Geography Reference
In-Depth Information
On the basis of time geography theory (Hägerstrand
1970
), several approaches
(Yu and Shaw
2008
;Fangetal.
2011
; Chen and Kwan
2012
; Scott and He
2012
;
Yoon et al.
2012
;Shaw
2012
) have been proposed to identify an opportunity set of
activities which is able to support activity scheduling. These approaches focus on the
space-time constrained opportunities within the potential path area of a (dynamic)
transportation network. For example, Fang et al. (
2011
) defined a time-varying
network-based prism to identify the joint participation space of multiple people
within space and time dimensions. The opportunities within the joint participation
space constituted their candidate activity opportunities. Scott and He (
2012
)usedthe
potential path area to determine an individual's destination choice set for shopping.
Chen and Kwan (
2012
) proposed four models to identify the choice set with multiple
flexible activities under space-time constraints (Newell et al.
1994
; Sips et al.
2007
;
We n t z e t a l .
2010
; McQuoid and Dijst
2012
;Sui
2012
) confined by a space-time
movement environment (Hägerstrand
1970
; Lenntorp
1976
;Islam
2010
; Ellegård
and Svedin
2012
). These four models conceptualized trip-chaining behavior based
on a fixed set of activities and a fixed number of origin and destination stations.
Yoon et al. (
2012
) also confirmed that the space-time prism concept can account for
variations in choice sets.
However, the choice sets for activities limited by a space-time prism should
be investigated based on knowledge of the transportation network as well as of
time-space constraints. To accumulate transportation knowledge for urban man-
agement, many cities have equipped their transportation networks with various
sensors to collect plentiful video data and loop signals for future data mining.
Beside this traditional knowledge, trajectory data collected by Global Positioning
System (GPS)-equipped vehicles also provide much useful information for mining
transportation network knowledge, such as traffic speeds in occupied links and the
spatiotemporal frequency of often-used links. This kind of information can facilitate
activity scheduling by identifying critical links. Therefore, this chapter proposes
an approach which identifies critical links and opportunities for joint participation
based on analysis of GPS-recorded taxi trajectories within the framework of time
geography theory.
This chapter is organized as follows. In the next section, the dynamic network-
based space-time prism is reviewed. Then, in Sect.
7.3
, critical links and opportu-
nities are identified given the dynamic network-based space-time prism and vehicle
occupation and frequency data from the transportation network. A multi-objective
approach to scheduling the joint participation of multiple individuals is proposed
in Sect.
7.4
. Section
7.5
describes a scenario study demonstrating the feasibility of
identifying critical links and opportunities for scheduling multiple trips for multiple
people. Brief conclusions are drawn in Sect.
7.6
.
7.2
Dynamic Network-Based Space-Time Prism
A space-time prism representing a reachable space-time regime for individuals is
commonly used to identify available activity opportunities between a given set of
origins and destinations. To identify real-life available activity opportunities, several
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