Path planning is one of the most important aspects for ambulance driving. A local dynamic
path planning method based on the potential field theory is presented in this paper. The …

We propose a new framework for decision making under uncertainty to overcome the main
drawbacks of current technology: modeling complexity, scenario generation, and scaling …

Based on comparative studies on correlation coefficient theory and utility theory, a series of
rules that utility functions on dual hesitant fuzzy rough sets (DHFRSs) should satisfy, and a …

Facing various uncertainties in real world traffic, navigation services are typically formulated
as a certain stochastic shortest path problem (SSPP). In the past several years, many …

为了提高突发交通拥堵情境下在途路径诱导效率, 从用户体验层面出发, 对诱导方案设计进行
深入研究. 提高用户体验有利于提高用户对诱导系统的服从率, 从而提高诱导效率 …

One of the famous examples in the study of route optimization in the field of computers is
Travelling Saleman Problem (TSP). Researches throughout the years various algorithms …

This paper proposes a data-driven distributionally robust shortest path (DRSP) model where
the distribution of the travel time is only observable through a finite training dataset. Our …

Ride-sharing is a promising solution for transportation issues such as traffic congestion and
parking land use, which are brought about by the extensive usage of private vehicles. In the …

Stress and anxiety are well known feelings for a car driver when it comes to finding a free on-
street parking spot in an urban area or estimating the time for punctual arrival at a certain …

Traffic and transportation are crucial to the sustainable development of most metropolitan
cities, where the stochastic shortest path (SSP) problem for vehicle routing is a challenging …