The　scientific　assessment　of　the　levels　of　bus　service　is　a　prerequisite　for　optimizing　bus　system　performance,　as　it　provides　directions　for　policy　formulation　and　guiding　improvements　in　management　measures.　The　assessment　has　significant　importance　in　promoting　the　prioritized　development　of　public　transport.　As　the　overall　level　of　the　bus　system　is　not　fully　shown　because　of　the　single　evaluation　dimension,　this　study　introduced　the　latest　domestic　and　international　research　on　the　operational　efficiency,　operational　service　quality,　satisfaction,　and　intelligence　of　bus　systems.　The　study　discussed　the　scientific　challenges　in　evaluating　bus　operational　efficiency　and　service　quality,　covering　aspects　such　as　the　optimization　of　timetables,　selection　of　efficiency　evaluation　metrics,　reduction　of　metric　subjectivity,　definition　of　target　groups,　and　selection　of　research　perspectives.　It　categorized　and　outlined　the　content　and　models　used　to　evaluate　bus　operation　efficiency　and　operational　service　quality.　When　evaluating　operational　efficiency,　the　focus　is　on　metrics　related　to　bus　lines　and　networks,　whereas　the　evaluation　of　operational　service　quality　focuses　on　metrics　associated　with　infrastructure.　Satisfaction　evaluation　primarily　incorporates　metrics　related　to　passengers,　whereas　data　processing　and　information　service　capabilities　are　primarily　considered　when　evaluating　intelligence.　This　study　analyzed　the　similarities　and　differences　in　metric　selection　across　various　evaluation　dimensions　and　explored　the　impact　of　the　interaction　between　crossed　metrics　on　the　comprehensive　evaluation　of　the　system.　Finally,　the　following　directions　for　future　research　are　proposed.　When　building　a　bus　service　evaluation　system,　the　enterprises,　governments,　and　passengers　should　be　considered　to　enhance　the　completeness　of　the　evaluation　system.　During　the　evaluation　process,　it　is　necessary　to　emphasize　the　characteristics　of　multimode　transportation.　Factors　such　as　system　collaboration,　networking,　and　intelligence　should　serve　as　key　metrics.　In　addition,　it　is　crucial　to　consider　the　regional　characteristics　of　the　city　and　the　features　of　travel　demand.　In　alignment　with　technological　innovation　and　industry　development　trends,　corresponding　metrics　need　to　be　constructed　for　diversified　bus　operation　modes,　such　as　community　buses,　barrier-free　buses,　demand-responsive　buses,　public　transport　emergency　service　levels,　and　green　travel.　©　2024　Southwest　Jiaotong　University.　All　rights　reserved.