An efficient multi‐destinations trip planning protocol for intelligent transport system

Abstract

AbstractTargeting several destinations on the same trip is commonly seen over the downtown areas. Several drivers leave their home or work everyday targeting multiple end‐destinations for shopping or entertaining purposes. The sequence of visiting destinations can be selected randomly by the drivers, especially if they are less familiar with the area of interest or with multi‐destinations trips. However, expert drivers that travel more frequently towards several destinations should be more cautious planning their trips. They consider the relative locations of these end‐destinations and use their historical knowledge regarding the traffic over the connected road segments there. This paper proposes an efficient multi‐destinations trip planning protocol (MDPP) that recommends drivers with the best sequence of destinations to visit. The proposed protocol considers the location of each destination and the relative distance between all located destinations. It also considers the traffic distribution over the investigated areas of interest to recommend drivers to avoid highly congested road segments or road segments that suffer traffic issue such as accident or emergency existence. From the experimental results, we can see that the MDPP protocol has selected the best path towards the targeted destinations compared with other common selected sequences. It has decreased the travel time, fuel consumption, and the gas emissions for different investigated scenarios.