We present an approach to “participatory route planning”, a novel concept that takes advantage of mobile devices, such as cellular phones or embedded systems in cars, to form an interactive, participatory network of vehicles that plan their travel routes based on the current trafﬁc conditions and existing routes planned by the network of participants, thereby making more informed travel de-cision for each participating user. The premise of this approach is that a route, or plan, for a vehicle is also a prediction of where the car will travel. If routes are created for a sizable percentage of the total vehicle population, an estimate for the overall trafﬁc pattern is attainable. Taking planned routes into account as predictions allows the entire trafﬁc route planning system to better distribute vehicles and minimize trafﬁc congestion. We present an approach that is suitable for realistic, city-scale scenarios, a prototype system to demonstrate feasibility, and experiments using a state-of-the-art microscopic trafﬁc simulator.
This figure shows the mean travel times for varying numbers
of vehicles using our method, a shortest-path baseline (SP),
and a commercial-like system using sensor data (SD). We observe
that our method (red) outperformed both the shortest-path baseline
(navy) and the commercial-like system with sensor data (sky blue).
For more results, please refer to our full paper.
This work was supported in part by ARO Contract W911NF-10-1-0506, NSF awards 0917040, 0904990 and 1000579, and RDECOM Contract WR91CRB-08-C-0137.