Abstract
With advances in connected vehicle technology, dynamic vehicle route guidance models gradually become indispensable equipment for drivers. Traditional route guidance models are designed to direct a vehicle along the shortest path from the origin to the destination without considering the dynamic traffic information. In this paper a dynamic travel time estimation model is presented which can collect and distribute traffic data based on the connected vehicles. To estimate the real-time travel time more accurately, a road link dynamic dividing algorithm is proposed. The efficiency of the model is confirmed by simulations, and the experiment results prove the effectiveness of the travel time estimation method.
Highlights
For the past decades, many densely populated cities suffered from traffic congestion in road systems
Advancements made in connected vehicle technology which is integrated with wireless communications and global position system (GPS) allow much greater access to realtime roadway data
Accounting for time-dependent traffic characteristics and dynamic route guidance systems (DRGS)’s challenges, this paper proposes a road link dynamic dividing (RLDD) model to process spatial and temporal traffic data for estimating travel time more accurately
Summary
Many densely populated cities suffered from traffic congestion in road systems. To alleviate the problems caused by traffic congestion, widening existing roads and constructing new roads are the main methods This kind of method cannot satisfy the requirement of the increasing number of vehicles. Static route guidance systems are designed to compute the shortest path with Dijkstra algorithm to direct a vehicle from its origin to destination These paths are identified based on predetermined set of network attributes and not combined with real-time traffic conditions on roadways. Along with computational power available, has made implementation of dynamic route guidance systems (DRGS) feasible and one of the most promising technologies for alleviation of traffic congestion, which will reduce the travel time of drivers, avoid congested road segments, and raise road network efficiency.
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