RT Journal Article
A1 Peng Cao
A1 Zhandong Xu
A1 Qiaochu Fan
A1 Xiaobo Liu

PB iet
T1 Analysing driving efficiency of mandatory lane change decision for autonomous vehicles
JN IET Intelligent Transport Systems
VO 13
IS 3
SP 506
OP 514
AB Mandatory lane change (MLC) is a critical step in formulating global route of an autonomous vehicle on the urban road network. Improper MLC decisions on arterial roads could jeopardise efficiency (travel cost) and reliability (possibility of failed lane change). However, the existing research studies seldom investigate the optimal MLC decision at the planning level to maximise the reliability-based driving efficiency. This research aims at addressing two core strategic decision variables (MLC decision point on the road and maximum waiting time before giving up MLC). A series of simulation experiments for various scenarios are conducted for an arterial road to reveal their relationship. The results indicate that both identified decision variables inherently affect travel time spent on this road and the rate of failed MLCs, and a trade-off exists between arterial travel time and the rate of failed MLCs. Based on the simulation analysis, an analytical lane-level link performance (LLP) function is formulated to assess the impacts of MLC decisions on driving efficiency. The analysis validates that the optimal MLC strategic decision (MLC decision position and maximum waiting time) can be determined by maximising LLP function. It is promising to apply the proposed LLP function in lane-level routing algorithm in the future.
K1 MLC decision position
K1 arterial road
K1 planning level
K1 existing research studies
K1 analytical lane-level link performance function
K1 reliability-based
K1 arterial travel time
K1 optimal MLC strategic decision
K1 MLC decision point
K1 travel cost
K1 optimal MLC decision
K1 mandatory lane change decision
K1 critical step
K1 simulation experiments
K1 urban road network
K1 improper MLC decisions
K1 failed lane change
K1 driving efficiency
K1 failed MLCs
K1 simulation analysis
K1 maximum waiting time
K1 core strategic decision variables
K1 global route
K1 lane-level routing algorithm
K1 autonomous vehicle
DO https://doi.org/10.1049/iet-its.2018.5253
UL https://digital-library.theiet.org/;jsessionid=3kqtbee51tbgm.x-iet-live-01content/journals/10.1049/iet-its.2018.5253
LA English
SN 1751-956X
YR 2019
OL EN