This study introduces the novel concept of local detouredness, i.e. detours on subsections of a route, as a new phenomenon for understanding and modelling route choice. Traditionally, Stochastic User Equilibrium (SUE) traffic assignment models have been concerned with judging the attractiveness of a route by its total route cost. However, through empirical analysis we show that considering solely the global properties of a route is insufficient. We find that it is important to consider local detouredness both when determining realistic and tractable route choice sets and when determining route choice probabilities. For example, analysis of observed route choice data shows that route usage tends to decay with local detouredness, and that there is an apparent limit on the amount of local detouredness seen as acceptable. No existing models can account for this systematically and consistently, which is the motivation for the new route choice model proposed in this paper: the Bounded Choice Model with Local Detour Threshold (BCM-LDT). The BCM-LDT model incorporates the effect of local detouredness on route choice probability, and has an in-built mechanism that assigns zero probabilities to routes violating a bound on total route costs and/or a threshold on local detouredness. Thereby, the model consistently predicts which routes are used and unused. Moreover, the probability expression is closed-form and continuous. SUE conditions for the BCM-LDT are given, and solution existence is proven. Exploiting the special structure of the problem, a novel solution algorithm is proposed where flow averaging is integrated with a modified branch-and-bound method that iteratively column-generates all routes satisfying local and global bounds. Numerical experiments are conducted on small-scale and large-scale networks, establishing that equilibrated solutions can be found and demonstrating the influence of the BCM-LDT parameters on choice set size and flow allocation.

中文翻译：

---

局部绕行：对路线选择和交通分配进行建模的新现象


本研究引入了局部绕行的新概念，即在路线的小路段上绕行，作为理解和建模路线选择的新现象。传统上，随机用户均衡 （SUE） 流量分配模型一直关注通过路由的总成本来判断路由的吸引力。然而，通过实证分析，我们表明仅考虑路由的全局属性是不够的。我们发现，在确定现实和可处理的路线选择集以及确定路线选择概率时，考虑局部绕行性都很重要。例如，对观察到的路线选择数据的分析表明，路线使用量往往会随着本地绕道而衰减，并且被视为可接受的本地绕道数量存在明显限制。没有现有的模型可以系统、一致地解释这一点，这就是本文提出的新路线选择模型的动机：具有局部绕行阈值的有界选择模型 （BCM-LDT）。BCM-LDT 模型结合了本地绕行对路径选择概率的影响，并具有一个内置机制，该机制为违反总路径成本限制和/或本地绕行阈值的路径分配零概率。因此，该模型始终如一地预测哪些路由已使用和未使用。此外，概率表达式是封闭式和连续的。给出了 BCM-LDT 的 SUE 条件，并证明了解的存在。利用问题的特殊结构，提出了一种新的求解算法，其中流平均与改进的分支定界方法集成在一起，该方法迭代地列生成满足局部和全局边界的所有路由。 在小规模和大规模网络上进行了数值实验，确定了可以找到平衡解，并证明了 BCM-LDT 参数对选择集大小和流量分配的影响。