Urban intersection classification: a comparative analysis

Understanding the scene in front of a vehicle is crucial for self-driving vehicles and Advanced Driver Assistance Systems, and in urban scenarios, intersection areas are one of the most critical, concentrating between 20% to 25% of road fatalities. This research presents a thorough investigation on the detection and classification of urban intersections as seen from onboard front-facing cameras. Different methodologies aimed at classifying intersection geometries have been assessed to provide a comprehensive evaluation of state-of-the-art techniques based on Deep Neural Network (DNN) approaches, including single-frame approaches and temporal integration schemes. A detailed analysis of most popular datasets previously used for the application together with a comparison with ad hoc recorded sequences revealed that the performances strongly depend on the field of view of the camera rather than other characteristics or temporal-integrating techniques. Due to the scarcity of training data, a new dataset is created by performing data augmentation from real-world data through a Generative Adversarial Network (GAN) to increase generalizability as well as to test the influence of data quality. Despite being in the relatively early stages, mainly due to the lack of intersection datasets oriented to the problem, an extensive experimental activity has been performed to analyze the individual performance of each proposed systems.European Commissio

THE FLOW INSTABILITIES WITHIN AN URBAN INTERSECTION

The experiment uses wind-tunnel modelling method to investigate an intermittent ventilation of pollutants within an urban intersection. The model is designed after a typical inner-city area occurring frequently in European countries. It consists of apartment houses with roofs arranged to the several blocks. Blocks form regular patterns divided by intersections with height to width ratio equal to one. Project has focused on velocity characteristics inside the intersection and adjacent canyon. The skewness and kurtosis of velocity components were studied in order to identify an area with strong intermittent tendency. Velocity measurement was carried out using 2-component LDA. Pollutants have released from line source and mean concentration was obtained using slow flame ionization detector. Comparison of time-mean flow and concentration spatial distribution verified that vertical vortices, the typical flow patterns formed inside street canyons, as well as corner vortices created just behind the turning of the street are responsible for accumulation of emissions emitted by vehicle traffic. Flow instabilities corresponding to enhancement of skewness value break down these patterns and significantly ventilate street canyons removing exhalations. Longitudinal velocity indicates an unsteady acceleration near the rooftop level whereas deceleration occurred close to surface, so it produces a higher rotational speed in recirculation zone. In contrary, the strongest downward penetration of fresh air (into the canyon) is located behind the roof eaves on leeward building. With incoming downward gust, the recirculation zone is completely destroyed. Speed extremities (derived from kurtosis) also show the highest value at eaves level. Similar process appears in horizontal plane. Intensification of longitudinal wind runs up the circulation inside corner vortex, whereas lateral gust propagating just behind the turning of street diminishes the whole vortex and cleans up the area. Vertical and horizontal momentum flux was analyzed by quadrant analysis. This method has detected the localities with highest momentum transfer from free stream down to the canyon. This transfer corresponds with large air mixing. It also found out notable momentum transfer from rotational zone downward to the surface, where accumulation of pollutants occurred

A Two-Stage Allocation Scheme for Delay-Sensitive Services in Dense Vehicular Networks

Driven by the rapid development of wireless communication system, more and more vehicular services can be efficiently supported via vehicle-to-everything (V2X) communications. In order to allocate radio resource with the reasonable implementation complexity in dense urban intersection, a two-stage allocation algorithm is proposed in this paper, whose main objective is to minimize delay and ensure reliability. In particular, as for the first stage, the allocation policy is based on traffic density information (TDI), which is different from utilizing channel state information (CSI) and queue state information (QSI) in the second stage. Moreover, in order to reflect the influence of TDI on delay, a macroscopic vehicular mobility model is employed in this paper. Simulation results show that the proposed algorithm can acquire an asymptotically optimal performance with the acceptable complexity

Fine-Grained Reliability for V2V Communications around Suburban and Urban Intersections

Safe transportation is a key use-case of the 5G/LTE Rel.15+ communications, where an end-to-end reliability of 0.99999 is expected for a vehicle-to-vehicle (V2V) transmission distance of 100-200 m. Since communications reliability is related to road-safety, it is crucial to verify the fulfillment of the performance, especially for accident-prone areas such as intersections. We derive closed-form expressions for the V2V transmission reliability near suburban corners and urban intersections over finite interference regions. The analysis is based on plausible street configurations, traffic scenarios, and empirically-supported channel propagation. We show the means by which the performance metric can serve as a preliminary design tool to meet a target reliability. We then apply meta distribution concepts to provide a careful dissection of V2V communications reliability. Contrary to existing work on infinite roads, when we consider finite road segments for practical deployment, fine-grained reliability per realization exhibits bimodal behavior. Either performance for a certain vehicular traffic scenario is very reliable or extremely unreliable, but nowhere in relatively proximity to the average performance. In other words, standard SINR-based average performance metrics are analytically accurate but can be insufficient from a practical viewpoint. Investigating other safety-critical point process networks at the meta distribution-level may reveal similar discrepancies.Comment: 27 pages, 6 figures, submitted to IEEE Transactions on Wireless Communication

Vehicle-to-Vehicle Communications with Urban Intersection Path Loss Models

Vehicle-to-vehicle (V2V) communication can improve road safety and traffic efficiency, particularly around critical areas such as intersections. We analytically derive V2V success probability near an urban intersection, based on empirically supported line-of-sight (LOS), weak-line-of-sight (WLOS), and nonline-of-sight (NLOS) channel models. The analysis can serve as a preliminary design tool for performance assessment over different system parameters and target performance requirements

Analyzing the Effects of LED Traffic Signals on Urban Intersection Safety

In 2002, there were 1,299,000 crashes at signalized intersections in the United States. These crashes account for approximately 21 percent of total crashes and about 24 percent of all fatal and injury collisions. The social and financial impact of this number of collisions is substantial. The Federal Highway Administration (FHWA) and other agencies have recognized the detrimental effects of intersection crashes on our society and continue to fund research that will lead to a decrease in crash frequency. Numerous countermeasures have been tested for their potential to reduce crashes. Infrastructure improvements such as the construction of left-turn lanes, the removal of unwarranted signals and improvement of drainage through intersections have all proven to be effective at reducing crashes. Improving the visibility of traffic signals has also been cited as an important safety measure. Many intersection improvements are prohibitively expensive to implement—a drainage upgrade may cost in excess of $20,000, and new turn lanes may exceed$40,000. The financial impact of a countermeasure is always an important consideration to decision makers who are charged with the responsibility of allocating resources effectively. Low-cost safety countermeasures have become highly desirable as funding for transportation projects becomes more limited. Light emitting diodes (LEDs) have been used in various applications since their invention more than 40 years ago. As the new style of lighting gained popularity in other disciplines, engineers began to recognize the potential for LEDs in traffic applications. Traffic signal bulbs account for approximately 90 percent of the total energy usage at a typical intersection. By converting incandescent bulbs to LEDs, energy consumption can be decreased by about 80 percent. The California Department of Transportation (Caltrans) was one of the first agencies to realize large-scale cost saving by using LEDs. In 2003, Caltrans saved taxpayers $10 million per year by converting state-operated signals to LED. LED use became more widespread in the traffic industry as other government entities became aware of the potentially massive energy savings, eventually leading to the adoption of standard specifications and federal energy requirements for traffic signal modules. Conversion to LEDs has triggered other benefits besides the well-known energy reduction. They do not burn or distort lens covers, they may help preserve intersection wiring by drawing less power and they appear brighter than conventional signals. All of these advantages may also lead to an impact in another sector of traffic engineering—intersection safety. Visibility of LEDs seems to be superior, which could positively affect driver behavior. Reduced maintenance on the fixtures decreases the exposure of workers to traffic and the total number of work zones required at intersections. Also, the minimal energy usage allows for the use of battery backup systems to operate the intersection during a power outage. Could all of these factors combined improve overall intersection safety? The objective of this study was to use empirical Bayes estimation to determine whether there was a noticeable decrease in crashes at signalized intersections that have been converted to LED signals. In the field of traffic engineering, little research has been published about the safety benefits of increased signal visibility, though it has always been considered inherently beneficial. A study by Thomas et al. discusses the high reduction in crashes and high cost-benefit ratio for projects that replaced pedestal-mounted signals with more visible mast-arm-mounted ones. Improved traffic signal visibility was determined to be a cost-effective safety strategy. The Institute of Transportation Engineers cites improved signal visibility as a useful safety measure to be considered for implementation. LED signals are specifically described as being brighter and more conspicuous during inclement weather. Engineers have begun to utilize LEDs in railroad crossings as a potential safety improvement due to improved visibility and longer life. Flashing lights are installed horizontally at approaches to warn drivers of a train