Urban Transport Information Research Articles

Visualization Study Based on Cab Trajectory Data

With the acceleration of urbanization and the popularization of mobile technology, cabs have become an important part of urban transportation. Cab trajectory data, which is an important source of urban transportation information, contains rich information on driving paths, stopping time, number of passengers and so on. By mining and analyzing these trajectory data, it can reveal the spatial and temporal distribution law of urban traffic and provide powerful support for traffic management, urban planning, business analysis and other fields. Visualization, as an intuitive and effective way to convey information, plays a crucial role in the analysis and application of cab track data. The purpose of this paper is to use data preprocessing, machine learning, and data visualization techniques to study the cab trajectory data, to explore the value of this kind of data at a deeper level, and ultimately to provide strong support for urban transportation and business decision-making fields.

Publisher Erratum: Design of energy-saving driving strategy based on proximal policy optimization considering urban transport information

Publisher Erratum: Design of energy-saving driving strategy based on proximal policy optimization considering urban transport information

Design of energy-saving driving strategy based on proximal policy optimization considering urban transport information

Eco-driving has always been an ongoing topic. In urban driving conditions, traffic regulations, other vehicle behaviors, and special driving scenarios will have a major impact on the energy consumption of autonomous vehicles. As a representative algorithm of artificial intelligence, reinforcement learning has the ability to perform well under complex tasks. This paper uses deep reinforcement learning algorithms to design the economical driving strategies of autonomous vehicles in three driving scenarios: driving at signalized intersection under free traffic flow, car-following on ramps, and driving at signalized intersection considering queue effects. In the above three driving scenarios, the driving strategy proposed in this paper achieves economical driving performance while satisfying the driving scenario requirements.

A vehicle license plate data access model based on the jump hash consistency algorithm.

The massive amount of vehicle plate data generated by intelligent transportation systems is widely used in the field of urban transportation information system construction and has a high scientific research and application value. The adoption of big data platforms to properly preserve, process, and exploit these valuable data resources has become a hot research area in recent years. To address the problems of implementing complex multi-conditional comprehensive query functions and flexible data applications in the key-value database storage environment of a big data platform, this paper proposes a data access model based on the jump hash consistency algorithm. Algorithms such as data slice storage and multi-threaded sliding window parallel reading are used to realize evenly distributed storage and fast reading of massive time-series data on clustered data nodes. A comparative analysis of data distribution uniformity and retrieval efficiency shows that the model can effectively avoid generating the cluster hotspot problem, support comprehensive analysis queries with various complex conditions, and maintain high query efficiency by precisely positioning the data storage range and utilizing parallel scan reading.

Modeling Public Transport Network System by Using Statistics, Network Theory and Ant Colony Optimization

In some countries, bicycles are often used to access public transit stations, but the proportion of out-of-the-way travel is much smaller due to the limited availability of bicycles. Public bicycles are innovative rental or free bicycle schemes in urban areas that can be used for day-to-day mobility as one-way use is possible and can be considered as part of a public transport system. Different from traditional, mostly leisure bike rental services, they provide fast and easy access and have a variety of organizational layout, business models and useful technology for smart bikes (rented via smart cards or mobile phones). We find that bicycle-sharing systems that complement the traditional public transport system could potentially increase the competitiveness and attractiveness of sustainable modes of urban transport and thus help cities to promote sustainable daily mobility. Finally, we emphasize that the availability of open sources of urban transport information, such as public transport in our case, is crucial for analyzing urban mobility patterns. The aim of the research is to analyze and model PPP bicycle rentals using mathematical and computer methods. The article presents the application of the statistical and topological properties of bicycle rental and return network theory in city Novo mesto. The article uses swarm intelligence, a colony of ants to optimize the development of wheels across 14 stations. The wider city Novo mesto region with a population of almost 30 000 people, as a key industrial center, is heavily dependent on urban transport.

Modelling the potential effect of shared bicycles on public transport travel times in Greater Helsinki: An open data approach

Modelling the potential effect of shared bicycles on public transport travel times in Greater Helsinki: An open data approach

독립교차로의 통행시간 기반 신호제어 알고리즘

본 연구에서는 개별차량의 구간통행시간 정보를 이용한 독립교차로의 실시간 신호제어 알고리즘을 개발하였다. DSRC와 같이 개별차량의 ID와 검지시각 정보를 수집할 수 있는 검지체계를 적용하였으며, 개별차량의 통행시간 정보로 부터 도착교통류율, 지체, 적색시간 변화에 따른 지체 변화량을 산정하기 위한 모형을 정립하였다. 통행시간기반 신호제어 알고리즘은 교차로 지체를 최소화 시키기 위한 현시별 적색시간 변화량을 결정하며, 선형계획모형을 적용하여 신호시간의 최적화 과정을 수행한다. 알고리즘의 효과평가를 위해 CORSIM과 RUN TIME EXTENSION을 적용한 미시적 시뮬레이션 분석을 시행하였으며, 이동류의 포화상태를 확인하여 지체 최소화를 위한 신호시간이 산정됨을 확인하였다. 또한 Probe 차량의 비율에 따라 이동류의 지체추정 성능을 확인하였으며, 특정 시나리오에 한정된 결과이나 40% 이상 Probe 차량 비율이 확보되는 경우 효과적 신호제어가 가능함을 확인하였다. 최근 국내 교통관리분야에서는 하이패스, 첨단교통관리시스템(ATMS), 광역교통정보사업(UTIS) 등 개별차량의 구간정보를 수집할 수 있는 검지체계가 급격히 확산되고 있으며, 본 연구는 실시간 신호운영 분야에서 검지체계의 변화를 수용하기 위한 방안으로서 새로운 형태의 신호제어 방법론을 제시하였다는데 의의가 있겠다. This research suggested a real-time traffic signal control algorithm using individual vehicle travel times on an isolated signal intersection. To collect IDs and passing times from individual vehicles, space-based surveillance systems such as DSRC were adopted. This research developed models to estimate arrival flow rates, delays, and the change rate in delay, by using individual vehicle's travel time data. This real-time signal control algorithm could determine optimal traffic signal timings that minimize intersection delay, based on a linear programming. A micro simulation analysis using CORSIM and RUN TIME EXTENSION verified saturated intersection conditions, and determined the optimal traffic signal timings that minimize intersection delay. In addition, the performance of algorithm varying according to market penetration was examined. In spite of limited results from a specific scenario, this algorithm turned out to be effective as long as the probe rate exceeds 40 percent. Recently, space-based traffic surveillance systems are being installed by various projects, such as Hi-pass, Advanced Transportation Management System (ATMS) and Urban Transportation Information System (UTIS) in Korea. This research has an important significance in that the propose algorithm is a new methodology that accepts the space-based traffic surveillance system in real-time signal operations.

The Fusion Model of Intelligent Transportation Systems Based on the Urban Traffic Ontology

The Fusion Model of Intelligent Transportation Systems Based on the Urban Traffic Ontology