Utilization of Neural Network-Based Approach in Bike Routes Optimization for Port Said Urban Road Network

Abstract

Transport department of urban cities always need to keep abreast of sustainable developments such as in Port Said city that is an important urban city in Egypt. Bike routes planning mission is not an easy occupation especially in developing countries. Mixed traffic is a main shape of the transportation system in most of their systems that are far away from the sustainable transport policies. One of the most effective solutions, for a modern sustainable transport, is the increasing of bike users. On the other side, a lot of problems and accidents had been occurred according to bike crossing among other transport vehicles; cars, buses, taxis, and others. This paper aims at studying the introduction bike routes effectiveness. It concludes the driver’s reaction to a definite planning scenario and how the objective function is affected by the optimistic impact of the modal modification. The objective function has been supposed by assigning a suitable time saving for bike users using artificial neural network (ANN) approach. It shows the effect of bike speed change on the route using a greedy algorithm of the user’s maximization welfare function. The study designated only four streets from seven selected streets to be suitable routes for bike routes introduction. The average bike speed is predicted to increase from 1.5 km per hour to 2.4 km per hour after introducing the bike routes.