Traffic Signal Optimization for Multiple Intersections Based on Reinforcement Learning

In order to deal with dynamic traffic flow, adaptive traffic signal controls using reinforcement learning are being studied. However, most of the related studies are difficult to apply to the real field considering only mathematical optimization. In this study, we propose a reinforcement learning-based signal optimization model with constraints. The proposed model maintains the sequence of typical signal phases and considers the minimum green time. The model was trained using Simulation of Urban MObility (SUMO), a microscopic traffic simulator. The model was evaluated in the virtual environment similar to a real road with multiple intersections connected. The performance of the proposed model was analyzed by comparing the delay and number of stops with a reinforcement learning model that did not consider constraints and a fixed-time model. In a peak hour, the proposed model reduced the delay from 3 min 15 s to 2 min 15 s and the number of stops from 11 to 4.7 compared to the fixed-time model.

Pedestrian Compliance at Signalized Intersections along Major Arterials

Background: Pedestrian non-compliance at signalized crossings is unsafe and considered one of the causes of pedestrian crashes. The speed limit on most major urban roads is 60 km/hr or less. However, the speed on some urban roads is higher in some countries. In this case, the situation is more unsafe and increases the possibility of fatal injuries or fatalities in the case of a crash. Therefore, it is expected that the pedestrians will be more cautious on these roads. Aim: This study aims to explore pedestrian compliance at signalized intersections on major arterials with 80 km/hr speeds in Qatar. Methods: Video data were collected for pedestrian movements at multiple intersections. Results: The study reported a 68.1 percent compliance rate at the study locations. The results also revealed that 14.6 percent of the pedestrians crossed during the Flashing Don’t Walk interval and 17.3 percent crossed during the Steady Don’t Walk interval. These rates are considered high compared to other countries. Several variables that may influence pedestrians’ behavior were investigated. Binary and ordinal logistic regression models were developed to describe the pedestrian crossing behavior as a function of these variables. Conclusion: Male and middle-age pedestrians were more likely to cross during these two intervals. The analysis showed that female pedestrians, elder pedestrians, pedestrians crossing in groups, pedestrians waiting before crossing, and pedestrians crossing against a flow of other pedestrians are more likely to comply and cross during the Walk interval compared to other groups. Several solutions were proposed in the study to increase compliance rates.

Shape retrieval using angle-wise contour variance

In this study, we propose a geometric feature set for 2D shape retrieval. Conventional Hough feature gives the edge locations along with angle and creates Hough table if there are multiple intersections at borders. In this paper, a statistical way to represent the relation of repeating contours at each angle around the shape centroid is presented. The main contribution of this paper is to use the standard deviation of repeating contours. We calculate the angle between the shape centroid and each point on the contour. For each integer angle value, three features were extracted: the number of contour repetitions, the average distance of the points at that angle to the centroid, and the standard deviation of the points at the same angle. Thus, a 2D image was represented by a constant sized matrix, regardless of its size. In the case of similarity between two images, instead of merging features within a single expression, the algorithm picked the feature with the highest similarity rate for that comparison. We tested the proposed method on MPEG-7, Kimia99, ETH-80 datasets for a benchmark with the state-of-the-art. It outperformed most of the recent methods in terms of retrieval rate.

Food and Mediations

The chapter attempts to look at food and its representation in media with a special focus on Punjab and its cuisine. The work locates important symbols pertaining to the food culture of Punjab in sites such as cookbooks and cinema, which interestingly mix traditional with contemporary representations of material life. The first section looks at the cultural expressions of Punjabi cuisine in cookbooks against the backdrop of the history of Punjab, its ancient ties, and cultural affiliations of the past. Questions of caste, gastro-ethnicity, and stereotyping are also examined. The second section attempts to review select Bollywood films in order to cast light onto the contemporary socio-cultural conceptions of Punjabi culture. The study concludes by observing the ways in which food emerges as a commodity spectacle through stories and ideas on the food of Punjab. The work is carried out in order to exemplify the role of food in the creation of a cultural imaginary and explore the subtle connection that food and food culture share with the multiple intersections of an individual's identity.

Research on the Design of Disaster Prevention Plan for 22km Ultra-long Highway Tunnel with Multiple Intersections

The Tianshan Shengli Tunnel is currently the longest high-altitude highway tunnel. In order to ensure the safe operation of the tunnel, the SES software is used to investigate the wind speed laws in the tunnel, and the tunnel is divided into 16 disaster prevention sections based on the shaft and critical wind speed. The principles of disaster prevention and rescue of Tianshan Shengli Highway Tunnel are given, and the emergency treatment process of tunnel disaster prevention and rescue is given. The disaster prevention and rescue plan of Tianshan Shengli Tunnel from fire occurrence, personnel and vehicle evacuation, and fire treatment are discussed in detail.