Best point detour query in road networks

Abstract

A point detour is a temporary deviation from a user preferred path P (not necessarily a shortest network path) for visiting a data point such as a supermarket or McDonald's. The goodness of a point detour can be measured by the additional traveling introduced, called point detour cost or simply detour cost. Given a preferred path to be traveling on, Best Point Detour (BPD) query aims to identify the point detour with the minimum detour cost. This problem can be frequently found in our daily life but is less studied. In this work, the efficient processing of BPD query is investigated with support of devised optimization techniques. Furthermore, we investigate continuous-BPD query with target at the scenario where the path to be traveling on continuously changes when a user is moving to the destination along the preferred path. The challenge of continuous-BPD query lies in finding a set of update locations which split P into partitions. In the same partition, the user has the same BPD. We process continuous-BPD query by running BPD queries in a deliberately planned strategy. The efficiency study reveals that the number of BPD queries executed is optimal. The efficiency of BPD query and continuous-BPD query processing has been verified by extensive experiments.

Collective Travel Planning in Spatial Networks

“…drop operation: if the size of A is greater than 1, when dropping a point p, we compute CT C(p) (lines [21][22][23][24]. Then, we precheck the validity of A.drop(p) by comparing the value of…”

Finding regions of interest using location based social media

“…As a variant of NN queries, Continuous Nearest Neighbor queries (CNN) [1,13,24,15,16] report the kNN results continuously while the user is moving along a path. This type of queries aims to find the split points on the query path where an update of the kNN is required, and thus to avoid unnecessary recomputation.…”

Effective and Efficient: Large-Scale Dynamic City Express

“…which means that the minimum incurred distance for the request r is ∆dist j (r, S i ) when we insert r into segment r i,j → r i,j+1 of c i 's schedule S i . We compute the initial priorities of requests in R (line [16][17][18][19], and assign the requests according to their priorities in H g (line [20][21][22][23][24][25][26][27][28]. The priority of a request r is the minimum ∆dist(r, S i ) among the schedules of all candidate couriers, which can be computed using the procedure BestR(r, cand(r)) (line 17).…”

“…We initialize the global priority queue H g and the local priority queue H i for each courier c i ∈ C (line 1-6). The initialization of H i is done in procedure InitH (line [20][21][22][23][24][25][26][27], which computes the candidate entries for c i and pushes each candidate along with the lower bound of its incurred distance into the priority queue. To initialize H g , we simply pop out the top element from each H i (line 5) and push it into H g (line 6).…”

“…The best point detour problem is proposed by Shang et al [23], which aims to find a detour that can pass a certain type of node with the minimum additional traveling cost. The best point detour problem is different from our problem studied in this paper since we aim at optimizing the route for multiple requests and multiple couriers in a dynamic environment.…”