We deal with an algorithm that, once origin and destination are fixed, individuates the route that permits to reach the destination in the shortest time, respecting an assigned maximal travel time, and with risks measure below a given threshold. A fluid dynamic model for road networks, according to initial car densities on roads and traffic coefficients at junctions, forecasts the future traffic evolution, giving dynamical weights to a constrained K shortest path algorithm. Simulations are performed on a case study to test the efficiency of the proposed procedure
Abstract. Many urban areas suffer from traffic congestion. Intuitively, it may seem that a road expa...
This paper presents a stochastic motion planning algorithm and its application to traffic navigation...
For navigation purposes, drivers rely on applications such as Google maps or navigating devices mou...
We deal with an algorithm that, once origin and destination are fixed, individuates the route that p...
We deal with the optimization of traffic flows at road junctions, in order to manage congestion phe...
Current routing devices route an individual car driver from start to destination in the shortest tim...
Despite measures to reduce congestion, occurrences of both recurrent and non-recurrent congestion ca...
Shortest path determination in a dynamic transportation network has been a real challenge where netw...
In this paper, a predictive dynamic traffic assignment model in congested capacity-constrained road ...
The research presented in this dissertation aims to develop computationally tractable models and alg...
This thesis develops methodologies for solving constrained shortest path problems in dynamic and ran...
A novel path planning approach is presented to solve optimal path in stochastic, time-varying networ...
The dynamic and stochastic shortest path problem (DSSPP) is defined as finding the expected shortest...
The aim of this work is to present a technique for the optimisation of emergency vehicles travel ti...
Current day routing systems use predicted travel times to calculate optimal routes. Some routing alg...
Abstract. Many urban areas suffer from traffic congestion. Intuitively, it may seem that a road expa...
This paper presents a stochastic motion planning algorithm and its application to traffic navigation...
For navigation purposes, drivers rely on applications such as Google maps or navigating devices mou...
We deal with an algorithm that, once origin and destination are fixed, individuates the route that p...
We deal with the optimization of traffic flows at road junctions, in order to manage congestion phe...
Current routing devices route an individual car driver from start to destination in the shortest tim...
Despite measures to reduce congestion, occurrences of both recurrent and non-recurrent congestion ca...
Shortest path determination in a dynamic transportation network has been a real challenge where netw...
In this paper, a predictive dynamic traffic assignment model in congested capacity-constrained road ...
The research presented in this dissertation aims to develop computationally tractable models and alg...
This thesis develops methodologies for solving constrained shortest path problems in dynamic and ran...
A novel path planning approach is presented to solve optimal path in stochastic, time-varying networ...
The dynamic and stochastic shortest path problem (DSSPP) is defined as finding the expected shortest...
The aim of this work is to present a technique for the optimisation of emergency vehicles travel ti...
Current day routing systems use predicted travel times to calculate optimal routes. Some routing alg...
Abstract. Many urban areas suffer from traffic congestion. Intuitively, it may seem that a road expa...
This paper presents a stochastic motion planning algorithm and its application to traffic navigation...
For navigation purposes, drivers rely on applications such as Google maps or navigating devices mou...