Abstract
Bus rapid transit (BRT) has a great potential to improve the service level of transit system and has been implemented in many Chinese cities. However, the priority it can provide to buses has not been explored fully. Therefore, this study mainly investigated two advanced control strategies (signal priority using advanced detection and transit speed control). Signal priority using advanced detection is a strategy which detects one cycle ahead of buses’ arrival in order to adapt a more flexible control algorithm to provide signal priority for buses. Another is transit speed control, which provides priority at intersections for buses by controlling the speed of them and predicting their arrival at certain intersection. These two advanced strategies were modeled and evaluated using simulation software VISSIM and presented better performance than other three scenarios (base case, exclusive bus lane, and conventional transit signal priority). Only the eastbound direction would be researched as its traffic flow and bus volume are much larger than those of the other direction. Data used in this model was collected in Yingtan City. It is also shown that both the operation of BRT and the efficiency of private traffic can be much improved by applying the two strategies proposed above.
Highlights
Bus rapid transit (BRT) is a high-quality bus-based transit system that delivers fast, comfortable, and economical urban mobility through the provision of segregated right-of-way infrastructure, rapid and frequent operations, and excellence in marketing and customer service [1, 2]
Using VISSIM simulation software, we modeled Shengli avenue, which is an important corridor in the downtown area of Yingtan
With the help of data provided by the final report on urban transit planning of Yingtan (2011–2020) [20], we modeled Shengli avenue in VISSIM
Summary
Bus rapid transit (BRT) is a high-quality bus-based transit system that delivers fast, comfortable, and economical urban mobility through the provision of segregated right-of-way infrastructure, rapid and frequent operations, and excellence in marketing and customer service [1, 2]. Wang et al proposed a transit speed control strategy to dynamically control the operating speed of transit to make sure that it can arrive at intersections within certain time range so that preference treatment can be obtained [17] They recommended a near-side bus stop design at each intersection to accommodate to dwelling buses. Considering the feasibility of these strategies in China and the maneuverability in simulation, these strategies were not taken into account To evaluate these two advanced control strategies and to find out whether they really work, we modeled these two strategies using VISSIM in our study together with other three scenarios (base case, bus lane, and conventional TSP) as comparison.
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