Cost-Optimal Time-dEpendent Routing with Time and Speed Constraints in Directed Acyclic Road Networks

2016 ◽  
Vol 15 (06) ◽  
pp. 1413-1450
Author(s):  
Yaqiong Liu ◽  
Hock Soon Seah ◽  
Guochu Shou
Keyword(s):  
Travel Time ◽  
Nonlinear Optimization ◽  
Fuel Consumption ◽  
Real World ◽  
Computer Games ◽  
Road Networks ◽  
Minimum Cost ◽  
Time Dependent ◽  
Optimal Time ◽  
Step Algorithm

Travel costs on road networks always change over time which implies road networks are time dependent. Most studies on time-dependent road networks simply find the shortest path with the least travel time without considering waiting at some nodes, or fuel consumption and toll fee. In real-world applications or computer games, waiting may be allowed at some nodes but disallowed at other nodes; a user can traverse an edge at different speeds; monetary travel cost contains fuel cost and toll fees; and users usually prefer the minimum-cost route under time and speed constraints. Therefore, we study Cost-Optimal Time-dEpendent Routing (COTER) problem with time and speed constraints. We utilize two fuel consumption models and compute the minimum fuel consumption with given travel time for highway edges via nonlinear optimization. We allow the toll fee function to be an arbitrary single-valued time-dependent function. We define an Optimal Cost (OC) function for each candidate node [Formula: see text], and derive the recurrence relation formula between [Formula: see text]’s incoming neighbors’ OC-functions and [Formula: see text]’s OC-functions. To solve COTER, we propose a five-step algorithm, namely, ALG-COTER, which uses Fibonacci-heap optimized Dijkstra, topological sorting, dynamic programming, binary min-heap optimization, nonlinear optimization, and backtracking algorithms. Experimental results on three real-world road networks of different sizes demonstrate that our algorithm finds the optimal route efficiently and is scalable to different parameters.

scholarly journals Time-Dependent Alternative Route Planning: Theory and Practice

Algorithms ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 220
Author(s):  
Spyros Kontogiannis ◽  
Andreas Paraskevopoulos ◽  
Christos Zaroliagis
Keyword(s):  
Travel Time ◽  
Real World ◽  
Route Planning ◽  
Theory And Practice ◽  
Time Dependent ◽  
Planning Theory ◽  
Alternative Route ◽  
Alternative Graph ◽  
Query Algorithm ◽  
Alternative Routes

We consider the problem of computing a set of meaningful alternative origin-to-destination routes, in real-world road network instances whose arcs are accompanied by travel-time functions rather than fixed costs. In this time-dependent alternative route scenario, we present a novel query algorithm, called Time-Dependent Alternative Graph (TDAG), that exploits the outcome of a time-consuming preprocessing phase to create a manageable amount of travel-time metadata, in order to provide answers for arbitrary alternative-routes queries, in only a few milliseconds for continental-size instances. The resulting set of alternative routes is aggregated in the form of a time-dependent alternative graph, which is characterized by the minimum route overlap, small stretch factor, small size, and low complexity. To our knowledge, this is the first work that deals with the time-dependent setting in the framework of alternative routes. The preprocessed metadata prescribe the minimum travel-time informations between a small set of “landmark” nodes and all other nodes in the graph. The TDAG query algorithm carries out the work in two distinct phases: initially, a collection phase constructs candidate alternative routes; consequently, a pruning phase cautiously discards uninteresting or low-quality routes from the candidate set. Our experimental evaluation on real-world, time-dependent road networks demonstrates that TDAG performed much better (by one or two orders of magnitude) than the existing baseline approaches.

scholarly journals Optimal time-dependent sequenced route queries in road networks

2015 ◽  
Author(s):  
Camila F. Costa ◽  
Mario A. Nascimento ◽  
José A. F. Macêdo ◽  
Yannis Theodoridis ◽  
Nikos Pelekis ◽  
...  
Keyword(s):  
Road Networks ◽  
Time Dependent ◽  
Optimal Time

scholarly journals Trip Travel Time Forecasting Based on Selective Forgetting Extreme Learning Machine

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Zhiming Gui ◽  
Haipeng Yu
Keyword(s):  
Travel Time ◽  
Extreme Learning Machine ◽  
Road Networks ◽  
Time Estimation ◽  
Learning Ability ◽  
Prediction Algorithm ◽  
Travel Time Estimation ◽  
Trace Data ◽  
Learning Machine ◽  
Travel Time Forecasting

Travel time estimation on road networks is a valuable traffic metric. In this paper, we propose a machine learning based method for trip travel time estimation in road networks. The method uses the historical trip information extracted from taxis trace data as the training data. An optimized online sequential extreme machine, selective forgetting extreme learning machine, is adopted to make the prediction. Its selective forgetting learning ability enables the prediction algorithm to adapt to trip conditions changes well. Experimental results using real-life taxis trace data show that the forecasting model provides an effective and practical way for the travel time forecasting.

Real-world assessment of urban bus transport in a medium-sized city of the Middle East: Driving behavior, emission performance, and fuel consumption

2021 ◽  
Vol 12 (3) ◽  
pp. 113-124 ◽  
Author(s):  
Omid Ghaffarpasand ◽  
Mohammad Reza Talaie ◽  
Hossein Ahmadikia ◽  
Amirreza Talaie Khozani ◽  
Maryam Davari Shalamzari ◽  
...  
Keyword(s):  
Middle East ◽  
Fuel Consumption ◽  
Real World ◽  
Driving Behavior ◽  
Emission Performance ◽  
Urban Bus ◽  
Bus Transport

Influences of vehicles’ fuel consumption and exhaust emissions on the trip cost without late arrival under car-following model

2016 ◽  
Vol 27 (01) ◽  
pp. 1650011 ◽  
Author(s):  
Tie-Qiao Tang ◽  
Qiang Yu
Keyword(s):  
Fuel Consumption ◽  
Exhaust Emissions ◽  
Optimal Time ◽  
Fuel Cost ◽  
Total Cost ◽  
Car Following ◽  
Time Headway ◽  
Late Arrival ◽  
Car Following Model ◽  
Open Road

In this paper, we use car-following model to explore the influences of the vehicle’s fuel consumption and exhaust emissions on each commuter’s trip cost without late arrival on one open road. Our results illustrate that considering the vehicle’s fuel cost and emission cost only enhances each commuter’s trip cost and the system’s total cost, but has no prominent impacts on his optimal time headway at the origin of each open road under the minimum total cost.

Performance Approximation for Time-Dependent Queues with Generally Distributed Abandonments

2021 ◽  
Author(s):  
Gregor Selinka ◽  
Raik Stolletz ◽  
Thomas I. Maindl
Keyword(s):  
Performance Measures ◽  
Real World ◽  
Queueing System ◽  
Time Dependent ◽  
Interval Length ◽  
Arrival Process ◽  
Real World Data ◽  
World Data ◽  
Extant Literature ◽  
Approximation Quality

Many stochastic systems face a time-dependent demand. Especially in stochastic service systems, for example, in call centers, customers may leave the queue if their waiting time exceeds their personal patience. As discussed in the extant literature, it can be useful to use general distributions to model such customer patience. This paper analyzes the time-dependent performance of a multiserver queue with a nonhomogeneous Poisson arrival process with a time-dependent arrival rate, exponentially distributed processing times, and generally distributed time to abandon. Fast and accurate performance approximations are essential for decision support in such queueing systems, but the extant literature lacks appropriate methods for the setting we consider. To approximate time-dependent performance measures for small- and medium-sized systems, we develop a new stationary backlog-carryover (SBC) approach that allows for the analysis of underloaded and overloaded systems. Abandonments are considered in two steps of the algorithm: (i) in the approximation of the utilization as a reduced arrival stream and (ii) in the approximation of waiting-based performance measures with a stationary model for general abandonments. To improve the approximation quality, we discuss an adjustment to the interval lengths. We present a limit result that indicates convergence of the method for stationary parameters. The numerical study compares the approximation quality of different adjustments to the interval length. The new SBC approach is effective for instances with small numbers of time-dependent servers and gamma-distributed abandonment times with different coefficients of variation and for an empirical distribution of the abandonment times from real-world data obtained from a call center. A discrete-event simulation benchmark confirms that the SBC algorithm approximates the performance of the queueing system with abandonments very well for different parameter configurations. Summary of Contribution: The paper presents a fast and accurate numerical method to approximate the performance measures of a time‐dependent queueing system with generally distributed abandonments. The presented stationary backlog carryover approach with abandonment combines algorithmic ideas with stationary queueing models for generally distributed abandonment times. The reliability of the method is analyzed for transient systems and numerically studied with real‐world data.

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