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Abstract
Air contamination becomes an urgent problem to be considered as a result of the rapid growth in traffic all over the world. Traffic emissions differ from vehicle to vehicle depending on the vehicle type, production year, fuel octane number, and periodical maintenance of the vehicle. The majority of drivers do not revise their harmful vehicles emissions regularly. Therefore, effective tracking of high-emitting vehicles can be an important solution for reducing traffic air pollution. This study proposes a location strategy for vehicle remote sensing monitors aided with ID-plate recognizer to capture any violated vehicle emissions. The problem is formulated into a graph theory problem, and then a novel adapted metaheuristic algorithm is used to solve the problem. The methodology, using a benchmark problem, has managed to solve the problem to the optimality. Moreover, its robustness is measured statistically.
Highlights
Since the middle of the past century, traffic has grown tremendously all over the world
This study presents a novel methodology for solving the remote emission sensing monitors location problem which received little attention in the literature
The heuristics steps of the methodology are simple to deploy and general for any network. They only depend on the path enumeration criteria which are defined for transport networks
Summary
Since the middle of the past century, traffic has grown tremendously all over the world. The exhaust from vehicles contains carbon monoxide (CO), hydrocarbons (HC), nitrogen oxide (NO), particulate matter (PM), and many other toxic substances Some vehicles emit these substances with high levels which exceed the allowable threshold due to the carelessness of the owners in revising their vehicles periodically or even using the appropriate type of fuel (economic aspects) [4]. Strict regulations with a real-time ticket for violating vehicles would force drivers to check their cars’ emissions regularly. The problem solution would guarantee the full observation of traffic emissions through the network. A novel strategy is developed to minimize the required number of emission sensors (i.e., the system proposed in Figure 1) to be installed on a network to intercept all the traffic (i.e., every vehicle once at least).
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