Intelligent Transportation Services Research Articles

Development of Intelligent Marine Traffic Service Application Software for Haikou Bay

Li, D.-L., 2019. Development of intelligent marine traffic service application software for Haikou Bay. In: Gong, D.; Zhu, H., and Liu, R. (eds.), Selected Topics in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 94, pp. 490–494. Coconut Creek (Florida), ISSN 0749-0208.Intelligent maritime traffic management platform can greatly improve the service efficiency and the shipping security of maritime transport industries. In fact, it is more significant for the development of maritime traffic industry. This paper devises an intelligent and integrated VTS information platform for marine transport service in Haikou Bay based on the traditional VTS system, builds a GIS-T-based VTS architecture, and proposes an intelligent VTS ship traffic prediction algorithm based on the grey system theory adaptive GM (1,1) model. The findings show that, in relation to the traditional VTS, the GIS-T-based VTS architecture has a better effect in spatial data management and analysis, and the algorithm based on GM (1,1) model renders a higher prediction precision, thereby effectively improving the marine transport intelligence level in Haikou Bay. This study has borne another one theoretical and practical fruit for the intelligent marine transport services and has a certain application value.

Route Recommendations for Intelligent Transportation Services

The accumulated large amount of mobility data and the ability to track moving people or objects have enabled us to develop advanced mobile recommendations, which are essential to recommend a sequence of locations to an individual user on the move. In this paper, we study a particular case of mobile recommendations, route recommendations to drivers, by utilizing vehicle GPS data. Specifically, we formulate a new Route Recommendation with Relaxed Assumptions (RR-RA) problem, the goal of which is to recommend a sequence of locations to a driver based on his current location in order to maximize his business success. To make our recommendation practical and scalable for real practice, we need to produce recommendation results in a timely fashion once a request emerges. Therefore, we propose an efficient algorithm to efficiently generate recommendations. Furthermore, we identify and address a destination-oriented route recommendation (DORR) problem. Without solving DORR problem, RR-RA alone does not work well in practice because drivers may encounter the destination constraint on a daily basis. We develop a dedicated and efficient algorithm for solving DORR problem. The package of solutions for both RR-RA and DORR problems provide a comprehensive approach for route recommendations to drivers. We evaluate our methods using both real-world GPS data and synthetic data, and demonstrate the effectiveness and efficiency of proposed methods with different evaluation metrics.

Diversified Routing Queries in Dynamic Road Networks

Route planning and recommendation are increasingly important in the recent two decades. In this light, we propose and study novel diversified routing (DR) queries that discover the most convenient routes in dynamic road networks, where travel time, congestion probability, and global travel cost are taken into account. Given a dynamic transportation network, a source, a destination, a travel time threshold $\tau _{t}$ , a congestion probability threshold $\tau _{p}$ , and a global travel cost threshold $\tau _{g}$ , the DR query finds: 1) the route with the minimum travel time whose global travel cost does not exceed $\tau _{g}$ ; 2) the route with the minimum congestion probability whose global travel cost does not exceed $\tau.g$ ; and 3) the route with the minimum global travel cost whose travel time does not exceed $\tau _{t}$ and congestion probability does not exceed $\tau _{p}$ . Such types of queries are very useful in many mobile applications, such as travel planning and recommendation, urban computing, intelligent transportation, and location-based services in general. The DR queries face two challenges: 1) how to model the dynamic road networks and to define the travel time, congestion probability, and global travel cost practically and 2) how to prune the search space effectively and to return the query results in the real time. To overcome the challenges and to process the DR queries efficiently, we develop a search framework based on network expansion. A series of optimization techniques is developed to further enhance the query efficiency. Finally, we conduct extensive experiments on large datasets to verify the performance of the developed algorithms.

Novel Interference Cancellation of Channel Estimation Scheme Based on LTE in V2V Communications

Transportation infrastructures integrate advanced Information Technology to enable the operations and management of transportation systems. Advanced vehicle and road systems of a comprehensive concept that improve the efficiency and safety of road traffic are being built and will be commercially available through Intelligent Transport Systems (ITS) technology and services. To support ITS technology, Vehicle-To-Everything (V2X) is needed, and in the 3rd Generation Partnership Project, many studies have focused on Long Term Evolution (LTE)-based vehicle communications. In order to realize reliable and optimized communications performance in vehicle communications, which move in propagation environments at high speed, in this study, we propose a novel channel estimation scheme suited for LTE sidelink-based Vehicle-To-Vehicle systems. Conventional channel estimation schemes can be categorized as Decision-Directed Channel Estimation, spectral temporal averaging, and smoothing methods. In this study, unlike conventional channel estimation schemes, we propose a Novel Interference Cancellation of Channel Estimation (NICCE) using Quadratic Smoothing of the pilot symbols, which estimates a channel with greater accuracy, and a novel interference cancellation of channel estimation in data symbols. In simulation results, the proposed NICCE scheme shows improved overall performance in terms of the Normalized Mean Square Error and uncoded Bit Error Rate relative to conventional schemes.

Double Auction-Based Pricing Mechanism for Autonomous Vehicle Public Transportation System

The autonomous vehicle (AV) is expected to be an important “building block” of the future smart city. Recently, an AV-based public transportation system has been successfully developed to provide precise, effective, and intelligent public transportation services. For better quality of service, the system encourages market competition by accommodating multiple AV operators. To facilitate the pricing process, a pricing mechanism was developed but it can only process one service request each time. This can significantly impair the overall passenger admissibility, especially when there are many outstanding requests to be processed. In this paper, we redesign the pricing mechanism for handling multiple requests simultaneously. To do this, we formulate the key component of the mechanism, i.e., request-AV allocation, as a double combinatorial auction-based process. We construct a new winner determination problem that can accommodate requests of different AV service types. We also investigate its duality to devise an efficient service charge determination rule. We evaluate the performance of the proposed mechanism and charging rule with extensive simulations. The results show that the mechanism can result in better social welfare than the original scheme. Moreover, we examine the computational time required and the percentage of successfully served passengers. The simulations demonstrate that the mechanism can make the AV public transportation system more practical.

A three-stage online map-matching algorithm by fully using vehicle heading direction

Map-matching is essential for almost all intelligent transportation systems, including context and personalized services. To support real-time intelligent transportation services, online map-matching is usually a prerequisite. Although many map-matching methods have been proposed, they often fail to balance the two conflicting objectives, i.e., matching quality and computation time. To alleviate the contradiction, in this paper, we propose a three-stage online map-matching algorithm, named as SD-Matching, to fully exploit a new dimension of collected GPS trajectory data (i.e., vehicle heading direction) in a provably smart way. In the first stage, heading direction is first used to enhance the probability computation of candidate edges for a given GPS point. In the second stage, heading direction is also employed to narrow down the searching space and serve as a cost-effective guider in the shortest path computation for two consecutive GPS points. In the third stage, heading direction is further utilized to refine the vehicle travelling path for a sequence of GPS points, together with the topology of the road network. Finally, we evaluate the SD-Matching algorithm using the real-world taxi data and road network data in the city of Beijing, China, to demonstrate its effectiveness and efficiency.

Services and Security Threats in SDN Based VANETs: A Survey

As the number of vehicles is increasing, the number of road side accidents is also increasing rapidly. The majority of these accidents is caused by the negligence of the driver. For intelligent transportation services, new protocols and architecture are continuously being developed by researchers around the globe. Thus to ensure the safety of drivers many countries are now adopting and investing a lot on vehicular ad hoc network (VANET). On the other perspective, there are many issues related to this field that must be resolved before VANET technology is practically adopted. In the case of no or low‐security, several attacks can occur that may affect the efficiency and the reliability of the system. To make VANET systems more efficient software defined networking (SDN) technology is introduced in it. This technique was shortly named as SDN‐based VANET. SDN‐based VANET system helps us to get rid of the restriction and the challenges that are present in the simple VANET systems. It helps us to decrease the overall load on the network by managing the overall network through a single remote controller. In this survey paper, we will elaborate the concept of SDN‐based VANET, its working, applications, services, security threats, and benefits over the previous techniques.

Analysis and Evaluation of the Influence of Selected its Services on Road Traffic Safety and Efficiency

Abstract The implementation of Intelligent Transport Systems (ITS) nowadays is associated with a strong need to solve problems related to the high accident rate, as well as low efficiency of transportation process management. The topic of this paper is the characterisation of selected intelligent transport services and the determination of their influence on road traffic safety and efficiency. Two services implemented within the framework of the National Traffic Management System in Poland were distinguished, namely: transmitting information to drivers and incident detection. A general analysis of the relationship between the functioning of ITS services and safety on national roads, as well as traffic efficiency therein was conducted.

Connected Vehicular Transportation: Data Analytics and Traffic-Dependent Networking

With onboard operating systems becoming increasingly common in vehicles, the real-time broadband infotainment and Intelligent Transportation System (ITS) service applications in fast-motion vehicles become ever demanding, which are highly expected to significantly improve the efficiency and safety of our daily on-road lives. The emerging ITS and vehicular applications, e.g., trip planning, however, require substantial efforts on the real-time pervasive information collection and big data processing so as to provide quick decision making and feedbacks to the fast moving vehicles, which thus impose the significant challenges on the development of an efficient vehicular communication platform. In this article, we present TrasoNET, an integrated network framework to provide realtime intelligent transportation services to connected vehicles by exploring the data analytics and networking techniques. TrasoNET is built upon two key components. The first one guides vehicles to the appropriate access networks by exploring the information of realtime traffic status, specific user preferences, service applications and network conditions. The second component mainly involves a distributed automatic access engine, which enables individual vehicles to make distributed access decisions based on access recommender, local observation and historic information. We showcase the application of TrasoNET in a case study on real-time traffic sensing based on real traces of taxis.

Research of Intelligent Public Transportation Service Design in China

In order to build a user-friendly and urban intelligent public transportation service system, this paper, treating the analysis of public transportation system of Beijing as a breakthrough point, provides a perfect service design of public transportation and the optimization of travel route basing on the user's habits, scheduling and health conditions. All the travel data of traffic system and users’ data such as health indicators are obtained from cloud platform. The development and application prospect of intelligent public transportation embodies the user-centered design concept. This paper preliminary develops a user-friendly and efficient design system of urban public transportation services with the trait of intelligence.

Increased Traffic Flow Through Node-Based Bottleneck Prediction and V2X Communication

Transport delays due to traffic jams are manifested in many urban areas worldwide. To make road traffic networks more efficient, intelligent transport services are currently being developed and deployed. In order to mitigate (or even avoid) congestion, vehicle-to-vehicle and vehicle-to-infrastructure communications provide a means for cooperation and intelligent route management in transport networks. This paper introduces the novel predictive congestion minimization in combination with an A * -based router (PCMA * ) algorithm, which provides a comprehensive framework for detection, prediction, and avoidance of traffic congestion. It assumes utilization of vehicle-to-X communication for transmission of contemporary vehicle data such as route source and destination or current position, as well as for provision of the routing advice for vehicles. PCMA * further contains a component for intelligent selection of vehicles to be rerouted in case of a congestion, as well as an A * -based routing algorithm, taking into consideration the current road conditions and predicted future congestion. We prove the performance by dynamic microscopic traffic simulations in a real-world and an artificial road network scenario. Due to the well-performing prediction, the results reveal substantial advantages in terms of time and fuel consumption compared not only with situations with no active rerouting system but also with simple rerouting algorithms and more sophisticated approaches from literature.

A review of data management and protocols for vehicular networks

In recent years, with the development of vehicular technology, vehicular communication has increasingly become a crucial and rising area. Creating an accident-free environment is the foremost goal of taking a real interest in this new research field. Some progress has been made in this area, new architectures, protocols and implementations of Vehicular Ad Hoc Network (VANET) have been made to supply Intelligent Transportation Services (ITS). The vehicle-to-vehicle communications play a vital role in vehicular networks, so we present a comprehensive overview of data management in this paper in order to explore the present research status with its main problems in vehicular communication. We describe the protocol of vehicular networks and the various types of data managed in that environment, also we analyse the challenges we face right now.

Improving Routing Performances to Provide Internet Connectivity in VANETs over IEEE 802.11p

In the intelligent transportation systems, many applications and services could be offered in the road via Internet. Providing these applications over vehicular ad hoc network (VANETs) technology may require good performances in routing. The channel fading and quality of received signal are the two main factors which affect the Mobile ad hoc network perfor-mances as well as mobility of vehicles, in terms of throughput and delay packets that are relevant to the performance evaluation of the routing protocols. In this paper, we propose an efficient relay selection scheme based on Contention Based Forwarding (CBF) and Fuzzy Logic System (FLS) that considers two important Quality of Service parameters such as link stability, and quality of received signal to select a potential relay vehicle, in order to improve the routing performances in the network. The simulation results show that the proposed relay selection scheme enhances throughput, and decreases packet delay and overhead comparing it with an existing link stability based routing protocol(MBRP) and M-AODV+.

Intelligent Transport Systems in the Management of Road Transportation

Abstract Extension of European Union causes increase of free transfer of people and goods. At the same time they raised the problems associated with the transport, e.g. congestion and related accidents on roads, air traffic delays and more. To increase the efficiency and safety of transport, the European Commission supports the introduction of intelligent transport systems and services in all transport sectors. Implementation of intelligent transport systems and services in the road transport reduces accident frequency, increases the capacity of existing infrastructure and reduces congestions. Use of toll systems provides resources needed for the construction and operation of a new road network, improves public transport, cycling transport and walking transport, and also their multimodal integration with individual car transport.

Simulation Based Analysis of Bee Swarm Inspired Hybrid Routing Protocol Parameters Using Realistic Mobility Model In Vehicular Ad-Hoc Networks

Vehicular Ad-hoc Networks (VANET's) are basically emanated from Mobile Ad hoc networks (MANET's) in which vehicles act as the mobile nodes, the nodes are vehicles on the road and mobility of these vehicles are very high. The main objective of VANET is to enhance the safety and amenity of road users. It provides intelligent transportation services in vehicles with the automobile equipment to communicate and co-ordinates with other vehicles in the same network that informs the driver’s about the road status, unseen obstacles, internet access and other necessary travel service information’s. The evaluation of vehicular ad hoc networks applications in based on the simulations. A Realistic Mobility model is a basic component for VANET simulation that ensures that conclusion drawn from simulation experiments will carry through to real deployments. This paper attempts to evaluate the performance of a Bee swarm inspired Hybrid routing protocol for vehicular ad hoc network, that protocol should be tested under a realistic condition including, representative data traffic models, and the realistic movement of the mobile nodes which are the vehicles. In VANET the simulation of Realistic mobility model has been generated using SUMO and MOVE software and network simulation has been performed using NS2 simulator, we conducted performance evaluation based on certain metric parameters such as packet delivery ratio, end-to-end delay and normalized overhead ratio.

Availability of TV White Spaces Using Spectrum Occupancy Information and Coverage Maps

Radio Spectrum is the natural resource that allows the operation of radio services, such as Television, Mobile Telephony, and applications for Intelligent Transportation Services, Internet of Things, among others. The current allocation system is inefficient because assigned spectrum is not fully utilized by operators and cannot be accessed by any other user, despite its availability. Secondary spectrum usage is proposed as an alternative to optimize its use, allowing that a secondary user can access certain portion of spectrum allocated to primary service. In particular of TV service, this portion is known as TV White Space, TVWS. The most common models to identify available spectrum in TV service are based on frequency allocation and network planning information provided by TV operators, which are not enough to make an accurate estimation. A spectrum detection model built with traditional models and analysis of coverage maps obtained by simulations is presented, and applied in Cali ‑ Colombia to establish how many TVWS are available, taking into account the effect that terrain has on the propagation of the service. The amount of TVWS detected increases using our model compared to TVWS identified only with traditional models.

A Kind of Novel ITS Based on Space-Air-Ground Big-Data

Abstract-Based on the big-data collected from Space-Air-Ground, i.e. Space means satellite, Air means helicopter, the key technologies of novel ITS (Intelligent Transportation System) are investigated, including data acquisition sensor, dynamic data transmission, massive data storage, multi-source data fusion, massive data mining and analysis, etc. On this basis, the cloud computing platform of novel ITS is designed, including Space-Air-Ground bigdata acquisition & transmission subsystem, cloud computing platform, intelligent transportation application & service subsystem. With the help of the data visualization, data prediction, and decision making, the complete traffic big-data set including people (passenger, driver), vehicle, and road traffic environment, can create their core addedvalues. The applications of novel ITS include: providing transportation data services for traffic enterprise and business users, such as customized mining, and specific industry analysis; providing accurate transportation information services for the citizen; providing business model for all levels of users, such as data visualization and customized services.

A Survey on TCP in VANET: Architecture, Issues

Vehicular communication is an important and emerging area of research in the field of vehicular technology. The improvement of programming and equipment in correspondence frameworks prompts the era of new systems. Many researches and projects have been conducted in this upcoming area. Many government projects have been implemented in the USA, Japan and the European Union. The principle goal of utilizing this new technology is to make an accident free environment. New architectures, protocols and implementations of vehicular ad-hoc network (VANET) have been made in recent years to provide Intelligent Transportation Services. This paper incorporates survey of overall examination chip away at different issue identified with TCP in VANET. The main issue is Congestion when congestion occur number of packets are drops, some packets are also lost. To overcome this problem congestion control algorithm is used when congestion occur this algorithm slow down the transmission rate. Additionally VANET has number of difficulties like technical, social and economical. To solve this issue numerous procedures to be utilized because of this it enhances bandwidth utilization and throughput.

Shortest path and vehicle trajectory aided map-matching for low frequency GPS data

Map-matching algorithms that utilise road segment connectivity along with other data (i.e. position, speed and heading) in the process of map-matching are normally suitable for high frequency (1Hz or higher) positioning data from GPS. While applying such map-matching algorithms to low frequency data (such as data from a fleet of private cars, buses or light duty vehicles or smartphones), the performance of these algorithms reduces to in the region of 70% in terms of correct link identification, especially in urban and sub-urban road networks. This level of performance may be insufficient for some real-time Intelligent Transport System (ITS) applications and services such as estimating link travel time and speed from low frequency GPS data. Therefore, this paper develops a new weight-based shortest path and vehicle trajectory aided map-matching (stMM) algorithm that enhances the map-matching of low frequency positioning data on a road map. The well-known A∗ search algorithm is employed to derive the shortest path between two points while taking into account both link connectivity and turn restrictions at junctions. In the developed stMM algorithm, two additional weights related to the shortest path and vehicle trajectory are considered: one shortest path-based weight is related to the distance along the shortest path and the distance along the vehicle trajectory, while the other is associated with the heading difference of the vehicle trajectory.The developed stMM algorithm is tested using a series of real-world datasets of varying frequencies (i.e. 1s, 5s, 30s, 60s sampling intervals). A high-accuracy integrated navigation system (a high-grade inertial navigation system and a carrier-phase GPS receiver) is used to measure the accuracy of the developed algorithm. The results suggest that the algorithm identifies 98.9% of the links correctly for every 30s GPS data. Omitting the information from the shortest path and vehicle trajectory, the accuracy of the algorithm reduces to about 73% in terms of correct link identification. The algorithm can process on average 50 positioning fixes per second making it suitable for real-time ITS applications and services.

An examination on RFID innovation diffusions in Chinese public intelligent transportation services

Radio frequency identification (RFID) has been widely used in not only industries but also public services. As a typical application of RFID, the electronic toll collection (ETC) has great contributes to public transportation services, especially in the developing countries. This study developed a research model based on innovation diffusion theory to identify critical factors impacting the RFID adoption intention in public services. Specifically, it investigated the correlations of perceived characteristics of innovation (PCI), communication channels and government polices with adoption intentions. In total, 180 valid survey datasets of ETC users in China were obtained. The partial least squares structural equation modelling (SEM) was used to analyse the model. The results indicated that the PCI were significant in impacting RFID adoptions. Communication channels had a strong influence on people's perceived relative advantages. A moderate effect of government policies was also found. The theoretical and practical implications were presented later.