Using Data to Improve the Efficiency of Traffic Flow

Using the Data to Improve the Efficiency of Traffic Flow
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1.0. Definition of Problem
Traffic congestion is a critical issue due to its multifaceted impact. Inefficient flow of traffic results in overutilization of resources, including roads and human capital, primarily due to the wastage of time. Similarly, it also affects the meantime for commuters, subsequently affecting the utilization of time on a wide scale with its far-reaching implications for business and the economy (Fong et al., 2017). Similarly, inefficient traffic flow results in the over-consumption of fuel and energy (Fong et al., 2017). Therefore, it is important to take measures and implement instruments and solutions that can help improve the traffic flow consistently.
2.0. Impacted Stakeholders
The stakeholders likely to be impacted by the problem include:
City Government: Due to the cost associated with the over-utilization of resources.
Commuters: Due to the impact on their mean time to travel from one destination to another (such as to/from home to/from office on a routine basis).
Residential and commercial drivers: Traffic congestion adds to commute time. Similarly, drivers face an increased risk of road accidents if the traffic flow remains inconsistent and their exposure to traffic congestion remains high.
Businesses: Due to the time to be allocated for commuting for business purposes. Similarly, it is critically problematic for businesses that rely on home delivery services as traffic jams and congestion may affect their commitments for delivery time.
3.0. Smart City Technology Solution
The technology-based solution proposed to improve the traffic flow is to use modern technologies that can offer insights about the traffic flow and help optimize route planning and other aspects of road management, ultimately resulting in reduced congestion and consistency. As discussed, the contemporary approach to traffic management requires a sophisticated approach focusing on the complex interplay among different factors at different levels (Fong et al., 2017). Therefore, there must be more than a single technology or a linear solution. Therefore, the set of technologies described below is considered to address the problem effectively:
3.1. In-Vehicle Cameras
In-vehicle cameras can offer potential insights into the average speed, breakdowns, accidents, and other incidences if processed using targeted algorithms. The authorities can use this information to apply queueing theory, which involves a mathematical overview of the waiting lines at any point (Fong et al., 2017). It means the authorities can get an idea about the build-up of vehicles at any particular point or various points within the network to predict and respond in real-time. Similarly, the information can also be used to detect 'abnormal events,' guiding the authorities to take appropriate measures promptly before the ripple effect of those events results in congestion or traffic jams.
3.2. Road Sensors
Road sensors are necessary when seen from the perspective of the speed-flow-density relationship. The sensors, including the radars and other detectors, give an overview of the key bottlenecks and congestion at different points to help the concerned authorities predict the next development, such as impending traffic jams. These sensors provide valuable information about the volume of traffic, density, and average speed (Fong et al., 2017). Therefore, the managers can use these insights to apply re-routing strategies and readjust the traffic signals to keep the flow intact and help the bottlenecks ease before they become unmanageable.
3.3. GPS System
The GPS is also help...