Title-: Traffic near my college area
Authors-: Satvic Bhand
Varsha Kucheria
Shruti Bundela
Introduction-:
Traffic congestion near my college campus has emerged into recurring problem affecting student’s regular commute, safety, and punctuality. Increasing vehicle movement during peak hours leads to delays, noise, and inconvenience for a lot of individuals travelling from that area.. Understanding student’s experiences and perceptions is essential to assess the severity and causes of this issue. This study uses a survey-based approach to analyse the traffic problem in the campus vicinity and support informed solutions.
Objective -:
To understand the underlying issues of the traffic congestion near my campus area leading to delays and frustration.
Literature Review -:
Mamoona Humayun,
Detecting and counting on road vehicles is a key task in intelligent transport management and surveillance systems. The applicability lies both in urban and highway traffic monitoring and control, particularly in difficult weather and traffic conditions. In the past, the task has been performed through data acquired from sensors and conventional image processing toolbox. However, with the advent of emerging deep learning based smart computer vision systems the task has become computationally efficient and reliable. The data acquired from road mounted surveillance cameras can be used to train models which can detect and track on road vehicles for smart traffic analysis and handling problems such as traffic congestion particularly in harsh weather conditions where there are poor visibility issues because of low illumination and blurring. Different vehicle detection algorithms focusing the same issue deal only with on or two specific conditions. In this research, we address detecting vehicles in a scene in multiple weather scenarios including haze, dust and sandstorms, snowy and rainy weather both in day and nighttime. The proposed architecture uses CSPDarknet53 as baseline architecture modified with spatial pyramid pooling (SPP-NET) layer and reduced Batch Normalization layers. We also augment the DAWN Dataset with different techniques including Hue, Saturation, Exposure, Brightness, Darkness, Blur and Noise. This not only increases the size of the dataset but also make the detection more challenging. The model obtained mean average precision of 81% during training and detected smallest vehicle present in the imageFarzeen Ashfaq, Noor Zaman Jhanjhi2 and Marwah Khalid Alsadun.
Mary Jo Salvacion Goetsch1, Dr. Jonathan E. Lobaton
The purpose of this study was to determine the characteristics, roles and challenges of traffic personnel and their implications toward efficient traffic management system in Bacolod City during the second quarter of
calendar year 2018. A mixed methods research design was used which involved the use of both quantitative and qualitative methods by means of survey responded by 150 traffic personnel, key informant interview
participated by 3 Barangay Captains and a City Councilor, and focus group discussion participated by 6 traffic personnel which were all selected through a purposive and convenience sampling techniques.
Frequency count, percentage, weighted mean, standard deviation, Mann Whitney U, Kruskal Wallis and IBM SPSS Version 19 were employed to analyze and present the data for quantitative part. While the
qualitative part of the study, Thematic Analysis was utilized. The findings showed that traffic personnel who participated in the study were almost equally divided when grouped according to age, while majority were
male, attained college level, have less than 7 years of experience and designated as traffic enforcer.Meanwhile, not all completed the required trainings. When it comes to their roles as traffic personnel, it
showed that they are mainly managing traffic flow and implementing traffic rules and regulations in theroads. Moreover, it showed that majority of them are highly knowledgeable on City Ordinance 338, and there are no significant differences when they were grouped according to age, sex, educational attainment, and job designation. However, significant differences were found in their level of knowledge on the aforementioned
ordinance when they were grouped according to length of service and trainings attended. On the other hand, it was found out that the top most challenge experienced by theparticipants is the arrogance of drivers. The
lack of discipline which includes disregarding of traffic rules and regulations among drivers follows next. Ignorance of the traffic rules and regulations among road users, attitude of drivers, bad weather conditions,
high volume of vehicles and road widening projects are also included in the short list of challengesencountered by traffic personnel in the City. Finally, results of this study were used in formulating anenhanced traffic management system program for Bacolod Traffic Authority Office
Data Collection-:
For the above problem 5 questions were framed on Likert’s Scale
The Questions framed are as follows;-
Q.-1 I believe that inadequate traffic management is the main cause of congestion outside my college
Q.-2 I experience traffic congestion outside my college during peak hours.
Q.-3 I think that proper traffic control measures (signals, police presence, speed breakers) can reduce traffic problems outside my college.
Q.-4 I believe that awareness among students and commuters can help reduce traffic problems outside my college.
Q.5-I feel that traffic congestion outside my college increases during specific time slots (morning, afternoon, evening).
Data Analysis
The t-stat value at which we arrived at values which is greater than 1.96, accept positively, meaning people agree.
Conclusion