Segment Trees based Traffic Congestion Avoidance in Connected Cars Context

Scalable Data Model for Traffic Congestion Avoidance in a Vehicle to Cloud Infrastructure

“…The query operation can become a bottleneck when the query frequency is high or the number of vehicles on the road network is high (traffic congestion). An innovative traffic modeling solution is described in [ 22 ] where the traffic state is defined by the generated vehicle routes that simulates the traffic. For traffic simulation they integrated and adapted OSMAnd navigation application to generate vehicle routes like in real world route planning context.…”

“…As is shown in Section 6 , this data structure has scaling limitations due to performance of update and query operations. Following the same methodology [ 24 ] like the approach in [ 22 ] our work is proposing a novel and scalable solution based on K-ary Tree. Using this approach, we efficiently model simulated traffic in order to predict and avoid traffic congestion in urban areas.…”

“…The first query, Q1, focuses on the number of vehicles that pass a road during any specific time interval. The work in [ 22 ] adapts the segment tree data structure to answer this query.…”

“…This data structure should support efficient update operations too. Segment tree is such a data structure and it was proposed by the work in [ 22 ] for the purpose of representing traffic information. In their proposal the segment tree represents the entire time interval (e.g., a day) for traffic query and update on a specific map segment.…”

“…Route planning algorithms use and impact different aspects (e.g., traffic information) of daily travel experience as is presented and evaluated in various works [ 10 , 11 , 12 , 13 , 14 , 15 , 16 ]. From implementation cost perspective, it was shown that traffic modeling through simulation is an efficient and reliable approach [ 17 , 18 , 19 , 20 , 21 , 22 , 23 ]. Considering all the above mentioned challenges and achievements, we found that there is an urgent need to develop a scalable traffic modeling database that can be used by navigation systems to predict and avoid congestion based on accurate traffic information during route planning.…”