The real-time kinematic differential Global Positioning System (GPS) has facilitated a new horizon in traffic engineering. Multiple car-following experiments conducted with a real-time kinematic GPS with 10 vehicles participating in a probing field gave high-quality results in headway, speed, relative speed, and acceleration. The expected accuracies for measuring position and speed were 10 mm and 0.16 km/h, respectively. The vehicles were driven in a loop consisting of two parallel straight sections connected by two semicircular curves. Different driving conditions were induced in the platoon by instructing the leading driver to follow predetermined speed variations. The experiments yielded sets of continuous observations. Headway, speed, and acceleration were measured using conventional equipment for the purpose of comparing accuracy. The accuracy of the data obtained using the GPS was superior to that of the same data obtained using conventional measurements. The variation in driving characteristics down the stream of vehicles was studied using the experimental data. The results showed that the reaction time between a change in relative speed and the corresponding change in acceleration varies during the driving process. The reaction time of individual drivers also changes along the platoon. The good-quality data were able to give high-resolution plots of acceleration and relative speed illustrating that both the reaction time and the functional relationship between acceleration and relative speed do not remain constant.

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The performance of six microscopic traffic flow models was investigated on the basis of how well these models fit with the real-time kinematic Global Positioning System (GPS) measurements. Ten passenger cars equipped with the GPS receivers participated in the car-following experiments, conducted at a test track. The genetic algorithm-based approach is adopted to optimize the model parameters for two different cases: using speed and headway data. The optimized performance of each model is analyzed for various driving conditions introduced by the different level of disturbances to the lead vehicle's speed, which include half-wave, one-wave, two-wave, three-wave, random, and constant speed patterns. In the former case with speed data, five models performed well with the average percentile error ranging from 3.87% to 4.71% and standard deviation ranging from 1.09% to 1.64%. In the latter case with headway data, only three models performed well with the average percentile error ranging from 12.04% to 12.91% and standard deviation ranging from 4.53% to 5.13%. All models performed better in the former case than in the latter case. The interpersonal variations are significant compared with the intermodel variations and indicate individual drivers' influence on the car-following phenomena.

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At 00:02 on 14th November 2016, a Mw 7.8 earthquake occurred in and offshore of the northeast of the South Island of New Zealand. Fault rupture, ground shaking, liquefaction, and co-seismic landslides caused severe damage to distributed infrastructure, and particularly transportation networks; large segments of the country’s main highway, State Highway 1 (SH1), and the Main North Line (MNL) railway line, were damaged between Picton and Christchurch. The damage caused direct local impacts, including isolation of communities, and wider regional impacts, including disruption of supply chains. Adaptive measures have ensured immediate continued regional transport of goods and people. Air and sea transport increased quickly, both for emergency response and to ensure routine transport of goods. Road diversions have also allowed critical connections to remain operable. This effective response to regional transport challenges allowed Civil Defence Emergency Management to quickly prioritise access to isolated settlements, all of which had road access 23 days after the earthquake. However, 100 days after the earthquake, critical segments of SH1 and the MNL remain closed and their ongoing repairs are a serious national strategic, as well as local, concern. This paper presents the impacts on South Island transport infrastructure, and subsequent management through the emergency response and early recovery phases, during the first 100 days following the initial earthquake, and highlights lessons for transportation system resilience.