Real-time urban regional route planning model for connected vehicles based on V2X communication

Abstract

Advancement in the novel technology of connected vehicles has presented opportunities and challenges for smart urban transport and land use. To improve the capacity of urban transport and optimize land-use planning, a novel real-time regional route planning model based on vehicle to X communication (V2X) is presented in this paper. First, considering the traffic signal timing and phase information collected by V2X, road section resistance values are calculated dynamically based on real-time vehicular driving data. Second, according to the topology structure of the current regional road network, all predicted routes are listed based on the Dijkstra algorithm. Third, the predicted travel time of each alternative route is calculated, while the predicted route with the least travel time is selected as the optimal route. Finally, we design the test scenario with different traffic saturation levels and collect 150 sets of data to analyze the feasibility of the proposed method. The numerical results have shown that the average travel times calculated by the proposed optimal route are 8.97 seconds, 12.54 seconds, and 21.85 seconds, which are much shorter than the results of traditional navigation routes. This proposed model can be further applied to the whole urban traffic network and contribute to a greater transport and land-use efficiency in the future.

An Adaptive Route Planning Method of Connected Vehicles for Improving the Transport Efficiency

“…The essence of existing individual route-planning methods for CVs is to selfishly design a route with the shortest individual travel time [38], including static [13] and dynamic [38] shortest-time routes. Non-cooperative route-planning methods reduce the overall travel efficiency.…”

Multiobjective Model Predictive Control Based on Urban and Emission Macroscopic Fundamental Diagrams

“…An alternative to Perimeter Control is the Routing strategy, also known as Route Guidance, used to suggest alternative paths offered by the road infrastructure. This application has some advantages since its applicability suits well in a period in which the spread of information is guaranteed by the development of different technological systems such as smartphones providing floating car data (FCD) [37], [38], and emerging vehicle-to-everything (V2X) communication technologies [39], [40], [41]. A second advantage relies on the minor infrastructure costs since it is not necessary to control the traffic light system, but the usage of Intelligent…”

A Novel Rough Numbers based Extended MACBETH Method Implementation in the Prioritization of the Connected Autonomous Vehicles

“…In a study regarding the integration of CAVs and VSL, an investigation of bottleneck discharge rates and system delay reductions is performed (Han et al, 2017). In a different study, integrating CAVs and dynamic route guidance systems are investigated (Wang et al, 2020). A simulation study of the matter shows that CAVs' ability to gather and transmit data enables the detection of shorter routes in means of travel times.…”