified from those combinations.

Quick Response Based Automatic Ticket Generation, Payment and Monitoring for Suburban Trains

Manual booking and monitoring of tickets in suburban trains is a hectic and time consuming process for the passengers and officials. Due to improper monitoring the government suffers a revenue loss every year. Hence we propose the development of an application that generates a QR code once the passenger logs in and is read to travel. The QR code has to be scanned at the boarding and destination station checkpoints for entry and exit access. The user’s ticket details are stored in a database for security purpose. After the scanning process at the destination, the travel fare computed based on the boarding and destination stations shall be automatically deducted from the dedicated wallet. Thereby, streamlining the system through our application makes the process effortless, efficient and compatible. The ticket checker is also provided with a checker application with which the user’s ticket information in the database can be verified. Thereby, streamlining the system through our application makes the process effortless, efficient and compatible.

A LOW COST PERSONAL DESTINATION PREDICTOR BY INTERFACING THE GPS AND GSM

This paper proposes and implements a solution for the navigation difficulty and enhancing the rail transportation in a simple way by combining Wireless Communication and GPS Technology by developing a GPS Based Real Time Personal Destination Predictor. In this method by sending SMS (Short Message Service) and Voice Call to the registered passenger’s mobile phone, we alert the passenger about his destination at the specified time before reaching the destination. If the user sends the PNR (Passenger’s Name Record) number obviously the server responds with a SMS to the mobile phone of the particular ticket received user. Once the request is responded, the GPS (Global Positioning System) which is the train will locate the live position of the train as latitude and longitude value which will be transferred by the wireless communication to the server and the server will response the location from the Google Maps and intimate the passenger before the specified time of the arrival of the destination station of the passenger, which can be known from the PNR details of the passenger, through SMS and Voice Call. Even the person waiting for the passenger in the destination can avail this facility from his mobile phone by registering with the passenger’s PNR number.

Virtual Sorting: Improving Organization of Moving and Processing of Empty Car Flows

The growth in railway cargo carriage, followed by the search for its more efficient implementation results in the need to improve the regulatory framework for interaction of all participants in the transportation process on railways and the technology of organization of moving and processing of car flows on public tracks, reducing existing costs. This explains topicality of reducing shunting operations through flexible arrangement of wagons by destination stations. The objective of the study is to develop the technology of «virtual sorting of empty cars». The work has used methods of system analysis and the specific tools of railway traffic management and control. The technology is based on replacing physical rearrangement of empty cars when performing shunting work by introducing changes into the documents, that accompany the car, regarding the destination station and the recipient. It allows to reduce the planning horizon of turnover of empty cars by clarifying their destination assignments within the delivery process and, as a consequence, to obtain a significant economic effect by reducing the costs of processing transit car flows, by reducing the risks of not providing empty cars for loading, by attracting additional loading volumes, by accelerating the turnover of cars and other effects. Ultimately, the implementation of the suggested technology can increase the competitiveness of railway transport.

Prototype of Railway Passenger Warning System Based on Arduino Uno Atmega 328 Microcontroller

Service and convenience are important factors in carrying out modes of transportation, especially railways. As the development of railways in Indonesia is needed in terms of service and comfort. It often happens that passengers who miss the destination station are still problems that must be resolved in the service and comfort of the train facilities. Early warning systems that are still universal using speakers still lack maximum service. From the results of a survey conducted there are still many potential passengers who are worried about being missed by the destination station. In this research, a prototype of an early warning system with a vibrator mounted on the train seat was made when a passenger arrived at the destination station. This tool is able to provide early warning individually, so that people who will arrive at the destination station are not missed. This prototype works using the Arduino Uno Atmega328 microcontroller as its control system. Vibration machine with 53 Hz of vibration. After testing 43 respondents, the average person woke up after being given a vibration of 53 Hz is 4 seconds. Keypad as data input for destination destination code. The light if the passenger is not awakened turns on for 5 minutes. The results of this study are able to help the early warning system work through speakers more leverage