相关论文: Instant Accident Reporting and Crowdsensed Road Co…
Efficient and accurate incident prediction in spatio-temporal systems is critical to minimize service downtime and optimize performance. This work aims to utilize historic data to predict and diagnose incidents using spatio-temporal…
The ability to perceive and comprehend a traffic situation and to estimate the state of the vehicles and road-users in the surrounding of the ego-vehicle is known as situational awareness. Situational awareness for a heavy-duty autonomous…
Nowadays, in developing countries including Iran, the number of vehicles is increasing due to growing population. This has recently led to waste time getting stuck in traffic, take more time for daily commute, and increase accidents. So it…
In this paper, a collision avoidance system is presented to detect red light running and warn nearby vehicles and pedestrians in real time in order to prevent possible accidents. No complex infrastructure-based solution such as those based…
This report explores the use of machine learning techniques to accurately predict travel times in city streets and highways using floating car data (location information of user vehicles on a road network). The aim of this report is…
With the recent advancement in environmental sensing, vehicle control and vehicle-infrastructure cooperation technologies, more and more autonomous driving companies start to put their intelligent cars into road test. But in the near…
The future of transportation is being shaped by technology, and one revolutionary step in improving road safety is the incorporation of robotic systems into driver monitoring infrastructure. This literature review explores the current…
Smart Cities and Communities (SCC) constitute a new paradigm in urban development. SCC ideates on a data-centered society aiming at improving efficiency by automating and optimizing activities and utilities. Information and communication…
Prior art in traffic incident detection relies on high sensor coverage and is primarily based on decision-tree and random forest models that have limited representation capacity and, as a result, cannot detect incidents with high accuracy.…
Autonomous and connected vehicles are rapidly evolving, integrating numerous technologies and software. This progress, however, has made them appealing targets for cybersecurity attacks. As the risk of cyber threats escalates with this…
Graph neural networks (GNNs) are widely used in urban spatiotemporal forecasting, such as predicting infrastructure problems. In this setting, government officials wish to know in which neighborhoods incidents like potholes or rodent issues…
In the past several years, road anomaly segmentation is actively explored in the academia and drawing growing attention in the industry. The rationale behind is straightforward: if the autonomous car can brake before hitting an anomalous…
An integrated GPS-GSM system is proposed to track vehicles using Google Earth application. The remote module has a GPS mounted on the moving vehicle to identify its current position, and to be transferred by GSM with other parameters…
Autonomous driving needs various line-of-sight sensors to perceive surroundings that could be impaired under diverse environment uncertainties such as visual occlusion and extreme weather. To improve driving safety, we explore to wirelessly…
We study methods to estimate drivers' posture in vehicles using acceleration data of wearable sensor and conduct field tests. To prevent fatal accidents, demands for safety management of bus and taxi are high. However, acceleration of…
This work gives introduction to traffic control by connected automated vehicles. The influence of vehicle control on vehicular traffic and traffic control strategies are discussed and compared. It is highlighted that vehicle-to-everything…
In traffic management, it is a very important issue to shorten the response time by detecting the incidents (accident, vehicle breakdown, an object falling on the road, etc.) and informing the corresponding personnel. In this study, an…
Recent trend of railway train development can be characterized in several aspects : high speed, infortainment, intelligence in driving, and so on. In particular, trend of high speed in driving is prominent and competition for high speed…
For intelligent vehicles, sensing the 3D environment is the first but crucial step. In this paper, we build a real-time advanced driver assistance system based on a low-power mobile platform. The system is a real-time multi-scheme…
This paper presents a localization algorithm for autonomous urban vehicles under rain weather conditions. In adverse weather, human drivers anticipate the location of the ego-vehicle based on the control inputs they provide and surrounding…