Transportation Infrastructure Systems - Task 1

Total number of crashes by each calendar year (e.g., 2011, 2012, …, 2019)
Number of crashes in different days of a week (e.g., Mon, Tue, …, Sun)
Proportions of crashes in different hours in a day (e.g., 00:00-00:59, 01:00-01:59, …,23:00-23:59 hours)
Proportions of crashes by different levels of crash severity
Number and proportions of crashes by different types of crashes (hint: use DCA codes)

From above graphical representation concluded that from the 1^st January 2011 to 31^stDecember 2019, the crashed record according police tracking, April to October of 2015 and 2016 highest number of accident occurred. Week days reported comparatively larger number of crashed as compare to weekend and all that crashed happened in rush or office hours in between 8:00 a.m. to 8:00 p.m. of the day.as per the severity fatal accident have constant pattern throughout the all years, while serious accident is decreasing pattern to increasing the years and other injuries noted maximum crashed and having the fluctuated through all years. Also from DCA codes pedestrian, cross traffic and off path on straight was decline the number of crashed to recent years and major number of crashed are accountable due to read end DCA codes.

Transportation Infrastructure Systems - Task 2

for the generating the collision the diagram, considering the 218635085 as the number and detailed the following data.

ACCIDENT_NO	Accident Type Desc	LIGHT_CONDITION	Light Condition Desc	Road Geometry Desc	SEVERITY
T20080003829	Collision with vehicle	1	Day	Not at intersection	3
T20080012478	Collision with vehicle	3	Dark Street lights on	Cross intersection	3
T20090030469	Collision with vehicle	3	Dark Street lights on	Cross intersection	3
T20090039853	Collision with vehicle	1	Day	Cross intersection	3
T20100045310	Collision with vehicle	1	Day	Not at intersection	2
T20100049566	Collision with vehicle	2	Dusk/Dawn	Cross intersection	2
T20100051239	Collision with vehicle	1	Day	Cross intersection	3
T20110006830	Collision with vehicle	2	Dusk/Dawn	Cross intersection	3
T20110036971	Collision with vehicle	1	Day	Cross intersection	3
T20120000930	Collision with vehicle	1	Day	Cross intersection	3
T20130013607	Collision with vehicle	1	Day	Cross intersection	3
T20130014475	No collision and no object struck	3	Dark Street lights on	Not at intersection	3
T20130020999	Collision with vehicle	1	Day	Cross intersection	3
T20140004009	Collision with vehicle	1	Day	Cross intersection	2
T20140004219	Collision with vehicle	1	Day	Cross intersection	3
T20140007028	Collision with vehicle	3	Dark Street lights on	Cross intersection	2
T20140008074	Collision with vehicle	3	Dark Street lights on	Cross intersection	3
T20140009411	Struck Pedestrian	3	Dark Street lights on	Cross intersection	3
T20140010318	Collision with vehicle	1	Day	Cross intersection	3
T20140020263	Collision with vehicle	1	Day	Cross intersection	3
T20140024739	Collision with vehicle	1	Day	Cross intersection	3
T20150004306	Collision with a fixed object	3	Dark Street lights on	Cross intersection	2
T20160001810	Collision with vehicle	1	Day	Cross intersection	3
T20160021322	Collision with vehicle	3	Dark Street lights on	Cross intersection	3
T20160023929	Collision with vehicle	3	Dark Street lights on	Cross intersection	3
T20180019850	Collision with vehicle	3	Dark Street lights on	Cross intersection	3

Transportation Infrastructure Systems - Task 3

For the value of A, from the student number 218635085 and the average of last two digits is 6.5 from that considering the confidence level is 91.5% and the get resulted from the SPSS software.

Transportation Infrastructure Systems - Task 4

CAVs are required to improve street limit, driven by innovation empowered decrease in the security hole (for example vehicle progress), from around 0.9 seconds (s) to about 0.2s and take out mishaps identified with human mistake. When considering human solace, specialists gauge the base mediocre wellbeing hole to be around 0.5s between vehicles. The wide estimate go is driven by the determination of a fitting standard and vulnerability in how much innovation abilities will be applied later on. Notwithstanding this, various sources point towards assessed viable CAV limit elevates in the scope of 60% to 80% in vehicles per path hour[1]. CAVs give the most fascinating and promising open door for empowering clients to more readily screen transportation network conditions and settle on better working choices to decrease energy utilization, ozone harming substance discharges, travel delays and improve safety[2].

Austrian government faces the issue are Traffic signs and street markings and Incident and roadworks correspondences at dominant part level[3]. CAVs require profoundly noticeable street edges, bends, speed limit and other signage to finish the assignment of finding, exploring, and stopping. Nonetheless, the plan and keep up of signs and markings are far away from obliging CAVs. For instance, blurred street markings have irregular issues in North America; low upkeep need cause signs indiscernible in the UK; non-standard street signs confounded clients in the EU. So as to receive CAVs, governments and associations should call for uniform street stamping across EU individuals, or even propose worldwide normalization, and furthermore improve support measures and set up observing frameworks. To supplement the "meaningfulness" upkeep of streets, redesigns could likewise upgrade the splendor of streetlamps and much of the time control side of the road vegetation. Occurrences and roadworks will change the street design, which require CAVs to decipher constant changes, for example, blending paths proposals gave by brief signs and cones. As of now, two sites give ongoing data on car crashes and roadworks in the Australia. Despite the fact that, the two sites give the reason and season of mishaps, the absence of precise on location format imaging actually makes it hard for CAVs to recognize ongoing changes from chronicled maps, subsequently hard to navigate[3].

References for Impact of Connected and Automated Vehicles

He et al., "Cooperative Connected Autonomous Vehicles (CAV): Research, Applications and Challenges," 2019 IEEE 27th International Conference on Network Protocols (ICNP), Chicago, IL, USA, 2019, pp. 1-6, doi: 10.1109/ICNP.2019.8888126.

Jackeline Rios-Torres et al., “Impact of Connected and Automated Vehicles on Traffic Flow”,2018.

Sujanie Peiris et al., “Road Trauma in Regional and Remote Australia and New Zealand in Preparedness for ADAS Technologies and Autonomous Vehicles,” May 2020, Sustainability 12(11):4347

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